BIOLOGICAL FIELD STATIONBIOLOGICAL FIELD STATION Cooperstown, New York 44th ANNUAL REPORT 2011 BFS Upper Site (Moe Pond) Research Laboratory, now under renovation STATE UNIVERSITY

BIOLOGICAL FIELD STATION Cooperstown, New York 44th ANNUAL REPORT 2011

BFS Upper Site (Moe Pond) Research Laboratory, now under renovation

STATE UNIVERSITY OF NEW YORK COLLEGE AT ONEONTA

OCCASIONAL PAPERS PUBLISHED BY THE BIOLOGICAL FIELD STATION

No. 1. The diet and feeding habits of the terrestrial stage of the common newt, Notophthalmus viridescens (Raf.). M.C. MacNamara, April 1976

No. 2. The relationship of age, growth and food habits to the relative success of the whitefish (Coregonus clupeaformis) and the cisco (C. artedi) in Otsego Lake, New York. A.J. Newell, April 1976.

No. 3. A basic limnology of Otsego Lake (Summary of research 1968-75). W. N. Harman and L. P. Sohacki, June 1976. No. 4. An ecology of the Unionidae of Otsego Lake with special references to the immature stages. G. P. Weir, November 1977. No. 5. A history and description of the Biological Field Station (1966-1977). W. N. Harman, November 1977. No. 6. The distribution and ecology of the aquatic molluscan fauna of the Black River drainage basin in northern New York. D. E Buckley,

April 1977. No. 7. The fishes of Otsego Lake. R. C. MacWatters, May 1980. No. 8. The ecology of the aquatic macrophytes of Rat Cove, Otsego Lake, N.Y. F. A Vertucci, W. N. Harman and J. H. Peverly, December

1981. No. 9. Pictorial keys to the aquatic mollusks of the upper Susquehanna. W. N. Harman, April 1982. No. 10. The dragonflies and damselflies (Odonata: Anisoptera and Zygoptera) of Otsego County, New York with illustrated keys to the

genera and species. L.S. House III, September 1982. No. 11. Some aspects of predator recognition and anti-predator behavior in the Black-capped chickadee (Parus atricapillus). A. Kevin

Gleason, November 1982. No. 12. Mating, aggression, and cement gland development in the crayfish, Cambarus bartoni. Richard E. Thomas, Jr., February 1983. No. 13. The systematics and ecology of Najadicola ingens (Koenike 1896) (Acarina: Hydrachnida) in Otsego Lake, New York. Thomas

Simmons, April 1983. No. 14. Hibernating bat populations in eastern New York State. Donald B. Clark, June 1983. No. 15. The fishes of Otsego Lake (2nd edition). R. C MacWatters, July 1983. No. 16. The effect of the internal seiche on zooplankton distribution in Lake Otsego. J. K. Hill, October 1983. No. 17. The potential use of wood as a supplemental energy source for Otsego County, New York: A preliminary examination. Edward M.

Mathieu, February 1984. No. 18. Ecological determinants of distribution for several small mammals: A central New York perspective. Daniel Osenni, November 1984. No. 19. A self-guided tour of Goodyear Swamp Sanctuary. W. N. Harman and B. Higgins, February 1986. No. 20. The Chironomidae of Otsego Lake with keys to the immature stages of the subfamilies Tanypodinae and Diamesinae (Diptera). J. P.

Fagnani and W. N. Harman, August 1987. No. 21. The aquatic invertebrates of Goodyear Swamp Sanctuary, Otsego Lake, Otsego County, New York. Robert J. Montione, April 1989. No. 22. The lake book: a guide to reducing water pollution at home. Otsego Lake Watershed Planning Report #1. W. N. Harman, March

1990. No. 23. A model land use plan for the Otsego Lake Watershed. Phase II: The chemical limnology and water quality of Otsego Lake, New

York. Otsego Lake Watershed Planning Report Nos. 2a, 2b. T. J. Iannuzzi, January 1991. No. 24. The biology, invasion and control of the Zebra Mussel (Dreissena polymorpha) in North America. Otsego Lake Watershed Planning

Report No. 3. Leann Maxwell, February 1992. No. 25. Biological Field Station safety and health manuel. W. N. Harman, May 1997. No. 26. Quantitative analysis of periphyton biomass and identification of periphyton in the tributaries of Otsego Lake, NY in relation to

selected environmental parameters. S. H. Komorosky, July 1994. No. 27. A limnological and biological survey of Weaver Lake, Herkimer County, New York. C.A. McArthur, August 1995. No. 28. Nested subsets of songbirds in Upstate New York woodlots. D. Dempsey, March 1996. No. 29. Hydrological and nutrient budgets for Otsego lake, N. Y. and relationships between land form/use and export rates of its sub -basins.

M. F. Albright, L. P. Sohacki, W. N. Harman, June 1996. No. 30. The State of Otsego Lake 1936-1996. W. N. Harman, L. P. Sohacki, M. F. Albright, January 1997. No. 31. A Self-guided tour of Goodyear Swamp Sanctuary. W. N. Harman and B. Higgins (Revised by J. Lopez),1998. No. 32. Alewives in Otsego Lake N. Y.: A Comparison of their direct and indirect mechanisms of impact on transparency and Chlorophyll a.

D. M. Warner, December 1999. No.33. Moe Pond limnology and fish population biology: An ecosystem approach. C. Mead McCoy, C. P. Madenjian, V. J. Adams, W.

N. Harman, D. M. Warner, M. F. Albright and L. P. Sohacki, January 2000. No. 34. Trout movements on Delaware River System tail-waters in New York State. Scott D. Stanton, September 2000. No. 35. Geochemistry of surface and subsurface water flow in the Otsego lake basin, Otsego County New York. Andrew R. Fetterman, June

2001. No. 36 A fisheries survey of Peck Lake, Fulton County, New York. Laurie A. Trotta. June 2002. No. 37 Plans for the programmatic use and management of the State University of New York College at Oneonta Biological Field Station

upland natural resources, Willard N. Harman. May 2003. No. 38. Biocontrol of Eurasian water-milfoil in central New York State: Myriophyllum spicatum L., its insect herbivores and associated fish.

Paul H. Lord. August 2004. No. 39. The benthic macroinvertebrates of Butternut Creek, Otsego County, New York. Michael F. Stensland. June 2005. No. 40. Re-introduction of walleye to Otsego Lake: re-establishing a fishery and subsequent influences of a top Predator. Mark D. Cornwell.

September 2005. No. 41. 1. The role of small lake-outlet streams in the dispersal of zebra mussel (Dreissena polymorpha) veligers in the upper Susquehanna

River basin in New York. 2. Eaton Brook Reservoir boaters: Habits, zebra mussel awareness, and adult zebra mussel dispersal via boater. Michael S. Gray.

No. 42. The behavior of lake trout, Salvelinus namaycush (Walbaum, 1972) in Otsego Lake: A documentation of the strains, movements and the natural reproduction of lake trout under present conditions. Wesley T. Tibbitts.

No. 43. The Upper Susquehanna watershed project: A fusion of science and pedagogy. Todd Paternoster. No. 44. Water chestnut (Trapa natans L.) infestation in the Susquehanna River watershed: Population assessment, control, and effects.

Willow Eyres. No. 45. The use of radium isotopes and water chemistry to determine patterns of groundwater recharge to Otsego Lake, Otsego County, New

York. Elias J. Maskal. Annual Reports and Technical Reports published by the Biological Field Station are available from Willard N. Harman, BFS, 5838 St. Hwy. 80, Cooperstown, NY 13326.

44th ANNUAL REPORT 2011

BIOLOGICAL FIELD STATION COOPERSTOWN, NEW YORK

bfs.oneonta.edu

STATE UNIVERSITY COLLEGE AT ONEONTA

The information contained herein may not be reproduced without permission of

the author(s) or the SUNY Oneonta Biological Field Station

BFS 2011 ANNUAL REPORT CONTENTS

INTRODUCTION: W. N. Harman…………………………………………………………………...….1

ONGOING STUDIES:

OTSEGO LAKE WATERSHED MONITORING:

2011 Otsego Lake water levels. W.N. Harman and M.F. Albright………………………..6

Otsego Lake limnological monitoring, 2011. H.A. Waterfield and M.F. Albright..……9

A survey of Otsego Lake’s zooplankton community, summer 2011.

M.F. Albright and O. Zaengle………………………………………..…….…..20

Chlorophyll a analysis of Otsego Lake, summer 2011. A. Levenstein……....................29

Water quality monitoring of five major tributaries in the Otsego Lake

watershed, summer 2011. O. Zaengle………………………………………….35

Preliminary investigations of organic and inorganic carbon content of the

Otsego Lake watershed, summer 2011. G.W. Badger………………………...47

SUSQUEHANNA RIVER MONITORING:

Monitoring the water quality and fecal coliform bacteria in the upper

Susquehanna River, summer 2011. B. Scott...…………………..…….……….59

ARTHROPOD MONITORING:

Mosquito Studies- Thayer Farm. W.L. Butts……………………………………………73

REPORTS:

Monitoring the effectiveness of the Cooperstown wastewater treatment

wetland, 2011. M.F. Albright.…………………………..……………………..……….74

Efficacy of emergent plants as a means of phosphorus removal in a treatment

wetland, Cooperstown, New York. E. Gazzetti…………………………….………….82

Insight into a complex system: Cooperstown wastewater treatment wetland, 2011.

T. Robb……………………………………………………………………………………90

Treatment performance of advanced onsite wastewater treatment systems in the

Otsego Lake watershed, 2008-2011. H.A. Waterfield……………………………….108

Baseline water quality assessment of aquatic benthic macroinvertebrates in streams

prior to natural gas extraction; Otsego County, NY. K. Whitcomb …...……………122

Microfaunal community on lichens, Otsego County NY. B.P. German…………………….132

Alewife (Alosa psuedoharengus) density as a predictor of open water utilization by

walleye (Sander vitreus) in Otsego Lake, NY. B.E. Bowers………………………..140

Summer 2011 trap net monitoring of fish communities utilizing the weedy littoral

zone at Rat Cove and rocky littoral zone Brookwood Point, Otsego Lake

B.P. German……………………………………………………………………………146

Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 2011.

H.A. Waterfield and M.D. Cornwell…………………………………………………….152

Monitoring the dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria)

in the Goodyear Swamp Sanctuary, summer 2011. M.F. Albright………………….158

Afton Lake water quality, nutrients and algae. Harman, W.N., M.F. Albright and

H.A. Waterfield…………………………………………………………………………164

Laurel Lake water quality, nutrients, and algae, summer 2011. H.A. Waterfield,

W.N. Harman and M.F. Albright………………………………………………………169

2011 Catskill region aquatic nuisance species survey for the Catskill Center for

Conservation and Development. W.N. Harman………………………………………175

2011 pearly mussel surveys of portions of the Catatonk Creek, Butternut Creek

and Unadilla River. P.H. Lord and T.N. Pokorny………………………………………185

Drainage basin size as a predictor of fish species richness in the Otsego

Lake watershed. J.R. Foster and R. Lewis………………………………………….192

Spine punching: An effective way of marking spiny-rayed fish.

A. Bruno, J.R. Foster and J.C. Lydon………………………………………………..198

DEC Invasive Species Eradication and Control Grant final report. W.N. Harman,

H.A. Waterfield and M.F. Albright………………………………………………………205

Intestinal damage in locally occurring game fish infected with the acanthocephalan,

Leptorhynchoides thecatus. F.B. Reyda, C. Lange, J. Sheehan, U. Habal,

D. Willsey, L. Laraque, and M. O’Rourke…………………………………………..208

TECHNICAL REPORTS:

BFS Technical Report #31. Aquatic macrophyte management plan facilitation,

Lake Moraine, Madison County, NY, 2011. W.N. Harman, M.F. Albright

and O. Zaengle…………………………………………….…………………………….214

INTRODUCTION

Willard N. Harman

Internships and research assistants:

College undergraduate intern Owen Zaengle, from SUNY ESF measured water quality at 23

sites on tributaries throughout the Otsego Lake watershed. He also helped with plant management

strategies on Moraine Lake and removal of the exotic marsh thistle from Greenwoods Conservancy and

additional terrestrial sites. He was supported in part by the Catskill Regional Invasive Species

Partnership (CRISP), the Lake Moraine Association and the Peterson Family Charitable Trust (PFCT).

Benjamin German, from SUNY Cobleskill, held the Robert C. MacWatters Internship in the Aquatic

Sciences sponsored by SUNY Cobleskill and the BFS. He conducted the annual warm water fisheries

surveys at Brookwood Point and Rat Cove in Otsego Lake and investigated the meiofaunal community

on selected lichens. The latter work was supported in part by the PFTC. In addition, several SUNY

Cobleskill students, under Dr. John Foster’s supervision, conducted fisheries studies on Otsego Lake

and its watershed. Gilbert Badger, from SUNY Oneonta, sponsored by the OCCA, held a Rufus J.

Thayer Otsego Lake Research internship and monitored both organic and inorganic carbon at 23 sites

throughout the Otsego Lake watershed using a carbon analyzer recently acquired via an NSF grant.

Katherine Whitcomb, from SUNY Oneonta, was awarded a SUNY Oneonta Biology Department

internship supported by the OCCA. She conducted macroinvertebrate surveys in streams across Otsego

County to indicate pre-gas extraction surface water conditions. Tyson Rob, from SUNY Oneonta, was

given a BFS Internship. Sponsored by the Village of Cooperstown, he developed a bathymetric map of

the Village treatment wetland and evaluated nutrient and brightener movement through that system.

Edward Gazzetti, from SUNY Oneonta, received a BFS internship sponsored in part by CRISP. He

evaluated phosphorus content in cattail and reed canary grass in the Cooperstown wastewater treatment

wetland and a nearby control wetland. Bradley Bowers, from SUNY Cobleskill, used hydro-acoustic

data to evaluate overlap of habitat utilization of alewife and walleye. He was supported by the OCCA.

Alex Levenstein from Oneonta High School monitored chlorophylla concentrations in Otsego Lake. He

received a FHV Mecklenburg Conservation Internship sponsored by the OCCA. Brandt Scott, funded

by the Village of Cooperstown, monitored water quality in the Upper Susquehanna River. The following

students worked with Dr. Florian Reyda on fish parasites as described below: Michael O’Rourke,

Umrhan Habal, Danielle Willsey, Jason Sheehan, Cary Lange and Andrew Diagler.

Intensive offerings:

About 200 students enrolled in several SUNY Oneonta and SUNY Cobleskill on-campus courses

and attended field exercises on site. More than 1,000 K-12 students visited the BFS and received hands-

on experiences on Otsego Lake and BFS woodlands over the year enrolled in the pre-college “Learning

Adventures” and “Agricultural Environmental Quality” programs. Brad Bowers and Ben German

served as interpreters under the direction of Holly Waterfield.

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Faculty and staff activities:

Holly Waterfield has been collaborating with Mark Cornwell, SUNY Cobleskill, as they have

continued to utilize acoustic monitoring to document alewife population dynamics in Otsego Lake. She

and Matt Albright finalized work on a project, supported by a DEC grant, on phosphorus control

strategies related to onsite wastewater systems. For the 12th

year, we stocked Otsego Lake with walleye

fingerlings. Monitoring was continued by Holly, with advice and help from Lars Rudstam, Tom

Brooking (Cornell BFS) and Dave Warner (USGS Great Lakes Research Center, Ann Arbor)

evaluating the impacts on both the fishery, and with Matt Albright, impacts on water quality and trophic

cascades. Holly has also been collaborating with Lars Rudstam on a software comparison to further

refine analysis procedures for hydroacoustic data. Mark Cornwell and John Foster, SUNY Cobleskill,

were involved in fisheries research related to the walleye/alewife acoustic work including tracking of

several mature walleye in Otsego Lake over the year. Matt Albright, in fulfilling his responsibilities as

laboratory supervisor and coordinator of staff and intern activities was deeply involved in all BFS

activities. Dr. Jeff Heilveil taught an intensive field entomology course during the summer, the first

summer course housed entirely at the BFS. As part of the course, students produced a curated insect

collection for some of the BFS properties. Advising the SUNY Oneonta Biology Club, he conducted a

“taxonomic excursion” and camping event in the fall.

Matt Albright and Holly Waterfield became Certified Lake Managers (CLM) by the

North American Lake Management Sociality. The certification was associated with the Biology

Department’s development of the first so named Master of Science Degree in Lake Management

in the country. Holly Waterfield, Matt Albright and Bill Harman attended NALMS Annual

Meetings in Spokane, Washington. All coauthored papers on BFS research. Holly attended the

NALMS Board of Directors meeting as Regional Director. She also attended biannual Board

meetings in Denver. We attended and presented at the New York State Federation of Lake

Associations (NYS FOLA) meetings in Hamilton, NY. Matt and Bill are NYSFOLA Directors.

Holly attended and presented at the Northeast Natural History Conference in Albany, NY.

Florian and Matt were involved with the Earth Day events at SUCO, and Florian presented at

the Faculty Research Show.

The State of Canadarago Lake report was recently finalized. Under the authorship of

Matt and Holly, it relied on contributions by a number of interns involved at the BFS between

2008 and 2010. It, a multi-sponsored effort contracted through the Otsego County Soil and Water

Conservation District, is available on the publication page of our web site.

Paul Lord and Timothy Pokorny completed their DEC sponsored surveys of pearly

mussels in Catatonk Creek, Butternut Creek and the Unadilla River. Four species of greatest

conservation need were documented.

Drs. Nigel Mann, Donna Vogler and RP Withington conducted field trips in Biol 282,

282, General Ecology, on Otsego Lake in September. Nigel made four visits to the Thayer Farm

and Rum Hill properties in spring 2011, to look for suitable sites for mist-netting as part of the

Monitoring Avian Populations (MAPS) program. He visited the construction site for the new

ornithology facility at Upper Site to discuss the progress and design of the building work. He

2

intends to start contributing to this program in 2013 and, given the development of the new

facility at the Upper site, probably will use that area instead.

Florian Reyda and four of his students, Michael O’Rourke, Umrhan Habal and

Danielle Willsey, did a study last spring of the histopathology (tissue damage) caused by a

commonly occurring fish parasite in Otsego Lake. Their study focused on the damage caused to

yellow perch by the thorny-headed worm Leptorhynchiodes thecatus. There were many technical

challenges in the project involving obtaining cross-sections of parasites attached to host intestinal

wall. This effort was continued in the fall by Reyda and two other students, Jason Sheehan and

Cary Lange, who examined the damage caused by that parasite to smallmouth bass form the

lake. These works provided documentation of the damage that L. thecatus causes to these locally

important game fish species. In addition, Dr. Reyda has continued his collaborative work on

stingray tapeworms, in which two different students, Danielle Willsey and Andrew Daigler

each described a new species of tapeworm. The latter two studies were done with the aid of new

research grade compound scope in the Main Laboratory that enables digital imaging as well as

scientific illustration.

We conducted the fifth year of work involving water chestnut control in a wetland near Oneonta,

supported by a DEC Exotic Species Eradication grant of $29,000. We are also assisting the OCCA and

their citizen volunteers in the control of water chestnut in Goodyear Lake, also supported by the DEC.

Several small externally funded contracts have been renewed. The Village of Cooperstown has

sponsored BFS efforts to evaluate nutrient removal efficiency of a treatment wetland which began

receiving treated effluent in June 2010. A $10,000 contract with the Catskill Regional Invasive Species

Partnership supported a survey of the aquatic invasives in the region. We continue to administer two

National Science foundation proposals, one for over $400,000, to renovate the Upper Site Field

Research laboratory (see front cover) and another for over $100,000 for a diversity of equipment and

construction of weirs in headwater streams at the Thayer Farm to refine nutrient loading draining into

Otsego Lake.

Jeane Bennett-O’Dea continues to work part-time in the office assisting with administrative

tasks. Because of recent changes processing finances in the Oneonta Foundation, the SUNY Research

Foundation and funding associated with Thayer Farm renovations, her workload has greatly increased.

Several talented citizen volunteers again helped at the BFS during the year. Kathy Ernst continues to

assist us with computer graphics.

The Biological Filed Station Volunteer divers support the BFS and Otsego Lake in

twelve months of every year. From April through June the team deploys no-wake zone buoys

(NWZBs) around Otsego Lake and retrieves spar buoys. From May through October the team

regularly opens the water intake gate for the Village of Cooperstown’s water supply to allow

scrubbing of the interior of that line. From September through December the team retrieves

NWZBs around Otsego Lake deploying spar buoys. The team maintains buoy systems all year

and performs underwater sampling as required. Additionally, the team retrieves BFS equipment

lost in the lake as required and trains continuously for diving in all local conditions.

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Active Members of SUNY-Oneonta Biological Field Station's Volunteer Dive Team:

Jim Vogler: Open Water SCUBA Instructor. Jim has been diving with us for the last

four years & assists Paul Lord with all aspects of BFS diving. He is the first of the BFS

volunteer divers to earn a dive leadership certification. Jim works for the biology department at

SUNY-Oneonta and is married to Donna Vogler, biology professor at SUNY

Oneonta.

Dale Webster: Master SCUBA Diver; 14th year as volunteer diver; Dale's request to

become involved with BFS research through diving prompted establishment of the team in 1998.

Dale is works on campus as a carpenter and sells real estate.

Lee Ferrara: Master SCUBA Diver; 12th year as volunteer diver. Lee is a high

school science teacher in Oneonta.

Ed Lentz: Rescue & Ice Diver. Ed has been diving with us for the last six years and

still does ice dives in a wetsuit. Ed is a patent attorney and a past recipient of the OCCA

conservationist of the year award.

Bjorn (BJ) Eilertsen: Rescue, Multilevel, & Ice Diver. BJ has been diving with the

BFS for the last four years. He owns and manages a construction company.

Joseph W. Zarzynski: underwater archaeologist, scientific diver, author, and

educator. “Zarr” has been diving with us for the past two years and is currently involving

the team in a side-scan sonar investigation of Otsego Lake.

Krista Ransier: currently working on requirements for divemaster certification.

Krista is a student at Milford High School and started diving with us in 2011.

Robert Eklund, Jr: Advanced Open Water Diver and nitrox divers. Bob has been

diving with us for the past two years.

Simon Thorpe: is an Advanced Open Water Diver. Simon has been diving with us

for the past two years.

Antonio Carrasquillo: Open Water Diver: Tends for team and operates a personal

services business.

Wayne Bunn: recently retired civil engineer and NYS certified boat operator. Wayne

tends for the team.

Jeremiah Wood: Recently completed academic and pool training for SCUBA

certification. Jeremiah tends for then team.

Master SCUBA divers all have Advanced & Rescue training and training in at least

five specialty diving areas. Our Master SCUBA divers are all ice, deep, & night trained. Their

other training includes a mix of search and recovery, drift diving, multilevel diving, altitude

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diving, dry suit diving, wreck diving, boat diving, buoyancy diving, & equipment specialist.

Public support makes our work possible. Funding for BFS research and educational programs

was procured in 2011 from many citizens and organizations. Special thanks go to the Clark Foundation

who generously supports our annual needs. The OCCA, the Peterson Family Charitable Trust, Otsego

2000, the Village of Cooperstown, the Otsego Lake Association, SUNY Oneonta, and the SUNY

Graduate Research Initiative have also supported our endeavors. Consulting services on a diversity of

small lakes contributes to our annual income.

Willard N. Harman

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ONGOING STUDIES:

OTSEGO LAKE WATERSHED MONITORING:

2011 Otsego Lake water levels

W.N. Harman and M.F. Albright

Over the course of 2011, the record of water levels on Otsego Lake collected at the BFS were incomplete and patchy due to our transition from the Thayer Farm back to the main lab near Cooperstown. To address this, we communicated with personnel at the Village of Cooperstown’s Water Treatment Plant, where water levels are recorded daily so that discharge of the Susquehanna River over the dam at Mill Street can be calculated. When conducting this exercise, we recognized that since water level at Mill Street needs to be “corrected” to approximate that of the lake itself, it would be interesting to compare values recorded there with concurrent values where available. (Levels at the dam are influenced by the river’s slope between the lake proper and the dam, a distance of approximately 0.8 km (0.5 mi), and river discharge, which is dependent upon the configuration of the boards at the outlet device). Figure 1 graphically provides the relationship between the lake level (above mean sea level; 364.1 m) collected by BFS at Rat Cove with those collected by the Village of Cooperstown (VOC) at the outlet. Figure 2 provides lake levels collected at both locations over 2011. Lines connecting dates with missing records in the BFS dataset may miss true daily changes.

y = 0.8587x + 1.3056R² = 0.9015

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Figure 1. Comparison of Otsego Lake levels, above mean sea level (364.1 m), collected at Rat Cove by the Biological Field Station and at the lake’s outlet, collected by the Village of Cooperstown.

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Figure 2. 2011 Otsego Lake levels recorded at collected at Rat Cove by the Biological Field Station and at lake’s outlet, collected by the Village of Cooperstown.

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Figure 2 (cont.). 2011 Otsego Lake levels recorded at collected at Rat Cove by the Biological Field Station and at lake’s outlet, collected by the Village of Cooperstown.

8

Otsego Lake limnological monitoring, 2011

Holly A. Waterfield and Matthew F. Albright

INTRODUCTION

Otsego Lake is a glacially formed, dimictic lake (max depth 51m) supporting a cold water fishery. The Lake is generally classified as being chemically mesotrophic, although flora and fauna characteristically associated with oligotrophic lakes are present (Iannuzzi, 1992). This study is the continuation of a year-round monitoring protocol that began in 1991. The data collected in this report run for the calendar year and are comparable with contributions by Homburger and Buttigieg (1992), Groff et al. (1993), Harman (1994; 1995), Austin et al. (1996), Albright (1997; 1998; 1999; 2000; 2001; 2002; 2003; 2004; 2005; 2006; 2007; 2008), Albright and Waterfield (2009), and Waterfield and Albright (2010; 2011). Concurrent additional work related to Otsego Lake included estimates of fluvial nutrient inputs (Zaengle 2012), and descriptions of the zooplankton community (Albright and Zaengle 2012), chlorophyll a (Levenstein 2012), and nekton communities (German 2012; Bowers 2012; Waterfield and Cornwell 2012).

MATERIALS AND METHODS Physiochemical data and water samples were collected near the deepest part of the lake (TR4-C) (Figure 1), which is considered representative of whole-lake conditions, as past studies have shown the Lake to be spatially homogenous with respect to the factors under study (Iannuzzi 1991). Data and sample collection occurred bi-weekly during open water conditions, May through December. Sampling was conducted on 17 February through the ice. Samples were not collected in March or April due to marginal ice conditions. Physical measurements were recorded at 2-m intervals between 0 and 20 m and 40 m to the bottom; 5-meter intervals were used between 20 and 40 m. Measurements of pH, temperature, dissolved oxygen and conductivity were recorded with the use of a YSI® 650 MDS with a 6-Series multiparameter sonde which had been calibrated according to the manufacturer’s instructions prior to use (YSI Inc. 2009). This was the first year that an optical dissolved oxygen probe was used (as opposed to a Clark cell type). Samples were collected for chemical analyses at 4-m intervals between 0 and 20 m and 40m and 48m; 10-m intervals were used between 20 and 40 m. A summary of methodologies employed for sample preservation and chemical analyses is given in Table 1.

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Figure 1. Bathymetric map of Otsego Lake showing sampling site (TR4-C).

TR4-C

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Parameter Preservation Method Reference

Total Phosphorus H2SO4 to pH < 2Persulfate digestion followed by single reagent ascorbic acid Liao and Marten 2001

Total Nitrogen H2SO4 to pH < 2Cadmium reduction method following peroxodisulfate digestion

Pritzlaff 2003; Ebina et al. 1983

Nitrate+nitrite-N H2SO4 to pH < 2 Cadmium reduction method Pritzlaff 2003Ammonia-N H2SO4 to pH < 2 Phenolate method Liao 2001

Calcium Store at 4oC EDTA trimetric method EPA 1983Chloride Store at 4oC Mercuric nitrate titration APHA 1989Alkalinity Store at 4oC Titration to pH= 4.6 APHA 1989

Table 1. Summary of laboratory methodologies.

RESULTS AND DISCUSSION

Temperature Figures 2a and 2b depict temperatures measured in profile (0 to 48m) at site TR4-C from 6 January through 26 July and 8 August through 22 December 2011, respectively. Surface temperature ranged from 0.46oC below the ice on 17 February to 25.4oC at the surface on 26 July. Temperatures at 48m reached the annual minimum of 2.93oC on 6 January. Ice went off the lake on 12 April; spring turnover occurred between then and 3 May. Thermal stratification was evident by 18 May. Surface temperatures began to decrease after the profile collected 26 July and the thermocline occurred at greater depth until fall turnover, which occurred in late December (Figure 2b). Dissolved Oxygen

Isopleths of oxygen concentration based on the profiles for the calendar year are presented in Figure 3. On 5 April, prior to the onset of thermal stratification (May), dissolved oxygen was between 11.34 mg/l (at 48m) and 11.80 mg/l (at the surface). The minimum observed DO concentration was 4.59 mg/l recorded on 22 November at 48m. This is the highest minimum, late season, bottom concentration recorded since 1988 (Iannuzzi 1991). This compares to a minima bottom concentration in 2010 of 3.25 mg/l on 26 October. In most years between 1995 and 2009, the bottom minimum was near or below 1.0 mg/l. The areal hypolimnetic oxygen depletion rate (AHOD), calculated at 0.060 mg/cm2/day, remains well below the historical average (Table 2).

11

2a.

2b.

Figure 2. Otsego Lake temperature profiles (oC) observed at TR4-C between 6 January and 26 July (2a) and 8 August and 22 December (2b) 2011. Table 2

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25D

epth

(met

ers)

Temperature (oC)

1/6/2011

2/17/2011

5/3/2011

5/18/2011

6/1/2011

6/15/2011

6/28/2011

7/13/2011

7/26/2011

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25

Dep

th (m

eter

s)

Temperature (oC)

8/8/2011

8/24/2011

9/9/2011

9/27/2011

10/12/2011

11/2/2011

11/22/2011

12/5/2011

12/22/2011

12

Table 2. Areal hypolimnetic oxygen deficits (AHOD) for Otsego Lake, computed over summer stratification in 1969, 1972 (Sohacki, unpubl.), 1988 (Iannuzzi, 1991), and 1992-2011.

Time Interval AHOD (mg/cm2/day) 05/16/69 - 09/27/69 0.080 05/30/72 - 10/14/72 0.076 05/12/88 - 10/06/88 0.042 05/18/92 - 09/29/92 0.091 05/10/93 - 09/27/93 0.096 05/17/94 - 09/20/94 0.096 05/19/95 - 10/10/95 0.102 05/14/96 - 09/17/96 0.090 05/08/97 - 09/25/97 0.101 05/15/98 - 09/17/98 0.095 05/20/99 - 09/27/99 0.095 05/11/00 - 09/14/00 0.109 05/17/01 - 09/13/01 0.092 05/15/02 - 09/26/02 0.087 05/16/03 - 09/18/03 0.087 05/20/04 - 09/24/04 0.102 05/27/05 - 10/05/05 0.085 05/4/06 - 09/26/06 0.084 05/18/07 - 9/27/07 0.083 05/8/08 - 10/7/08 0.088

05/27/09 - 10/19/09 0.082 05/26/10 - 10/7/10 0.053

05/19/11 – 10/12/11 0.060 Calcium

Calcium concentrations followed a typical seasonal pattern of fluctuation similar to that of alkalinity. Mean annual concentration at TR4-C was 50.0 mg/l, ranging from 44.1 mg/l at 4m on 9 September to 52.9 mg/l at the bottom on 22 November. Chlorides

Mean chloride concentrations in Otsego Lake from 1925 to 2011 are shown in Figure 4. Between 1994 and 2005 mean concentration increased steadily at of rate of 0.5 to 1.0 mg/l per year (Figure 4). Since then, mean annual concentrations have been variable and have actually trended slightly downwards. The mean lake wide concentration in 2011 was 14.4 mg/l; in 2010 it was 15.5 mg/l. Chlorides in Otsego Lake have generally been attributed to road salting practices, with the greatest influx of the ion during spring snowmelt events or early-winter snow storms.

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Figure 4. Mean chloride concentrations at TR4-C, 1925-2011. Points later than 1990 represent yearly averages (modified from Peters 1987). Nutrients

Total phosphorus averaged 8.5 µg/l in 2011 (when not including tests that were below method detection), ranging from below detection (< 4 µg/l) on multiple dates to 40 µg/l at 12m on 13 July. Concentrations tended to be fairly homogeneous from surface to bottom. No phosphorus release from the sediments was observed prior to fall turnover, as dissolved oxygen was present at concentrations sufficient to maintain iron-phosphorus bonds in sediment materials. Nitrite+nitrate-N averaged 0.46 mg/l; ammonia-N was not measured, as it is generally below detectable levels (<0.02 mg/L) unless dissolved oxygen is depleted in the bottom of the hypolimnion. Total nitrogen analyses, yielding a mean of 0.62 mg/l, indicate an average organic nitrogen concentration of about 0.16 mg/l over the year. This situation was nearly identical to that observed in 2010 (Waterfield and Albright 2011).

Secchi disk transparency and chlorophyll a

Chlorophyll a concentrations were determined for samples collected on 10 dates from May through September 2011. Average 0-20m composite chlorophyll a concentration was 1.5 µg/l (range= 1.0 to 2.4 µg/l). This is compared to a mean concentration of 1.9 µg/l in 2010, and it is the lowest average recorded value since at least 1988. A more detailed description of the temporal and spatial distribution of chlorophyll a is provided by Levenstein (2012).

Secchi disk transparencies ranged from 3.0m on 3 May to a season-maximum of 10.1m

on 13 July (Figure 5). The temporal variation of transparency differed from that observed in 2010 (Figure 6). Mean summer Secchi transparencies for all years available (1935-2011) are given in Figure 7. The marked increase in transparency noted in 2009 continues to date, and is likely related to the filtration capacity of the growing zebra mussel population, as similar changes in water clarity and chlorophyll a have been documented concurrent with the

02468

101214161820

1920 1940 1960 1980 2000 2020

Chl

orid

e (m

g/l)

Year

14

establishment and growth of zebra mussel populations elsewhere (e.g. Leach 1993, Waterfield et al. 2011). Also, over summers of 2010 and 2011, Otsego Lake’s zooplankton community comprised a higher abundance of Daphnia spp., which had a mean length substantially greater than any year since 1990 (Albright and Leonardo 2011). It is not known if this is resultant of the establishment of zebra mussels or more a function of declining alewife (Waterfield and Cornwell 2012)

Figure 5. May through September Secchi transparencies at TR4C, Otsego Lake, 2011.

Figure 6. May through September Secchi transparencies at TR4C, Otsego Lake, 2010.

0

2

4

6

8

10

12

3-May 18-May 1-Jun 15-Jun 28-Jun 13-Jul 26-Jul 8-Aug 24-Aug 9-Sep 27-Sep

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2011 Otsego Lake Secchi Transparency

0

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18-May 26-May 4-Jun 15-Jun 1-Jul 15-Jul 3-Aug 12-Aug 26-Aug 9-Sep 24-Sep

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2010 Otsego Lake Secchi Transparency

15

REFERENCES Albright, M.F. 1997. Otsego Lake limnological monitoring, 1996. In 29th Ann. Rept. (1996).

SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. 1998. Otsego Lake limnological monitoring, 1997. In 30th Ann. Rept. (1997). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. 1999. Otsego Lake limnological monitoring, 1998. In 31st Ann. Rept. (1998).

SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. 2000. Otsego Lake limnological monitoring, 1999. In 32nd Ann. Rept. (1999).

SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. 2001. Otsego Lake limnological monitoring, 2000. In 33rd Ann. Rept. (2000).

SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. 2002. Otsego Lake limnological monitoring, 2001. In 34th Ann. Rept. (2001).


0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

'35 '68 '69 '70 '71 '72 '73 '75 '76 '77 '78 '79 '80 '81 '82 '84 '85 '86 '87 '88 '92 '93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11Se

cchi

Tra

nspa

renc

y (m

)

Year

Figure 7. Mean summer (May-October) Secchi disk transparency collected at TR4-C, 1935 to 2011.

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Albright, M.F. 2003. Otsego Lake limnological monitoring, 2002. In 35th Ann. Rept. (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. 2004. Otsego Lake limnological monitoring, 2003. In 36th Ann. Rept. (2003).





SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. and M. Leonardo. 2011. A survey of Otsego Lake’s zooplankton community,

summer 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta. SUNY Oneonta. Albright, M.F. and H.A. Waterfield. 2009. Otsego Lake limnological monitoring, 2008. In 41st

Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. and O. Zaengle. 2012. A survey of Otsego Lake’s zooplankton community, summer 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

APHA, AWWA, WPCF. 1989. Standard methods for the examination of water and wastewater,

17th ed. American Public Health Association. Washington, DC. Austin, T., M.F. Albright, and W.N. Harman. 1996. Otsego Lake monitoring, 1995. In 28th Ann.

Rept. (1995). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Bauer, H. 2011. Chlorophyll a survey, Otsego Lake, 2010. In 43rd Ann. Rept. (2010). SUNY

Oneonta Biol. Fld. Sta., SUNY Oneonta. Bowers, B. 2011. Littoral fish community survey of Rat Cove and Brookwood Point, summer

2010 In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Bowers, B.E. 2012. Alewife (Alosa psuedoharengus) density as a predictor of open water

utilization by walleye (Sander vitreus) in Otsego Lake, NY. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total

phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1721-1726.

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EPA. 1983. Methods for the analysis of water and wastes. Environmental Monitoring and Support Lab. Office of Research and Development. Cincinnati, OH.

Eureka Environmental Engineering. 2004. Manta water quality probe, startup guide. Austin, TX. German, B.P. German. 2012. Summer 2011 trap net monitoring of fish communities utilizing the

weedy littoral zone at Rat Cove and rocky littoral zone Brookwood Point, Otsego Lake. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Groff, A., J.J. Homburger and W.N. Harman. 1993. Otsego Lake limnological monitoring, 1992.

In 24th Ann. Rept. (1991). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N. 1994. Otsego Lake limnological monitoring, 1993. In 26th Ann. Rept. (1993).

SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N. 1995. Otsego Lake limnological monitoring, 1994. In 27th Ann. Rept. (1994).


Harman, W.N., L.P. Sohacki, M.F. Albright, and D.L. Rosen. 1997. The state of Otsego Lake, 1936-1996. Occasional Paper #30, SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N., L.P. Sohacki, and P.J. Godfrey. 1980. The limnology of Otsego Lake. In

Bloomfield, J.A. (ed.). Lakes of New York State. Vol. III. Ecology of East-Central N.Y. Lakes. Academic Press, Inc., New York.

Homburger, J.J. and G. Buttigieg. 1992. Otsego Lake limnological monitoring. In 24th Ann.

Rept. (1991). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Hydrolab Corporation. 1993. Scout 2 operating manual. Hydrolab Corp. Austin, TX. Iannuzzi, T.J. 1991. A model plan for the Otsego Lake watershed. Phase II: The chemical

limnology and water quality of Otsego Lake, Occasional Paper #23. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Leach, J. H. 1993. Impacts of the zebra mussel (Dreissena polymorpha) on water quality and fish

spawning reefs in western Lake Erie. In: Zebra Mussels: Biology, Impacts, and Control. Lewis Publishers, Boca Raton, FL p 381-397.

Levenstein, A. 2012. Chlorophyll a analysis of Otsego Lake, summer 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Liao, N. 2001. Determination of ammonia by flow injection analysis. QuikChem ® Method 10-

107-06-1-J. Lachat Instruments, Loveland, CO. Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis

colorimetry (acid persulfate digestion method). QuikChem ® Method 10-115-01-1-F. Lachat Instruments, Loveland, CO.

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Peters, T. 1987. Update on chemical characteristics of Otsego lake water. In 19th Ann. Rept. (1986). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow injection

analysis. QuikChem ® Method 10-107-04-1-C. Lachat Instruments, Loveland, CO. Waterfield, H.A., and M.F. Albright. 2010. Water quality monitoring of five major tributaries in

the Otsego Lake watershed. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., and M.F. Albright. 2011. Water quality monitoring of five major tributaries in the Otsego Lake watershed. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., M.F. Albright, and Mazziotta, N. 2011. Continued monitoring of Canadarago Lake and its tributaries, 2010 results (interim report). In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield H.A. and M.D. Cornwell. 2012. Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

YSI Incorporated. 2009. 6-Series multiparameter water quality sonde user manual. Yellow

Springs, OH.

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A survey of Otsego Lake’s zooplankton community, summer 2011

M.F. Albright and O. Zaengle1

INTRODUCTION

This study was a continuation of long-term monitoring of Otsego Lake’s zooplankton community in order to document any changes that might be attributable to top down management efforts to control alewife (Alosa pseudoharengus) through the re-establishment of walleye (Sander vitreus) and to the establishment of other species such as the zebra mussel (Dreissena polymorpha).

Historically, Otsego Lake has been considered oligo-mesotrophic based on

various trophic state indicators. Some of the earlier, comprehensive limnological data collected on Otsego Lake revealed transparencies and algal standing crops indicative of oligotrophic conditions (Godfrey 1977), despite phosphorus loading rates at levels typically associated with a more mesotrophic state (Godfrey 1979). This was attributed to Otsego’s large-bodied crustacean zooplankton, which were more abundant than in other New York lakes studied at that time (Godfrey 1977).

Alewife, a visually-oriented, efficient plantivore, was first documented in Otsego

Lake in 1986 (Foster 1990) and by 1990 it was the dominant forage fish in the lake. The zooplankton community had shifted from dominance by crustaceans, especially Daphnia spp., to rotifers (Foster and Wigens 1990). Rotifers are poor quality food items for fish, and they sequester fewer nutrients and have substantially lower algal grazing rates than do crustaceans (Warner 1999). Depressed abundances and lower mean sizes of crustacean zooplankton have been documented from the onset of alewife dominance through at least 2002; concurrent with this shift, mean summer transparencies declined while algal standing crops and rates of hypolimnetic oxygen depletion have increased (Harman et al. 2002). This was despite various mitigative efforts designed to reduce nutrient inputs to the lake (i.e., Murray and Leonard 2005; Albright 2005). Thus, the apparent shift toward more eutrophic conditions through the 1990s seemed attributable to cascading trophic changes resulting from the establishment of alewives and the subsequent declines in large crustacean zooplankton.

Otsego Lake has been stocked with walleye since 2000 at a targeted rate of

80,000 pond fingerlings each year. The primary intent was to take advantage of the forage base provided by alewives to re-establish this popular sports fish. Concurrent monitoring has attempted to document any changes that might be related to this trophic modification (Cornwell 2005).

Zebra mussels were first documented in Otsego lake in 2007 (Waterfield 2009)

and by 2010 adults were widespread on suitable substrate throughout the lake. The 1 Peterson Family Conservation Trust Fellow, 2011. Funded by PFCT and CRISP. Present affiliation: SUNY College of Environmental Science and Forestry.

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influence of this introduction on recent shifts in the zooplankton community is not known, but warrants consideration.

METHODS

Samples were generally collected bi-weekly, from 19 May to 27 September 2011, at TR4C, the deepest part of Otsego Lake (Figure 1). At this site a 0.2m diameter conical plankton net with 147um mesh was hauled from 12 m (approximately the top of the hypolimnion) to the surface. A G.O. TM mechanical flow meter mounted across the net opening allowed for the determination of the volume of lake water filtered. Samples were preserved in ethanol. The volume of the preserved samples was recorded, allowing for the later back-calculation of zooplankton abundances in lake water. Samples were viewed on a 1 ml gridded Sedgwick rafter cell. Zooplankton were identified, enumerated and measured using a research grade compound microscope with digital imaging capabilities. For each sample, at least 100 organisms were identified and measured to the nearest 0.001 mm.

Figure 1. Otsego Lake, New York, showing location of sample site (TR4-C).

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Mean densities and lengths for cladocerans, copepods and rotifers were used to calculate dry weight (Peters and Downing 1984), daily filtering rate (Knoechel and Holtby 1986) and phosphorus regeneration (Esjmon-Karabin 1983) on each date sampled according to the equations given in Table 1.

Table 1. Equations used to determine zooplankton dry weight (Peters and Downing 1984), filtering rates Knoechel and Holtby 1986), and phosphorus regeneration rates (Esjmon-Karabin 1983) (see Table 2).

Dry Weight: D.W.=9.86*(length in mm)2.1

Filtering Rate: F.R.=11.695*(length in mm)2.48 Phosphorous regeneration: Cladocerans: P.R.=.519*(dry weight in ug)-.023*e 0.039*(temp.in C) Copepods: P.R.=.229*(dry weight in ug)-.645*e 0.039*(temp.in C) Rotifers: P.R.=.0514*(dry weight in ug)-1.27*e 0.096*(temp.in C)


Table 2 provides a summary of the data, including mean epilimnetic temperature (which affects phosphorus regeneration rates), numbers of each taxon per liter, average length, mean dry weight per individual and per liter, phosphorus regeneration rates per individual and per liter, filtering rates, and the percentage of the epilimnion filtered per day. Figure 2 summarizes dry weight contributed by rotifers, copepods, and cladocerans over the summer of 2011; Figure 3 provides similar data collected over 2010. Table 3 provides mean crustacean density, mean cladoceran size and mean dry weight, percent of the epilimnion filtered per day, and phosphorus regeneration by crustaceans in 2000 and 2002 -2011.

Otsego Lake’s zooplankton community has changed substantially over the past

several years. In the early 2000s, the cladoceran community was dominated by Bosmina, a small bodied organism, typically ~0.3 mm. Daphnia, when present, were typically 0.6 to 0.7 mm. In the latter 2000s, Daphnia have increased in abundance relative to Bosmina (which have declined markedly), leading to an increase in mean cladoceran length (mean daphnid length, then still at 0.6 to 0.7 mm, was approximately twice that of the typical bosminid length). Over the summer of 2010, the mean daphnid abundance, at 7.7/l, comprised 61% of the cladoceran community. Interestingly, the mean daphnid length had increased to 1.2 mm. Given the length to weight ratios, this indicates that mean Daphnia dry weight has increased from about 4 to 14.5 µg. Over the summer of 2011, daphnid abundance averaged 5.1/l (60% of the cladoceran community) with a mean length of 1.03 mm.

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Avg Temp. #/L Avg lengthMean Dry

Wt Dry Wt

Phos. Regen. Rate

ugP*mgdrywt-1

Phos. Regen. Rate

Filtering Rates % Epilimnion

(°C) (mm) (µg) (µg/L) *ind*h-1 (µg/l/day) ml/ind/day filtered/day5/19 11.25

Cladocera 0.00Copepoda 63 0.518 4.290 270.74 0.139 0.902 2.288 14.44Rotifers 20 0.326 1.430 28.33 0.015 0.010 0.726 1.44Total 299.07 0.912 15.88

6/1 16.25Cladocera 8 0.780 6.580 55.73 0.634 0.848 6.315 5.35Copepoda 87 0.347 1.800 157.07 0.295 1.114 0.847 7.39Rotifers 23 0.182 0.360 8.44 0.106 0.022 0.171 0.40Total 221.24 1.983 13.14



7/13 22.01Cladocera 5 1.453 23.780 108.44 0.591 1.538 29.541 13.47Copepoda 19 0.201 0.400 7.75 1.512 0.281 0.219 0.42Rotifers 189 0.115 0.110 20.81 2.034 1.016 0.055 1.04Total 136.99 2.835 14.93 Table 2. Summary of 2011 mean epilimnetic temperature, zooplankton densities and mean length per taxa, as well as derived values for mean weight per individual and per liter, phosphorus regeneration per individual and per liter, filtering rates per individual and the percent of the epilimnion filtered per day.

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Avg Temp. #/L Avg lengthMean Dry

Wt Dry Wt

Phos. Regen. Rate

ugP*mgdrywt-1

Phos. Regen. Rate

Filtering Rates % Epilimnion

(°C) (mm) (µg) (µg/L) *ind*h-1 (µg/l/day) ml/ind/day filtered/day7/26 24.05Cladocera 20 0.430 2.490 50.92 1.075 1.314 1.442 2.95Copepoda 46 0.422 1.060 48.77 0.563 0.660 1.376 6.33Rotifers 88 0.111 0.100 8.82 0.733 0.155 0.050 0.44Total 108.51 2.128 9.728/8 24.29Cladocera 1 0.629 3.730 4.44 0.989 0.105 3.704 0.44Copepoda 53 0.402 2.170 115.75 0.358 0.995 1.220 6.51Rotifers 89 0.106 0.090 8.00 0.845 0.162 0.045 0.40Total 128.19 1.263 7.358/24 22.23Cladocera 1 0.516 1.040 0.58 1.224 0.017 2.267 0.13Copepoda 49 0.299 0.860 41.74 0.601 0.602 0.586 2.84Rotifers 15 0.101 0.070 1.07 1.073 0.027 0.040 0.06Total 43.39 0.646 3.039/9 19.75Cladocera 5 0.814 7.210 32.59 0.712 0.557 7.020 3.17Copepoda 8 0.458 2.450 20.78 0.278 0.138 1.686 1.43Rotifers 87 0.096 0.080 6.95 0.822 0.137 0.035 0.30Total 60.32 0.832 4.919/27 19.28Cladocera 3 0.846 8.050 20.93 0.681 0.342 7.725 2.01Copepoda 19 0.439 2.520 47.05 0.268 0.302 1.518 2.83Rotifers 12 0.096 0.080 0.94 0.808 0.018 0.035 0.04Total 68.92 0.663 4.88Season meanCladocera 8.096 0.758 6.826 55.174 0.818 1.007 6.688 5.878Copepoda 51.239 0.396 2.024 99.912 0.361 0.721 1.240 5.779Rotifers 49.096 0.140 0.271 8.280 0.602 0.076 0.136 0.412Total 163.37 1.805 12.07 Table 2 (cont.). Summary of 2011 mean epilimnetic temperature, zooplankton densities and mean length per taxa, as well as derived values for mean weight per individual and per liter, phosphorus regeneration per individual and per liter, filtering rates per individual and the percent of the epilimnion filtered per day.

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8/24 8/8 7/26 7/13 6/1 6/15 6/28 5/19 9/9 9/27

Figure 2. Dry weight contributed by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2011.

0

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Figure 3. Dry weight contributed by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2010.

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Table 3. Mean crustacean density, mean cladoceran size and mean dry weight, percent of the epilimnion filtered per day and phosphorus regeneration by crustaceans in 2000 and 2002 -2011.

2000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Mean cladoceran size (mm) 0.29 0.30 0.36 0.53 0.55 0.55 0.34 0.54 0.69 0.81 0.76 Mean crustacean density (#/l) 208 146 132 163 159 159 154 178 97 56.7 59.4 Mean crustacean dry weight (µg/l) 175 145 177 261 206 206 128 321 142 143 155 Mean % of epilimnion filtered/day 11.9 9.9 12.7 25.1 19.2 19.2 12.2 31.9 9.5 10.8 12.1 Mean phosphorus regeneration (µg/l/day) 4.49 2.6 3.1 4.4 2.7 2.4 3.0 5.8 1.5 1.9 1.8

CONCLUSION Table 4 summarizes several trophic characteristics of Otsego Lake before the

introduction of alewife (when the primary forage fish was cisco), following the introduction of, and dominance by, alewife, and over the summers of 2010-11. Over the 1990s, it is believed that alewife virtually eliminated the larger bodied crustaceans, leading to lower plankton filtering rates, higher algal standing crops, lower transparencies and greater hypolimnetic oxygen demand (Harman et al. 2002). Walleye stocking commenced in 2000, and the gradual rebound in numbers of larger crustaceans, particularly Daphnia, over the following several years, was attributed to a reduction in alewife (Waterfield and Cornwell 2011) due to predation by walleye. However, zebra mussels (Dreissena polymorpha), first documented in Otsego Lake in 2007, had become abundant by the spring of 2010. Filtering by them likely overshadowed that by zooplankton, leading to transparencies that were among the highest ever recorded and rates of hypolimnetic oxygen demand among the lowest ever recorded (Waterfield and Albright 2011). The reasons for the marked increase in mean Daphnia size is unknown. Table 4. Changes in Otsego Lake’s trophic characteristics between periods of cisco dominance, alewife dominance, and current conditions (SE) (1from Harman et al. 2002).

Cisco1 Dominance (1970-1988)

Alewife1 Dominance (1990-1999)

Walleye/ZebraMussels

(2010-2011) Common Cladocera Daphnidae

Bosminidae Leptodoridae

Bosminidae Daphnidae Bosminidae

Cladoceran size (mm) 0.8 0.33 0.79 Crustacean plankton biomass (ug·l-1) 500 100 150 Epilimnion filtered (%·day-1) 27.8% 9.7% 11.4% Chlorophyll a (ug·l-1) 2.4 (1.3) 6.4 (2.4) 1.8 Secchi depth (m) 5.1 (1.03) 3.3 (.46) 7.0 AHOD (mg·cm-2·day-1) 0.066 (0.021) 0.096 (1.3) 0.056

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REFERENCES Albright, M.F. 2005. A report on the evaluation of changes in water quality in a stream following the implementation of agricultural best management practices. In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Cornwell, M.D. 2005.Re-introduction of walleye to Otsego Lake; Re-establishing a fishery and subsequent influences of a top predator. Occas. Pap. No. 40. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Esjmont-Karabin, J. 1984. Phosphorus and nitrogen excretion by lake zooplankton

(rotifers and crustaceans) in relation to the individual body weights of the animals, ambient temperature, and presence of food. Ekologia Polska 32:3-42.

Foster, J.R. 1990. Introduction of the alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1989) SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Foster, J.R. and J. Wigen.1990. Zooplankton community as an ecological indicator in cold water fish community of Otsego Lake. In 22nd Ann. Rept. (1989). SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Godfrey, P.J. 1977. An alalysis of phytoplankton standing crop and growth: Their historical development and trophic impacts. In 9th Ann. Rept. (1976). SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Godfrey, P.J. 1979. Otsego Lake limnology: Phosphorus loading, chemistry, algal standing crop and historical changes. In 10th Ann. Rept. (1978). SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Harman, W.N., M.F. Albright and D.M. Warner. 2002. Trophic changes in Otsego Lake, NY following the introduction of the alewife (Alosa pseudohargenous). Lake and Reserv. Manage. 18(3)215-226.

Knoechel, R. and B. Holtbly.1986 Construction of body length model for the prediction of cladoceran community filtering rates. Limnol. Oceanogr. 31(1):1-16.

Murray, K. and P. Leonard. 2005. Continued water quality monitoring of five major tributaries to Otsego Lake, summer 2004. In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Peters, R.H. and Downing, J.A. 1984 Empirical analysis of zooplankton filtering and

feeding rates. Limnology and Oceanography, 29 (4). pp. 763-784

Warner, D.M. 1999. Alewives in Otsego Lake, NY: a comparison of their direct and indirect mechanisms of impact on transparency and chlorophyll a. Occas. Pap. No.32. SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

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Waterfield, H.A. 2009. Update on zebra mussel (Dreissena polymorpha) invasion and

establishment in Otsego Lake, 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.F. Albright. 2011. Otsego Lake limnological monitoring, 2010.

In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Waterfield, H.A. and M.D. Cornwell. 2011. Hydroacoustic surveys of Otsego lake’s

pelagic fish community, 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Chlorophyll a concentrations in Otsego Lake, summer 2011

A. Levenstein1

INTRODUCTION

This study is a continuation of a long term limnological survey of chlorophyll a concentrations in Otsego Lake. It is part of an annual analysis of biotic and abiotic factors of the lake (Harman et al. 1997). These factors are monitored to provide information regarding changes in the trophic state of the lake over time.

Chlorophyll a is a pigment used in the process of photosynthesis. Due to the fact that chlorophyll a is present in all types of algae, it is used as an indicator for the abundance of algae (Berkman and Canova 2007). The relative amount of algal biomass in a lake can be determined by measuring the chlorophyll a content of a sample and comparing it to previous samples. Relative algal biomass is an indicator of the lake’s trophic status and water quality.

Since algae are the most abundant primary producers in Otsego Lake, they have a large impact on all of the populations above them in the food web, including fish. When algae die and sink through the hypolimnion, they undergo decomposition by bacteria. This process consumes oxygen and can jeopardize cold water game fish such as lake trout (Salvelinus namaycush) if algal populations are large (Wetzel 1975). Conversely, if algal production is low, the production at higher trophic levels, including game fish, would decline. This survey provides information on the abundance of algae at different depths in the lake.

Monitoring of chlorophyll a concentrations in the Otsego Lake for the summer of 2011 has been concurrent to a study evaluating the overall chemical and physical parameters of Otsego Lake (Waterfield and Albright 2012).

METHODS AND MATERIALS

Chlorophyll a samples were acquired bi-weekly from 28 June to 8 August at the deepest part of the lake (site TR4-C, Figure 1). Samples were collected at 1-meter intervals from the surface to twenty meters using a VanDorn sampler. Samples were then transferred into 500 mL Nalgene bottles and placed into a dark iced cooler to limit exposure of chlorophyll a to light and heat.

Upon returning to the lab, a 200 mL aliquot of each sample was immediately filtered

through a 47mm Whatman GF/A Glass Micro Fiber Filter using a low pressure vacuum pump under subdued light. The filters were then folded in half to protect the chlorophyll a and patted dry with paper towels. Once folded and dried, the filters were placed in a clean 47mm Millipore 1 F.H.V. Mecklenburg Conservation Fellow, summer 2011. Present affiliation: Rensselaer Polytechnic Institute. Funding provided by the Otsego County Conservation association.

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Petri dish. Each dish was covered with aluminum foil and labeled with site, depth, and date. Dishes were stored in a freezer at -20°C until processing resumed. Processing continued by cutting each filter into small pieces using forceps and scissors. The cut pieces were placed into a 15mL glass grinding tube with approximately 4 mL of buffered acetone (90% acetone and 10% saturated MgCO3) and were then ground into a homogenous slurry using a power drill equipped with a Teflon pestle drill bit. After each sample was fully ground, they were transferred to a 15mL centrifuge tube and filled to 10 mL with buffered acetone. Each sample was shaken and centrifuged for 10 minutes at 10,000xG in order to take particulate matter out of suspension. Some of the sample was then poured into a 1 cm cuvette and placed in a Turner Designs TD-700 Fluorometer for analysis. Following the procedures of Arar and Collins (1997), chlorophyll a concentrations were determined.

Figure 1. A map of Otsego Lake with sample site TR4-C, used for collecting water samples for chlorophyll a analysis, summer 2011.

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Chlorophyll a concentrations this year on average were lower than all previous years on record at most of the tested depths. The average chlorophyll a concentration for 2011 was 1.32 ppb.

Figure 2 shows the average summer chlorophyll a concentrations from 2000 to 2011. This graph illustrates the yearly fluctuations that chlorophyll a concentrations experience. From 2000 to 2003, average chlorophyll a densities in Otsego Lake decreased steadily from 6.82 ppb in 2000 (Durie 2001) to 2.62 ppb in 2003 (Schmitt 2003). The trend then reversed and peaked in 2006 at 5.97 ppb (Stevens 2007). In 2007, chlorophyll a densities dropped to about 1.91 ppb; the same average density was noted in 2010 as well (Bauer 2011). Since data are incomplete for 2008 and 2009, it is unknown what the exact chlorophyll a densities were for those years. The data that are available from surface to 20 meter composite samples of Otsego Lake suggest that the average chlorophyll a concentration for 2008 was about 4 ppb (Albright and Waterfield 2009) and about 5 ppb for 2009 (Waterfield and Albright 2010). However, it should be noted that the composite sample data from previous years do not consistently correlate with the data from samples taken for their respective annual chlorophyll a reports.

Figure 2. Mean summer chlorophyll a concentrations for 2000 (Durie 2001), 2001 (Wayman 2002), 2002 (Wayman 2003), 2003 (Schmitt 2004), 2004 (Murray 2005), 2005 (Zurmuhlen 2006), 2006 (Stevens 2007), 2007 (Ottley 2008), 2008 (Albright and Waterfield 2009), 2009 (Waterfield and Albright 2010), 2010 (Bauer 2011), and 2011. Data from 2008 (Albright and Waterfield 2009) and 2009 (Waterfield and Albright 2010) are taken from surface to 20 meter composite samples because this survey was not completed during those years. The composite sample data may not be consistent with data collected for this survey.

A likely contributor to this decrease in chlorophyll a is the growing population of zebra mussels (Dreissena polymorpha) in Otsego Lake. Zebra mussels are filter feeders that consume suspended material, primarily phytoplankton (Bensen et. al. 2011). They were first discovered in Otsego Lake in 2007 (Waterfield 2009) and were considered widespread and abundant by 2010 (Albright and Zaengle 2012). Although zebra mussels consume algae, data from other areas that have been invaded suggest that zebra mussel activity may lead to blue-green algal blooms within

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the next decade (LLRS 2009). This occurs because zebra mussels selectively avoid consuming blue-green algae. Since the other types of algae are eaten by zebra mussels, the blue-green varieties thrive in the absence of their competitors.

Another contributor to the decline in chlorophyll a levels may be a recent increase in abundance of large-bodied cladoceran zooplankton (Albright and Leonardo 2011) resulting from a decrease in alewife abundance (Waterfield and Cornwell 2011). Zooplankton consume phytoplankton, so an increase in zooplankton mass and abundance would lead to increased grazing and therefore lower levels of phytoplanktonic algae.

Figure 3 shows chlorophyll a levels for the summers of 2000 to 2011, excluding 2008 and 2009. Chlorophyll a concentrations from 2011 are the lowest recorded at 15 of the 21 depths surveyed. The depth with the highest concentration of chlorophyll a in 2011 was 10 meters with a density of 1.83 ppb. The lowest density for 2011, 0.64 ppb, was observed at a depth of 18 meters.

Figure 3. Summer chlorophyll a concentrations for 2000 (Durie 2001), 2001 (Wayman 2002), 2002 (Wayman 2003), 2003 (Schmitt 2004), 2004 (Murray 2005), 2005 (Zurmuhlen 2006), 2006 (Stevens 2007), 2007 (Ottley 2008), 2010 (Bauer 2011), and 2011. Data are unavailable from 2008 and 2009.

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REFERENCES

Albright, M. and M. Leonardo 2011. A survey of Otsego Lake’s zooplankton community, summer 2010. In 43rd Annual Report (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. and O. Zaengle. 2012. A survey of Otsego Lake’s zooplankton community,

summer 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M. and Waterfield, H. 2009. Otsego Lake limnological monitoring, 2008. In 41st Annual Report (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Arar, E.J. and G.B. Collins.1997. Method 445.0, In Vitro Determination of Chlorophyll a and

Pheophytin a in Marine and Freshwater Algae by Fluorescence. In Methods for the Determination of Chemical Substances in Marine and Estuarine Environmental Matrices, 2nd Edition. National Exposure Research Laboratory, Office of Research and Development, USEPA., Cincinnati, Ohio. EPA/600/R-97/072.

Bauer, H. 2011. Chlorophyll a analysis of Otsego Lake, summer 2010. In 43rd Annual Report (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Benson, A. J. and D. Raikow. 2011. Dreissena polymorpha. USGS Nonindigenous Aquatic Species Database, Gainesville, FL.

Berkman, J. and M. Canova 2007. Algal Biomass Indicators: U.S. Geological Survey National Field Manual for the Collection of Water-Quality Data, book 9, chap. A7, 5 p.

Durie, B. 2001.Chlorophyll a analysis of Otsego Lake, summer 2000. In 33rd Annual Report (2000). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N., L.P. Sohacki, M.F. Albright, D.L. Rosen. 1997. The State of Otsego Lake, 1936- 96. Occasional Paper # 30, SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Large Lakes and Rivers Forecasting Research Branch (LLRS). "Algal Blooms in Western Lake Erie." US Environmental Protection Agency, 26 Aug. 2009. Web. 10 Aug. 2011. Murray, K. 2005. Chlorophyll a concentrations in Otsego Lake, summer 2004. In 37th Annual Report (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Ottley, S.G. 2008. Chlorophyll a concentrations in Otsego Lake, summer 2007. In 39th Annual Report (2007). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Schmitt, R. 2004. Chlorophyll a concentrations in Otsego Lake, summer 2003. In 36th Annual Report (2003). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Waterfield, H.A. 2009. Update on zebra mussel (Dreissena polymorpha) invasion and establishment in Otsego Lake, 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H. and Albright, M. 2010. Otsego Lake limnological monitoring, 2009. In 42nd Annual Report (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H. and Albright, M. 2012. Otsego Lake limnological monitoring, 2011. In 44th Annual Report (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Waterfield, H. and Cornwell, M. 2011. Hydroacoustic surveys of Otsego Lake’s pelagic fish

community, 2010. In 43rd Annual Report (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Wayman, K. 2002. Chlorophyll a concentrations in Otsego Lake, summer 2001. In 34th Annual Report (2001). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Wayman, K. 2003. Chlorophyll a concentrations in Otsego Lake, summer 2002. In 35th Annual Report (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Wetzel, R.G. 1975. Limnology. W.B. Sanders Company, Philadelphia. Zurmuhlen, S. 2006. Chlorophyll a analysis of Otsego Lake, summer 2005. In 38th Annual Report (2005). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2011

Owen Zaengle1

INTRODUCTION

This study is a continuation of water quality monitoring of the 5 major tributaries in the northern watershed of Otsego Lake that began in 1995. The study began as an attempt to assess agricultural Best Management Practices (BMPs) encouraged by the United States Department of Agriculture (USDA). Of the land in the northern watershed about 44 percent has agricultural uses. The USDA’s Environmental Quality Incentive Program and the Otsego County Conservation Association offered financial assistance to farmers willing to implement BMPs. Currently there are 23 farms in the study area that have adopted the BMPs. Through practices like conservation tillage, crop nutrient management, pest management, and conservation buffers, BMPs attempt to reduce soil loss as well as runoff of nutrients and other pollutants into streams (USDA NRCS 2006). Agricultural runoff has been well documented as a non-point source pollutant, especially of nutrients (Sharpley et al. 2006). Excessive nutrient runoff, mainly nitrogen and phosphorous, into streams can cause a condition known as eutrophication in lakes. High nutrient levels allow expansive plant and algal growth; these are characteristic of eutrophication and greatly alter energy flow, nutrient cycling, and water quality. In Otsego Lake eutrophication threatens the present biodiversity, Cooperstown’s drinking water supply, and the aesthetic and recreational values of the lake. The lake management plan cites eutrophication as the greatest threat to Otsego Lake (Anonymous 2007). Previously classified as a mesotrophic lake with oligotrophic fauna (Harman et. al. 1980), Otsego Lake has shown signs of eutrophication since the early 1990s.

However, significant changes in the lakes ecosystem have made the extent of nutrient loading into the lake difficult to evaluate. The introduction of alewife by 1986 (Foster 1989) enhanced algal growth due to its predatory domination of the local zooplankton (Warner 2000). The subsequent introduction of zebra mussels circa 2007 (Waterfield 2009) resulted in a drastic reduction of the algal community obscuring some of the more visible effects of eutrophication; as well as the quantifiable demand for hypolimnetic oxygen. Though visibility may be limited, nutrient management is of utmost importance in the Otsego Lake watershed.

METHODS

Methods were kept in accordance with previous year’s research. Water samples and measurements of physical parameters were taken weekly, from May 17 to August 9, at 23 sample sites. Sample sites had been previously established on White Creek, Cripple Creek, Hayden Creek, Shadow Brook, and Mount Wellington. These sites were selected in 1995 based 1 Peterson Family Conservation Trust Fellow, 2011. Funded by PFCT and CRISP. Present affiliation: SUNY College of Environmental Science and Forestry.

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upon access, stream characteristics, proximity to agricultural tracts, and general runoff patterns (Heavy 1996). The sites were amended in 1996. Table 1 provides coordinates and physical descriptions of each site. Figure 1 illustrates locations of sample sites and BMPs. Water samples were collected in acid-washed 125 mL bottles. The samples were kept on ice while in the field, and preserved with sulfuric acid upon returning to the lab. Using a Lachat® QuikChem FIA+ Water Analyzer samples were then analyzed for total nitrogen (TN), total phosphorous (TP), and nitrate+nitrite. Total nitrogen and nitrate+nitrite were found via cadmium reduction method (Pritzlaff 2003) and total phosphorous using ascorbic acid followed by persulfate digestion (Liao and Martin 2001). Nitrate+nitrite concentrations that were below the detection level of 0.02 mg/L were assigned a value of 0.01 mg/L for graphing purposes.

Physical parameters (temperature, pH, dissolved oxygen, and specific conductivity) were

measured using a Eureka® Amphibian Multiprobe. Prior to each weekly sampling the device was calibrated according to the manufacturers’ specifications.

Table 1. GPS coordinates and physical descriptions of sample locations (modified from Putnam 2010).

White Creek 1 (WC1): N 42º 49.612’ W 74º 56.967’ South side of Allen Lake on County Route 26 over a steep bank. White Creek 2 (WC2): N 42º 48.93’ W 74º 55.29’ Plunge-pool side of stream on County Route 27 (Allen Lake Road) where there is a large dip in the road. White Creek 3 (WC3): N 42º 48.407’ W 74º 54.178’ West side of large stone culvert under Route 80, just past the turn to Country Route 27. Cripple Creek 1 (CC1): N 42º 50.878 W 74º 55.584’ Weaver Lake accessed from the north side of Route 20 just past outflow of beaver dam. Cripple Creek 2 (CC2): N 42º 50.603’ W 74º 54.933’ Young Lake accessed from the west side of Hoke Road. The water at this site is shallow; some distance from shore is required for sampling. Cripple Creek 3 (CC3): N 42º 49.418’ W 74º 54.007’ North side of culvert on Bartlett Road. Cripple Creek 4 (CC4): N 42º 48.837’ W 74º 54.032’ Large culvert on west side of Route 80. The stream widens and slows at this point; this is the inlet to Clarke Pond. Cripple Creek 5 (CC5): N 42º 48.805’ W 74º 53.768’ Dam just south of Clarke Pond accessed from the Otsego Golf Club road. Samples were collected on the downstream side of the bridge. Hayden Creek 1 (HC1): N 42º 51.658’ W 74º 51.010’ Summit Lake accessed from the east side of Route 80, north of the Route 20 and Route 80 intersection. Small pull off but researcher must wade in the water to place the probe. Hayden Creek 2 (HC2): N 42º 51.324’ W 74º 51.294’ Downstream side of culvert on Dominion Road.

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Table 1 (cont.). GPS coordinates and physical descriptions of sample locations (modified from Putnam 2010).

Hayden Creek 3 (HC3): N 42º 50.890’ W 74º 51.796’ Culvert on the east side of Route 80 north of the intersection of Route 20 and Route 80. Hayden Creek 4(HC4): N 42º 50.267’ W 74º 52.175’ North side of large culvert at the intersection of Route 20 and Route 80. Hayden Creek 5 (HC5): N 42º 49.996’ W 74º 52.501’ Immediately below the Shipman Pond spillway on Route 80.

Hayden Creek 6 (HC6): N 42º 49.685’ W 74º 52.773’ East side of the culvert on Route 80 in the village of Springfield Center. Hayden Creek 7 (HC7): N 42º 49.279’ W 74º 53.984’ Large culvert on the south side of County Route 53. Hayden Creek 8 (HC8): N 42º 48.869’ W 74º 53.291’ Otsego Golf Club, above the white bridge adjacent to the clubhouse. The water here is slow moving and murky. Shadow Brook 1 (SB1): N 42º 51.831’ W 74º 47.731’ Small culvert on the downstream side off of County Route 30 south of Swamp Road. Shadow Brook 2(SB2): N 42º 49.891’ W 74º 49.067’ Large culvert on the north side of Route 20, west of County Route 31. Shadow Brook 3 (SB3): N 42º 48.799’ W 74º 49.839’ Private driveway (Box 2075) off of County Route 31, south of the intersection of Route 20 and Country Route 31 leading to a small wooden bridge on a dairy farm. Shadow Brook 4 (SB4): N 42º 48.337’ W 74º 50.608’ One lane bridge on Rathbun Road. This site is located on an active dairy farm. The streambed consists of exposed limestone bedrock. Shadow Brook 5 (SB5): N 42º 47.441’ W 74º 51.506’ North side of large culvert on Mill Road behind Glimmerglass State Park. Mount Wellington 1 (MW1): N 42º 48.843’ W 74º 52.608’ Stone bridge on Public Landing Road adjacent to an active dairy farm. Mount Wellington 2 (MW2): N 42º 48.77’ W 74º 53.004’ Small stone bridge is accessible from a private road off Public Landing Road; at the end of the private road near a white house there is a mowed path which leads to the bridge. Water here is stagnant and murky. Sampled on the lake side.

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Figure 1. Map showing sampling locations of five tributaries in the northern watershed of Otsego Lake, as well as locations of BMPs (asterisks).

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RESULTS & DISCUSSION

Temperature

Many aquatic organisms are sensitive to temperature; drastic changes in temperature can displace sensitive species. Conservation buffers, one tool of BMPs, shade streams promoting cooler and more stable temperatures. Mean site temperatures from the summer of 2011 ranged from 16.41oC to 24.42oC. Mean temperature values (+/- SE) for all sites are provided in Figure 2. Values were comparable to previous years of study, with mean temperature ranges in 2010 being 17.39oC to 23.56oC

Figure 2. Mean Temperatures of sampling sites along the stream gradients of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

pH and Conductivity

pH is the acidity, or the measure of the concentration of H+ ions on a logarithmic scale from 0 – 14 (Wetzel 2001). Most aquatic organisms are able to survive only within the midranges of the pH scale. The pH of natural waters is strongly influenced by the underlying geology in addition to biological processes such as photosynthesis and respiration. Low pH can ‘release’ toxic substances, mainly heavy metals, into the system. The pH of streams can also be influenced by atmospheric deposition and some types of wastewater. Mean pH ranges in 2010 were 7.3 -8.3 (Putnam 2011), reflecting the dominance of limestone bedrock in the northern portion of the watershed. Mean pH readings from the summer of 2011 were 7.7 – 8.5 at Hayden Creek 1 and Hayden Creek 7 respectively. This is similar to pH ranges from previous years. Figure 3 shows mean site pH over stream gradients.

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Figure 3. Mean pH of sampling sites along the stream gradients of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

Conductivity is the measure of the ability of water to conduct an electrical current

(Wetzel 2001). It is primarily influenced by dissolved inorganic ions, though it is also dependent upon temperature. Like pH, the underlying geology is the main contributor to baseline conductivity readings. If conductivity readings change drastically from baseline conditions, this can indicate a discharge of some pollutants. As with other parameters, conductivity readings are influenced by large precipitation events, fluctuating substantially over the duration of the event. Mean specific conductivity in 2010 ranged from 0.25 ms/cm to 0.54 ms/cm (Putnam 2011). Mean conductivity readings in the summer of 2011 ranged from 0.233 ms/cm at Whites Creek 1 to 0.451 ms/cm at Mount Wellington 2. Figure 4 shows mean site conductivity values over the stream gradients.

Figure 4. Mean conductivity of sampling sites along the stream gradients of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

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Dissolved Oxygen

Dissolved oxygen (DO) is necessary for aquatic organisms to survive. There are many factors which influence the amount of oxygen that water can hold. Temperature has a large impact on DO; the colder the water the more oxygen it can hold. Nitrogen and phosphorous levels can also affect the DO indirectly through increased organic production. Dissolved oxygen usually varies along the horizontal stream gradient, as well as seasonally (with temperature) and daily (with light availability). DO usually increases during the day as aquatic plants photosynthesize and release oxygen, and declines at night while they are consuming oxygen. In 2010 mean site DO ranged from 3.60 mg/L at WC1 to 9.42 mg/l at SB2 (Putnam 2011). Comparable to previous years, mean DO in the summer of 2011 ranged from 5.80 at HC1 to 10.16 at SB4. Figure 5 shows mean dissolved oxygen values over the stream gradients.

Figure 5. Mean dissolved oxygen of sampling sites along the stream gradients of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

Phosphorous

Phosphorous is an essential nutrient in aquatic ecosystems. It appears as organic or inorganic forms. Phosphates can be dissolved in water as well as attached to sediments. Phosphorous can enter a stream through soil, bedrock, decaying plant and animal materials, agricultural runoff, septic systems, and residential use. Sometimes particulate phosphorus settles out in pools along the stream gradient. In Otsego Lake phosphorous is the limiting nutrient (Harman et al, 1997); even a slight increase could have a considerable effect on algal production. In 2010 mean total phosphorus concentrations ranged from 16.8 µg/L at WC3 to 67.9 µg/L at MW2 (Putnam 2011). 2011 mean TP concentrations ranged from 20.2 µg/L at HC2 to 53.1 µg/L at HC1. Figure 6 shows TP concentrations along the stream gradients. Table 2 summarizes mean total phosphorus concentrations at each sampling site from 2001-2011 and Figure 7 graphically shows mean total phosphorus concentrations at the most downstream sites from 1996 to 2011.

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Figure 6. Mean total phosphorous of sampling sites along the stream gradients of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

Table 2. Mean total phosphorous at each sampling site, 2001-2011.

Comparison of phosphorus concentrations (ug/L), 2001-2011 Site 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

WC1 34 72 25 33 51 17 66 46 33 33 25 WC2 33 23 26 39 61 33 37 34 24 25 25 WC3 24 12 23 26 36 40 38 19 22 17 21 CC1 36 112 30 49 49 33 86 89 38 63 0 CC2 23 46 124 144 172 37 36 25 24 25 49 CC3 24 10 25 39 37 62 40 22 26 41 28 CC4 35 19 22 46 55 40 39 34 27 45 30 CC5 45 51 28 46 70 37 58 59 34 41 30 HC1 25 60 21 43 33 33 48 43 35 28 40 HC2 17 14 13 23 34 57 30 27 18 24 0 HC3 28 47 26 34 39 50 35 54 24 31 53 HC4 23 17 26 29 41 22 38 27 24 31 20 HC5 27 27 22 33 43 46 41 37 22 31 24 HC6 24 21 33 28 40 40 49 32 26 26 24 HC7 26 19 30 44 54 73 40 42 27 32 27 HC8 37 54 31 51 120 89 43 71 30 37 27 SB1 39 57 21 27 103 54 28 19 36 30 28 SB2 43 24 31 45 63 50 17 32 34 29 32 SB3 36 46 24 37 40 30 35 30 25 35 0 SB4 37 27 27 62 62 22 26 39 38 26 33 SB5 54 40 34 63 85 38 45 44 37 38 21

MW1 45 36 50 83 51 23 54 33 29 45 24 MW2 192 99 136 88 214 69 65 38 57 68 22

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Figure 7. Mean total phosphorous concentration (µg/L) at the most downstream sites (outlets) of 5 tributaries in the northern watershed of Otsego Lake 1996-2011.

Nitrogen

Nitrogen, like phosphorous, is a nutrient important to plant production. Nitrogen is much more readily dissolved in water than phosphorus, and thus much more mobile. Increases in nitrogen levels can also promote plant and algal production. Peak nitrogen levels have been shown to be directly related to the magnitude of major storm events (Wetzel 2001). Total nitrogen (TN) includes ammonia, nitrates, nitrites, and organic nitrogen. Ammonia testing was discontinued in 2010 as samples were consistently below detection levels (Putnam 2011). The mean TN concentrations from 2010 ranged from 0.51 mg/L at CC1 to 2.03 mg/L at SB2 (Putnam 2011). Figure 8 shows mean total nitrogen at sampling sites along the stream gradients.

Nitrate+nitrite are readily soluble in water, making them the most mobile forms of nitrogen. Nitrite is short-lived, converted to nitrate by oxidation (Wetzel 2001). Nitrate is the form of nitrogen most used by plants, microbes, and other biota as a nutrient and is commonly used as a fertilizer in agriculture. Mean nitrate+nitrite concentrations from 2010 ranged from 0.025 mg/L at CC1 to 1.34 mg/L at SB2. 2011 mean nitrate+nitrite concentrations ranged from 0.009 mg/L at CC2 to 1.572 mg/L at SB2. Figure 9 shows mean nitrate+nitrite at sampling sites along the stream gradients. Concentrations closely paralleled those of total nitrogen (see Figure 8). Figure 10 shows mean nitrate+nitrite concentrations at stream outlets from 1991 and 1998-2011.

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Figure 8. Mean total nitrogen of sampling sites along the stream gradient of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

Figure 9. Mean nitrate+nitrite of sampling sites along the stream gradient of five major tributaries in summer 2011. Distance from the lake increases moving from left to right on the graph.

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Figure 10. Mean nitrate+nitrite at stream outlets of 5 tributaries in the northern watershed of Otsego Lake 1991, 1998-2011.

CONCLUSIONS

Summer water quality monitoring in the five tributaties of the northern watershed showed that temperature, pH, conductivity, and dissolved oxygen were similar to ranges of previous years. The main goal of the BMPs in the northern watershed is to reduce nutrient loading, especially that of phosphorous. In four of the five streams in the study phosphorous input into the lake is lower this year than last year. The basins with the highest density of BMPs, mount wellington and shadow brook, seem to be trending downwards in phosphorous outflow. Continued sampling must be done in order to validate this hypothesis. Nitrate+nitrite concentrations fluctuate considerably year to year, this can be explained its mobility and correlation with precipitation events. Sampling should be continued in upcoming years to better evaluate the overall effectiveness of BMPs.

45

REFERENCES

Anonymous. 2007. A plan for the management of the Otsego Lake watershed. Otsego County Water Quality Coordinating Committee. Otsego County, New York.

Foster, J.R. 1989. Introduction of alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1988). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N., L.P. Sohacki M.F. Albright and D.L. Rosen. 1991. The state of Otsego Lake, 1936-1996. Occas. Pap. #30. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Liao, N. and S. Marten. 2001. Determination of total phosphorous by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

United States Department of Agriculture, Natural Resources Conservation Service. 2006. Best Management Practices to minimize agricultural phosphorus impacts on water quality. http://www.ars.usda.gov/is/np/BestMgmtPractices/Best%20Management%20Practices.pdf

Putnam, S. 2011. Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pritzlaff, D. 2003. Determination of nitrate-nitrite in surface and wastewaters by flow injection analysis. QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

Sharpley, A.N., T. Daniel, G. Gibson, L. Bundy, M. Cabrera, T. Sims, R. Stevens, J. Lemunyon, P. Kleinman, and R. Parry. 2006. Best management practices to minimize agricultural phosphorus impacts on water quality. U.S. Department of Agriculture, Agricultural Research Service, ARS–163, 50 pp.

Wetzel, R.G. 2001. Limnology, Lake and River Ecosystems, 3rd edition. Academic Press. San Diego, California.

Warner. D.M. 2000. Alewives in Otsego Lake, NY: A comparison on their direct diet and indirect mechanisms of impact on transparency and chlorophyll a. Occas. Pap. #32. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. 2009. Update on zebra mussel (Dreissena polymorpha) invasion and establishment in Otsego Lake, 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Preliminary investigations of organic and inorganic carbon content of the Otsego Lake watershed, summer 2011

G.W. Badger 1

INTRODUCTION

White Creek, Cripple Creek, Hayden Creek, Shadow Brook, and Mount Wellington watercourses constitute the northern watershed of Otsego Lake (Figure 1). Approximately 44% of the northern watershed is devoted to agricultural utilization (Harman et. al. 1997) and the potential for anthropogenically derived additions of total carbon (TC), total inorganic carbon (TIC/IC), and nitrogen affecting the larger lacustrine system merits further study of the total organic carbon (TOC) loading endemic to these waters. Carbon to nitrogen ratios may further illuminate complex interactions taking place in this multiple use watershed and lacustrine systems and therefore have been examined concurrently. This analysis will serve as a baseline for future examinations of the Otsego Lake watershed as well as Otsego Lake itself.

Figure 1. Map showing the numbered sampling locations and 5 tributaries in the northern watershed of Otsego Lake; BMPs are represented by black asterisks.

Carbon is the fourth most common element in the universe by mass (Croswell 1996) and is the chemical basis for all known life. It is very stable and so versatile chemically that it may 1 Thayer Research Intern supported by the OCCA. Current Affiliation: SUNY College at Oneonta.

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form an almost infinite number of compounds allowing a great deal of structural variety. Hydrogen, sulfur, nitrogen and phosphorus easily bond with it to form biologically critical compounds such as sugars, fats, antibiotics, and DNA/RNA. The result of this bonding, in many cases, creates an enhanced bioavailability to an array of organisms enabling further structural breakdown of the carbon-containing compounds. Despite its obvious benefits to biological processes, carbon can also form biologically harmful compounds which are resistant to environmental degradation and act as persistent toxins or pollutants in nature (McShaffrey 2006).

The total carbon (TC) present in watercourses includes organic carbon and inorganic carbon (the latter of which constitutes the bulk of the data examined for this study). The difference between the two is considered a rather arbitrary delineation and should be construed as such in any analysis. Carbon originating from decaying vegetation, bacterial growth, or metabolic activities of living organisms or chemicals which may manifest itself in a solid, liquid, or gaseous state is called organic carbon. Organic carbon can be further divided into dissolved organic carbon (DOC) and particulate organic carbon (POC) with DOC passing through a 45 µm filter and POC being retained on a 45 µm filter. Carbon, originating from mineral sources, is generally referred to as inorganic carbon (IC) and includes carbon dioxide (CO₂), bicarbonate (HCO₃⁻), carbonate (CO₃²⁻), and carbonic acid (H₂CO₃). Water may also dissolve atmospheric CO₂ under certain conditions forming H₂CO₃ and subsequently HCO₃⁻ and CO₃²⁻.

Organic carbon consists almost entirely of a mixture of plant, microbial, and animal products in various stages of decomposition and which, upon entering recipient lakes, degrades at rates ranging from days to weeks for DOC, and weeks to years in the case of POC (Wetzel 2001). Allocthonous DOC may enter tributaries through precipitation, leaching, and decomposition (Gergel et. al. 1999). Degradation of lignin and cellulose results in the high composition of humic and fulvic acids (Engstrom 1987), giving the water a tea color, as is exhibited in northern Otsego Lake tributaries. Anthropogenic inputs from agricultural practices can significantly alter TC levels through erosion, diversion of flow, turnover of soil, fertilizer application, etc. When examined in concert with naturally occurring inputs of DOC from plant exudates and detrital leaching, such anthropogenic inputs are frequently many times higher in the summer and fall than at other times of the year (Kaplan et. al. 1980). DOC is extensively modified through microbial action in soils, streams, wetlands, and littoral areas, and so larger macromolecules are degraded into more bioavailable compounds. Bioavailability of riverine dissolved organic matter appears to be greater under low discharge conditions and decreases with distance downstream (Wetzel 2001). When DOC is exposed to inorganic particulate matter, such as the limestone substrates of the northern Otsego Lake watershed, it may sediment through abiotic adsorption to clay, organic, or calcium carbonate (CaCO₃) particles (Wetzel 2001; McDowell 1985; Hope et. al. 1994) and/or through biotic adsorption to algae or biofilms (Fiebig et. al. 1991) effectively carrying energy from its place of origin to its place of transformation (Wetzel 2001; McDowell 1985; Fiebig et. al. 1991). Degradation of DOC may also occur when chromophoric dissolved organic matter (CDOM) is partially photolysed by UV-A, UV-B, and photosynthetically active radiation (PAR) through bleaching and the conversion of its more labile constituents to CO₂ (Eatherall et. al. 1998; Wetzel 2001). Recalcitrant macromolecules may undergo burial at rates from 1-20 g C m⁻² yr⁻¹. However, there is evidence to suggest that burial efficiency increases with latitude indicating that burial efficiency is, at least partially, enhanced by colder water and the correspondingly greater dissolution of oxygen in these waters allowing oxidation to occur (Alin et. al. 2007). Although autochonous DOC represents only a

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small portion of total DOC, its several sources of production include the release of extracellular DOC by phytoplankton (Nalewajko et. al. 1969) as well as secretion by aquatic macrophytes in the littoral zone which release comparable amounts (Wetzel et. al. 1972; Wetzel 1990).

Inorganic carbon’s constituents include CO₂, HCO₃⁻, CO₃²⁻, and H₂CO₃ and may vary in a stream due to spatial differences in quantity and composition of soil water inputs from different watershed fragments as the watercourse flows through differing soils and also due to gains or losses of carbon due to in-stream processes (Dawson et. al. 2000). Stream turbulence, velocity, depth, and gradient may also influence IC losses (Rebsdorf et. al. 1991) or gains in streams. As water percolates through the soils it becomes enriched with adsorbed CO₂ due to plant and microbial action and the H₂CO₃ formed solubilizes the limestone substrate forming calcium bicarbonate (Ca(HCO₃)₂). Ca(HCO₃) is highly soluble in water and forms Ca++ and HCO₃⁻ ions. Much of the northern Otsego Lake watershed region is underlain by a limestone (CaCO₃) substrate allowing for high levels of HCO₃⁻ to be generated upon direct contact with H₂CO₃ illustrated by the following chemical equations (Wetzel 2001).

CO₂ (atmospheric) ↔ CO₂ (dissolved) + H₂O

CO₂ + H₂O ↔ H₂CO₃

H₂CO₃ ↔ H+ + HCO₃⁻

A study of North American river water reveals that an average of 80% of alkalinity is attributable to carbonate rock dissolution (Morel et. al. 1993) and on a global-discharge weighted basis over 97% of runoff has been classified as of the Ca(HCO₃)₂ type (Meybeck 1993b). The northern Otsego Lake watershed is reflective of these findings and exhibits carbonate substrates in the entire sampling area (Fetterman 2001). HCO₃⁻ concentrations predominate within waters with pH ranging between 7 and 9 and are several orders of magnitude greater than either CO₂ or CO₃²⁻ under these pH conditions. Calcareous lakes, such as Otsego, are heavily buffered by this highly dynamic CO₂ ↔ HCO₃⁻ ↔ CO₃²⁻ equation maintaining a pH >8 (Wetzel 2001). The total IC concentration in fresh water is governed largely by pH, which is dependent on the buffering reactions of H₂CO₃ and the amount of HCO₃⁻ and CO₃²⁻ dissolved during weathering processes (Wetzel 2001).

Nitrogen is a component in all amino acids, is incorporated into proteins, and is present in the bases that make up nucleic acids, such as DNA and RNA. In plants, much of the nitrogen is used in chlorophyll molecules, which are essential for photosynthesis and further growth (Smil 2000). Carbon to nitrogen ratios generally range from 50:1 in streams (Wetzel 2001) which may be explained by the high lignin and cellulose content in plant structural compounds, neither of which contains substantive amounts of nitrogen. Carbon to nitrogen ratios in lacustrine systems are generally lower, around 12:1 (Wetzel 2001); aquatic plants contain fewer structural components, as they are largely unnecessary in aquatic systems. Research suggests that enhanced deposition, as might occur with agricultural use, causes increased rates of soil matter accumulation (Berg et.al. 1997; Harrison et. al. 2000; Schulze et. al. 2000; Hagedoorn et. al. 2003) increasing soil carbon sequestration as well as the quantity of matter available for decomposition. Since aquatic systems can be nitrogen-limited, excessive N inputs can result in water quality degradation including toxic algal blooms, oxygen deficiency, habitat loss, decreases in biodiversity, and fishery losses (Rabalais 2002). Research suggests chlorophyll a

49

concentrations in Otsego Lake have dropped significantly over the last 10 years (Bauer 2010). This may be indicative of agricultural BMP’s effecting lower nutrient outputs, though it may also indicate zebra mussels are substantially impacting chlorophyll a concentrations, or that filtering by crustacean zooplankton has increased due to alewife (Alosa psuedoharengus) management (Waterfield and Cornwell 2012).

METHODS

Samples were collected weekly at 23 established sites along the 5 major tributaries in the northern catchment basin (see Figure 1; Hewett 1997). This work paralleled and complemented the continuing SUNY Oneonta BFS data collection efforts between 7 June and 9 August 2011 encompassing the northern Otsego Lake watershed (Zaengle 2012).

A Eureka Amphibian® Multiprobe was calibrated before use weekly based on manufacturer supplied instructions Eureka Env. 2004). Specific conductivity and pH levels for each northern Otsego Lake catchment site were recorded. Water samples were collected in 125mL Nalgene HDPE plastic containers which were filled and squeezed slightly to eliminate gaseous head space. Samples were stored on ice until returning to the SUNY Oneonta BFS. Upon return samples were stored at 4°C until analysis could be performed. In preparation for testing, 40mL clear glass vials and their PTFE septa were acid washed and dried in a convection oven at 100°C and to which, after cleaning, samples were transferred. Samples were analyzed for total organic carbon (TOC) and inorganic carbon (IC) content with a Shimadzu TOC-V CPH carbon analyzer. Total nitrogen analysis was performed on samples with a LACHAT QuikChem FIA+ Water Analyzer using the cadmium reduction method (Pritzlaff 2003) following peroxodisulfate digestion as described (Ebina et. al. 1983) and for nitrate+nitrite N using the cadmium reduction method (Pritzlaff 2003). Organic Nitrogen (ON) was calculated by subtracting nitrate/nitrite content from the total nitrogen (TN) values; ammonium content was assumed to be negligible based on past analysis of stream samples.

RESULTS

Results indicated a gradual decline in TOC from headwater sites to Otsego Lake while IC, pH, and conductivity all generally increased as watercourses approached the lake. Conductivity and IC relationships exhibit an R2 of 0.8544 indicating a strong correlation between the two measures. Nitrogen was difficult to generalize based on the multiple use characteristics and input variables of the watershed, though it tended to decreased from headwater sites to the lake when considering only headwater and stream mouth values. For comparative purposes, TOC and IC additional sampling was performed on 29 June 2011, encompassing major eastern Otsego Lake tributaries; results are included in this report. Mean TOC concentrations in eastern Otsego Lake tributaries were roughly the same as their northern counterparts, but IC concentrations were substantially lower in the eastern watershed. Minimum and maximum measures of note from stream headwaters to stream mouths across all dates in the northern Otsego Lake watershed include TOC ranging from 1.502 to 8.120 mg/L at MW1 and CC1 respectively, IC ranges from 21.10 to 77.77 mg/L at WC1 and MW2 respectively, ON measurements of 0.07 to 1.45 mg/L at WC3 and SB4 respectively, pH values from 6.97 to 9.48 at HC1 and SB3 respectively, and a conductivity range of 0.165 to 0.488 ms/cm at WC1 and SB3 respectively.

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Means for each site on each tributary are represented in Figures 2-6 and should be interpreted from right to left with sites ordered from their headwaters to their mouth at Otsego Lake. Figure 7 illustrates the relationship existing between IC and conductivity values at each of the 23 northern Otsego Lake sampling sites. Figure 8 displays TOC and IC characteristics of major eastern Otsego Lake tributaries on 29 June 2011 for comparison with the northern tributaries.

Figure 2. Mean total organic carbon (mg/L) between 7 June and 26 July 2011 along five tributaries constituting the northern Otsego Lake watershed. Left-most sites represent stream mouths while sites to the right indicate stream headwaters.

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Figure 3. Mean inorganic carbon (mg/L) between 7 June and 26 July, 2011 along five tributaries constituting the northern Otsego Lake watershed. Left-most sites represent stream mouths while

Figure 4. Mean organic nitrogen (mg/L) betw

sites to the right indicate stream headwaters.

een 7 June and 26 July 2011 along five tributaries constituting the northern Otsego Lake watershed. Left-most sites represent stream mouths while sites to the right indicate stream headwaters.

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Figure 5. Mean pH change between 7 June and 26 July 2011 along five tributaries constituting the northern Otsego Lake watershed. Left-most sites represent stream mouths while sites to the right indicate stream headwaters.

Figure 6. Mean conductivity (mS/cm) between 7 June and 26 July, 2011 along five tributaries constituting the northern Otsego Lake watershed. Left-most sites represent stream mouths while sites to the right indicate stream headwaters.

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Figure 7. Inorganic carbon (mg/L) and conductivity (mS/cm) relationship between 7 June and 26 July 2011 along five tributaries constituting the northern Otsego Lake watershed. Each point represents a northern Otsego Lake watershed sample site.

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Figure 8. Mean total organic carbon (mg/L) and inorganic carbon (mg/L) on 28 and 29 June 2011 encompassing the northern Otsego Lake watershed as well as five eastern Otsego Lake tributaries for compare and contrast purposes.

DISCUSSION

Based on a typical stream geochemical and topographical makeup common to a limestone substrate of central New York State, one would expect to find decreasing TOC and increasing IC, ON, pH, and conductivity along a stream gradient. The five tributaries of the northern Otsego Lake watershed generally parallel the expected results. However, additional anthropogenic influences in the watershed may impact these values. Eastern Otsego Lake tributaries’ comparatively low IC content is largely indicative of their differing geological substrate (Harman 1997), which is primarily Panther Mountain shale.

White Creek (WC) can be characterized as exhibiting consistent values along its course from its headwaters to mouth maintaining relative linearity in chemical makeup along its course (Figures 1-6). TOC (Figure 2) appeared relatively stable throughout, decreasing slightly, with IC (Figures 3 and 7) and conductivity (Figures 6 and 7) increasing slightly, and pH (Figure 5) increasing in line with other watercourses in the study. The most interesting aspect of White Creek was that nitrogen content decreased almost linearly along its flow to the lake.

IC, 4.

htly in the wetland between CC4 and CC5 while (Figures 3 and 7) and conductivity (Figures 6 and 7) fell minimally. The large fall in ON

(Figure 4) between CC4 and CC5 appears to almost fully negate the rise attributable to the CC3 to CC4 portion of the watercourse.

well as s

alues these

d HC7 respectively.

ook

Cripple Creek (CC) sampling sites CC1-CC4 exhibited characteristic results for TOC,pH, and conductivity (Figures 2, 3, 4, 6 and 7). ON (Figure 4) fell markedly between CC2 andCC3. Furthermore, the there was a comparatively large drop in pH (Figure 5) from CC3 to CCTOC (Figure 2) and pH (Figure 5) rose very sligIC

Hayden Creek (HC) is similar to Cripple Creek in both its agricultural inputs as the presence of a wetland along its course. Hayden Creek’s headwater at Summit Lake (HC1) ia challenging sampling site with its accompanying soft sediment and may not provide meaningful results to the overall analysis. Values constituting IC, ON, pH, and conductivity (Figures 3, 4, 5, 6 and 7) generally rose as Hayden Creek approached the lake while TOC v(Figure 2) declined. Nitrogen rose more rapidly between HC3 to HC4 and HC5 to HC7 butrises were virtually negated by the time Hayden Creek reached HC4 an

Shadow Brook (SB) exhibited results typical for most of the tributaries observed in the northern Otsego Lake watershed . TOC (Figure 2) reflected a gradual decline along its length while IC (Figures 3 and 7) and conductivity (Figures 6 and 7) virtually mirrored each other from Shadow Brook’s headwaters to Otsego Lake. The pH (Figure 5) steadily rose as Shadow Brflowed toward the lake while nitrogen values rose between SB3 and SB4 and subsequently declined between SB4 and SB5.

Mount Wellington (MW) was atypical of the other sampled sites with TOC (Figure 2) exhibiting an increase from MW1 to MW2. This might be explained by several factors such as the MW2 sample site being located at the same elevation as the lake itself, little or no flow

55

outward, and/or inward flow from the lake itself. IC (Figures 3 and 7) increased substantially in its short course in conjunction with conductivity (Figures 6 and 7) but pH (Figure 5) fell. Nitrogen (Figure 4) increased along its course more rapidly than any other tributary sampled in the northern Otsego Lake watershed with MW1 and MW2 immediately adjacent to potential anthropogenic influences.

oversta ts

REFERENCES

Berg, B. and E. Matzner. 1997. Effect of N deposition on decomposition of plant litter and soil rganic matter in forest systems. Environ. Rev. 5 pp. 1-25.

Croswell, K. 1996. Alchemy of the heav 0-385-47214-5.

ntrol

Eatherall, A., P.S. Naden, and D.M. Cooper. 1998. Simulating carbon flux to the estuary: The first step. The Science of the Total Environment, 210/211 (1998) Pg. 519-533. Ebina, J., T. Tsutsui and T. Shirai. 1983. termination of total nitrogen and total phosphorous in water using peroxodisulf ater Res. 17(12):1712-1726.

Engstro or Fisheries and Aquatic Sciences 44:1306-1314.

CONCLUSION

This study’s findings should assist future research into TOC, IC, and nitrogen loading as it relates to the northern Otsego Lake watershed. While future research may indeed focus on Otsego Lake, the importance of watershed wetlands in the carbon/nitrogen cycle cannot be

ted. Investigating seasonal variation in carbon/nitrogen cycles of both Otsego Lake and itributaries will further our understanding of natural fluxes while simultaneously contributing toour understanding of anthropogenically enhanced loading regimes.

Alin, S.R. and T.C. Johnson. 2007. Carbon cycling in large lakes of the world: A synthesis of

production, burial, and lake-atmosphere exchange estimates. Global Biogeochemical Cycles, Vol. 21, GB3002. Bauer, H. 2010. Chlorphyll a analysis of Otsego Lake. In 43rd Annual Report. SUNY Oneonta

Bio. Fld. Sta., SUNY Oneonta.

o

ens. Anchor. ISBN http://kencroswell.com/alchemy.html. Dawson, J.J.C., C. Bakewell, and M.F. Billett. 2000. Is in-stream processing an important co

on spatial changes in carbon fluxes in headwater catchments? The Science of the Total Environment 265 (2001) Pg. 153-167.

Simultaneous deate oxidation. W

m, D.R. 1987. Influence of vegetation and hydrology on the humus budgets of Labrad

lakes. Canadian Journal of Eureka Environmental Engineering. 2004. Manta water quality startup guide. Austin, TX.

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Fetterm n, A.R. 1997. Geochemistry of surface and subsurface water flow in the Otsego Lake

iebig, D.M. and A.M. Lock. 1991. Immobilization of dissolved organic matter from

ergel, S.E., M.G Turner, T.K. Kratz. 1999. dissolved organic carbon as an indicator of the

agedoorn, F, D. Spinnler, and R. Siegwolf. 2003. Increased N deposition retards mineralization

arman, W.N., L.P. Sohacki, M.R. Albright, and D.L.Rosen. 1997. The State of Otsego Lake,

arrison, A.F., D.D. Harkness, A.P. Rowland, J.S. Garnett, and P.J. Bacon. 2000. Annual carbon

orest Ecosystems. Ecological Studies 142. Springer, Berlin, Heidelberg, New York. Pg. 237-

Oneonta.

ater: fluxes and processes. Environ. Pollut. 1994 84:301-324.

ceanogr. 25(66):1034-1043.

Morel, F.M.M. and J.G. Hering. 1993. Principles and Applications of Aquatic Chemistry. John

Wiley and Sons. New York. 374 pp.

abasin. Occasional Paper #35. SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

F groundwater discharging through the streambed. Freshwater Biol. 1991 26:45-55. G scale of watershed influence on lakes and rivers. Ecological Applications Vol. 9, No. 4

Pg. 1377-1390. H of old soil organic matter. Soil Biol. Biochem. 35:1683-1692. H 1936-1996. Occasional Paper #30. SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta. H and nitrogen fluxes in soils along the European forest transect determined using 14C- bomb. In: Schulze, E.D. (ed.). Carbon and Nitrogen Cycling in European F

256. Hewett, B. 1997. Water quality monitoring and the benthic community in the Otsego Lake

watershed. In 29th Annual Report (1996). SUNY Oneonta Bio. Fld. Sta., SUNY Hope, D., M.F. Billett, and M.S. Cresser. 1994. A review of the export of carbon in river w Kaplan, L.A., R.A. Larson, and T.L. Bott. 1980. Patterns of dissolved organic carbon in transport. Limnol. and O McDowell, W.H. 1985. Kinetics and mechanisms of dissolved organic carbon retention in a headwater stream. Biogeochemistry 1985 1:329-352. McShaffrey, D. 2006. Professor of Biology, Environmental Science and Leadership. Biology

Department. Marietta College. http://www.marietta.edu/~mcshaffd/. Meybeck, M. 1993b. Natural sources of C, N, P, and S. In Wollast R., F.T. Mackenzie, and L. Chou, eds. Interactions of C, N, P, and S biogeochemical cycles and global change. Springer-Verlag. Berlin. Pg. 163-193.

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Nalewa rand of phytoplankton populations from Lake Ontario. Canadian Journal

of Botany 47:405-413.

wastewaters by flow injection analysis. QuikChem®Method 10-115-01-1-F. LACHAT Instruments. Loveland, CO.

2002 Vol. 31 No. 2 31:102-112.

ed to soil type and land use. Freshwater Biol. 25:419-435.

Smil, V

etzel, R.G. 2001. Limnology, lake and river ecosystems, 3rd Ed. Academic Press. San Diego,

aengle, O. 2012. Continued water quality monitoring of five major tributaries in the Otsego

jko, C. and L. Marin. 1969. Extra-cellular production in relation to growth of fou planktonic algae Pritzlaff, D. 2003. Determination of nitrate-nitrite in surface and

Rabalais, N.N. 2002. Nitrogen in aquatic ecosystems. Ambio Rebsdorf A., N. Thyssen, and M. Erlandsen. 1991. Regional and temporal variation in pH, alkalinity, and carbon dioxide in Danish streams, relat

. 2000. Cycles of life. Scientific American Library. New York Schulze, E.D. (Ed.). 2000. Carbon and nitrogen cycling in European forest ecosystems. Ecological Studies 142. Springer, Berlin, Heidelberg, New York. 476 pgs. W

San Francisco, New York, Boston, London, Sydney, Tokyo. 1006 pgs.

ZLake watershed. In 44th Annual Report (2011). SUNY Oneonta Bio. Fld. Sta., SUNYOneonta.

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Upper Susquehanna River Water Quality Monitoring:

Monitoring water quality and fecal coliform bacteria in the Upper Susquehanna River, summer 2011

B. Scott1

INTRODUCTION

The Susquehanna River is a major water source in the Northeastern United States that

contributes more than 50% of the freshwater that enters into the Chesapeake Bay (SRBC 2009). The Susquehanna River also provides a source of electricity and drinking water for people living along the river. At peak, it discharges 446 million gallons of water per day (SRBC 2009). The Susquehanna River flows south approximately 444 miles from Otsego Lake, Cooperstown, NY to Havre de Grace, MD, where it empties into the Chesapeake Bay and the Atlantic Ocean. Excess nutrients carried into the Bay contribute to accelerated eutrophication and ultimately result in degraded water quality and habitat for estuarine species, thus efforts are focused on reducing nutrient inputs to the Bay (SRBC 2009). During the months of June, July and August, the Upper Susquehanna was sampled at nine sites and tested for temperature, dissolved oxygen, specific conductivity, nitrates+nitrites, total nitrogen, total phosphorous and fecal coliform levels. The Upper Susquehanna River is evaluated yearly in order to survey the physical and chemical parameters that are important considerations for the treatment plant relative to their permitted discharge. The Cooperstown Wastewater Treatment Plant treats waste from both the village of Cooperstown and Basset Hospital then releases the treated effluent into a treatment wetland (Albright and Waterfield 2011) which drains to the Susquehanna River. Water quality is monitored in order to identify the introduction of any new unauthorized substance that could jeopardize the water quality.

1 F.H.V. Mecklenburg Conservation Fellow, summer 2011. Present affiliation: Long Beach High School. Funding provided by the Village of Cooperstown.

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METHODS

Between 22 June and 10 August 2011, nine sites along the Upper Susquehanna River between Otsego Lake and Oaks Creek were sampled weekly (Figure 1). Additional sites were sampled along the southern end of Otsego Lake prior to 2009 but have been discontinued. Table 1 provides descriptions of the sample site locations and Figure 1 provides a visual representation of the sites. Table 1. Locations and descriptions of Upper Susquehanna River sampling sites.

Site Distance

from source Description

3 144 m Under the Main Street Bridge; accessed via slope beside the bridge.

6a 1012 m Below the dam at Bassett Hospital; accessed from the northern corner of the lower parking lot of Bassett Hospital.

7 1533 m Below the dam at Bassett Hospital; accessed from the southern corner of the lower parking lot of Bassett Hospital.

8 1724 m Under the Susquehanna Ave. bridge west of the Clark Sports Center; accessed via the slope beside the bridge.

12 4119 m Just above the sewage discharge of the Cooperstown Wastewater Treatment Plant, nearby Cooperstown High School. Accessed by an opening in the fence.

16 5460 m Small bridge perpendicular to the road on Clark Property. Accessed by crossing a gated bovine grazing area (cow field).

16a 5939 m Distinct bend in river alongside road on Clark property, in field directly across from large house with hay rolls in front. Accessed by long path found on the right side of the field. Be cautious of barbed wire.

17 8143 m Abandoned bridge on Phoenix Mill Rd.

18 9867 m Railroad trestle about 200 m north of the railroad crossing on Rt. 11 going out of Hyde Park, accessed by walking on the railroad tracks.

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Figure 1. 2011 Upper Susquehanna River sampling sites.

Each site was sampled weekly between the hours of 0800 and 1200. A Eureka® Manta multiprobe digital microprocessor was used to measure temperature, pH, specific conductivity, and dissolved oxygen levels. Probes were calibrated within 24 hours prior to usage. Water samples were collected in 125ml acid-washed Nalgene® bottles to be tested for nitrate+nitrite, total nitrogen, and total phosphorous by a Lachat®QwikChem FIA + Water Analyzer. Nitrate+nitrite was determined by the cadmium reduction method (Pritzlaff 2003) and total nitrogen by the cadmium reduction method after peroxodisulfate digestion (Ebina et. al 1983). Total phosphorous was determined by the ascorbic acid method following persulfate digestion (Liao and Martin 2001).

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Water samples for fecal coliform analysis were also taken at each site. Samples were kept in a cooler with ice until testing in order to minimize microbial growth. At the lab, the samples were tested for fecal coliform using the membrane filter method (APHA 1992). A total of six subsamples ranging from 5 ml to 50 ml were used from each sample and run through a pre-sterilized filter with a low-pressure vacuum. Filters were subsequently placed into sterile Milipore® culture dishes along with absorbent pads saturated with nutrient broth for the fecal coliform. All equipment that came into contact with the samples was sterilized in 70% ethanol then washed in hot tap water and dilution water in order to prevent cross-contamination between samples. In addition, the forceps that were used to move filters were sterilized by dipping them in 90% ethanol which was then burned off by passing through a candle flame. Following filtration sample dishes were placed into waterproof plastic containers which were submerged in a circulating water bath for 24 hours at 44.5 degrees Celsius. The process was finalized once the number of blue fecal coliform on each culture dish was counted and recorded as colonies/100ml.

RESULTS AND CONCLUSIONS

Temperature

Temperature readings for the summer of 2011 can be seen on Figure 2. Readings for the summers of 2004-2011 can be seen in Figure 3. The mean temperature of the Upper Susquehanna River for the summer of 2011 was 22.65˚C. The highest temperature recorded this year was 24.52◦C at sample site SR 6A (1012m. from the source) on 2 August. The lowest temperature recorded was 20.96◦C at SR18 (9867m. from the source) on 7 July.

Figure 2. Average temperature profile for the upper Susquehanna River, summer 2011.

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Figure 3. A profile of mean temperature along the upper Susquehanna River, summers of 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011.

pH

pH measures the degree acidity of a liquid sample. Determining pH is relevant when monitoring water quality because a drastic change in pH may indicate an introduction of a new substance in the water. pH readings for the summer of 2011 can be seen on Figure 4. Readings for summers 2004-2011 can be seen on Figure 5. The average pH for this summer was 7.95. pH levels for the summer of 2011 were generally stable, being between 7.8 (SR16A) and 8.1 (SR6A).

Figure 4. Mean pH profile for the upper Susquehanna River, summer 2011.

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Figure 5. A profile of pH levels along the Susquehanna, summers of 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011.

Conductivity

Conductivity is the measure of the water’s ability to conduct electricity based upon the amount of dissolved ions in it. Measuring conductivity is important because certain species of aquatic organisms can only survive in specific conductivity ranges. Changes in conductivity indicate changes in ionic content, potentially indicating that the water is being impacted by pollution. Conductivity levels for the summer of 2011 can be seen in Figure 6. Readings for summers 2004-2011 can be seen in Figure 7. The highest conductivity recorded this summer was 313 umho/cm at SR18. Lowest recorded was 227 umho/cm at SR3.

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Figure 6. Summary of mean specific conductivity levels of the upper Susquehanna River, summer 2011.

Figure 7. Profiles of specific conductivity levels along the Susquehanna River, summers 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010(Bauer 2011), and 2011.

Dissolved Oxygen

Aquatic organisms require specific amounts of oxygen dissolved in the water which makes monitoring dissolved oxygen necessary. Temperature plays a large part in dissolved oxygen levels, as colder water can hold more oxygen in solution. Dissolved oxygen levels for summer of 2011 can be seen on Figure 8. Readings for summers 2004-2011 are displayed on

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Figure 9. This year’s average concentration of dissolved oxygen was 8.04 mg/l, with the highest dissolved oxygen concentration 9.17 mg/l (SR8) and the lowest concentration 6.9 mg/l (SR12).

Figure 8. Dissolved oxygen concentrations in the upper Susquehanna River, summer 2011.

Figure 9. Profiles of dissolved oxygen concentrations in the Susquehanna River, summers 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011.

Total Phosphorus Phosphorus is the limiting factor in many aquatic ecosystems. Algal blooms and subsequent decreased dissolved oxygen levels and may result from increases in phosphorus levels. Phosphorus can be found in urban runoff and treated wastewater effluent (the local

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wastewater treatment plant is not required to remove phosphorus). This summer’s phosphorus levels were lower than those of previous years as seen in Figure 10. The reduction of total phosphorus in the water cold be in part due to the Wastewater Treatment Plant’s recent use of a restored wetland for tertiary treatment (Albright and Waterfield 2011). Concentrations for summers 2004-2011 can be seen on Figure 11.

Figure 10. Mean phosphorus concentrations along the upper Susquehanna River, summer 2011.

Figure 11. Mean phosphorus concentrations along the upper Susquehanna River for 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland), 2010 (Bauer 2011), and 2011.

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Nitrogen

Nitrogen is an essential nutrient for algae. Nitrogen in inorganic substances and the nitrogen used organically are collectively referred to as total nitrogen. Nitrogen levels have also been reduced compared to past results, apparently by the treatment wetland (Albright and Waterfield 2011). Nitrate + nitrite levels for the summer of 2011 can be seen in Figure 12. Readings for summers 2004-2011 can be seen in Figure 13. The total nitrogen levels for the summer of 2011 can be seen in Figure 14. Readings for summers 2004-2011 can be seen in Figure 15.

Figure 12. Nitrate + nitrite concentrations along the upper Susquehanna River for summer 2011.

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Figure 13. Average nitrite+nitrate concentrations along the upper Susquehanna River for summers 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011.

Figure 14. Total nitrogen levels concentrations along the upper Susquehanna River, summer 2011.

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Figure 15. Average total nitrogen concentrations along the upper Susquehanna River, summers 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011. Fecal Coliform

Fecal Coliform bacteria can indicate the presence of sewage contamination in a waterway and the possible presence of other pathogenic organisms. Fecal coliform bacteria can enter rivers through direct discharge of waste from mammals and birds, from agricultural and storm runoff, and from inadequately treated human sewage (APHA 1992). Fecal coliform levels for the summer of 2011 can be seen in Figure 16. Readings for the summers 2004-2011 can be seen in Figure 17.

Figure 16. Fecal coliform levels along the upper Susquehanna River, summer 2011.

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Figure 17. Average fecal coliform levels for summers along the upper Susquehanna River, summers 2004 (Hill 2005), 2005 (Bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), and 2011.

CONCLUSION

Data collected in the summer of 2011 indicated a decrease in total phosphorus and

nitrogen levels in comparison to previous years. This could reflect that the Wastewater Treatment Plant’s new method of polishing the effluent by using the treatment wetland has been successful. The physical parameters of the water quality showed little deviation from previous years.

REFERENCES

Albright, M.F. and Waterfield H.A. 2011 Monitoring the effectiveness of the Cooperstown

wastewater treatment wetland. In 43th Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

APHA, AWWA, WPCF. 1992. Standard methods for the examination of water and wastewater.

17th Ed. American Public Health Association, Washington D.C.

Bauer, E. 2006. Monitoring the water quality and fecal coliform in the upper Susquehanna River, summer 2005. In 38th Ann. Rept. (2005). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Bauer, H. 2011 Monitoring the water quality and fecal coliform in the upper Susquehanna River, summer 2010. In 43th Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Coyle, O.L. 2008. Monitoring water quality and fecal coliform bacteria in the Upper Susquehanna River, summer 2007. In 40th Annual Report (2007), SUNY Oneonta Bio. Fld Sta., SUNY College at Oneonta.

Ebina, J.T. Tsutsui, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total

phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1712-1726. Eureka Environmental Engineering. 2004. Manta water quality probe startup guide. Austin, TX. Hill, J.2005. Monitoring the water quality and fecal coliform in the upper Susquehanna River,

summer 2004. In 37th Ann. Rept. (2004). SUNY Oneonta Bio. Fld Sta., SUNY College at Oneonta.

Heiland, L. 2010. Monitoring water quality and fecal coliform bacteria in the upper Susquehanna River, summer 2009. In 42st Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Liao, N. 2001. Determination of ammonia by flow injection analysis. QwikChem® Method 10-

115-01-0-F. Lachat Instruments. Loveland, Colorado. Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis

chloriometry (acid persulfate digestion method). QwikChem® Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

Matus, J.E. 2009. Monitoring water quality and fecal coliform bacteria in the upper Susquehanna

River, summer 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Pritzlaff, D. 2003. Determination of nitrate+nitrite in surface and wastewaters by flow injection

analysis. QwikChem® Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado. Susquehanna River Basin Commision. 2009. http://www.srbc.net/about/index.htm. Zurmuhlen, S. J. 2007. Monitoring water quality and fecal coliform bacteria in the upper

Susquehanna River, summer 2006. In 39th Annual Report (2006), SUNY Oneonta Bio. Fld. Sta., SUNY College at Oneonta.

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http://www.srbc.net/about/index.htm

ARTHROPOD MONITORING:

Mosquito Studies – Thayer Farm W. L. Butts1

A rebound of mosquito populations from a low point in 2010 reflected precipitation patterns, with Coquillettidia perturbans (Walker) present and most commonly encountered prior to a period of unusually heavy precipitation which resulted in the presence of unusually high levels of surface water in areas not flooded in the previous year and which persisted for enough time to allow temporary water (i.e. flood water) species to complete development. The extent to which the large populations of the latter species will contribute to future populations may have been negatively affected by a period of somewhat lower temperatures. This may have exerted negative pressure by not allowing for sufficient development to the level at which viable eggs could be produced.

Table 1. Trap placements varied and are described relative to a large blown down tree immediately adjacent to the trail and beyond the path to the boat launch site at the pond west of the Upland Interpretive Center (UIC) and to the drainage outflow therefrom. (On 11 July a trap was set at the edge of the pond below the sap bush stand). Trap Site Date (2011) Trap____________ Outflow beyond Blowdown V-14 V-31; VI-13, 20, 29;VII-6; Light & CO2

IX-22; IX-26; IX-11 (VI-29 light only) Edge of pond below Sap Bush V11-11 Light & CO2 Between Step Ponds V11-19 Light & CO2 Edge of Wood on path to Boat Launch X-4 Table 2. Mosquitoes collected by all methods Date Trap Method Site Species Number V-14 Light Edge of Blowdown Coquillettidia perturbans (Walk) (1) VI-13 Light & CO2 Drain outflow-pond below UIC Anopheles punctipennis Say (1) VI-20 Light & CO2 “ “ C. perturbans ( Walk.) (7) VI-29 Light “ “ C. perturbans ( Walk.) (1) VII-6 Light & CO2 “ “ C. perturbans ( Walk.) (3) VII-20 Alighting Sap Bush An. punctipennis Say (1) VII-26 Alighting Step Ponds Ochlerotatus trivittatus (Coq.) (1) VIII-2 Alighting Step Ponds Ochlerotatus hendersoni (Coq.) (2) VIII-9 Alighting Outlet beyond step ponds Anopheles sp. (1) Oc. hendersoni (Coq.) (1) IX-29 Alighting Pond below UIC Oc. trivittatus (Coq.) (6) Aedes vexans (Meigen) (2) Aedes cinereus (Meigen) (1)

1 Professor emeritus. SUNY Oneonta Biological Field Station.

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Monitoring the effectiveness of the Cooperstown wastewater treatment wetland, 20111

M.F. Albright

BACKGROUND (from Albright and Waterfield 2011)

In 2002, the US Army Corp of Engineers (ACE) initiated a 1.6 million dollar Upper

Susquehanna River Watershed-Cooperstown Area Ecosystem Restoration Feasibility Study And Integrated Environmental Assessment. Authorized by the U.S. Congress, the pilot program was to “use wetland restoration, soil and water conservation practices, and non-structural measures to…improve water quality and wildlife habitat…in the Upper Susquehanna River Basin…” (ACE 2001). Initially identified were eight Field Assessed Benefit and Design Strategy sites (FABADS) in Otsego County. During 2003, the SUNY Oneonta Biological Field Station (BFS) monitored two restored sites which receive agricultural runoff as well as a local “pristine reference site”. Comparisons were made between inflows and outflows, and between the wetlands, of concentrations of different nutrient fractions, suspended sediments and fecal coliform bacteria. This short term study did indicate water quality improvements when nutrient levels at the inflow were elevated (Fickbohm 2005), though it is probable that not enough time had elapsed to allow these systems to naturalize to the point where treatment potential was realized.

A third ACE restoration wetland was sited in the outskirts of the Village of

Cooperstown adjacent to the municipal sewage treatment facility (Figure 1). The primary function of this 3 acre wetland was phosphorus and nitrogen removal, potentially by converting this site into a treatment wetland for the Village’s municipal effluent. However, at that time, funds to deliver the effluent to the wetland were lacking. The wetland design, provided by Ducks Unlimited, did not necessarily follow that generally utilized for treatment wetlands.

In 2009, funding was provided by the Village of Cooperstown’s Sewer Reserve Fund to

hire the services of Lamont Engineering to evaluate alternatives to address nutrient reduction from the wastewater treatment plant (Jackson 2009). A more restrictive SPDES permit by the NYSDEC regarding nutrient loading to the Susquehanna River is consistent with New York State being cosignatory with the Chesapeake Bay Nutrient Reduction Strategy. The engineering report evaluated approaches to reducing phosphorus and nitrogen introduced into the Susquehanna River, their capital and annual operational costs, and expected nutrient reductions. In conclusion, it was recommended that utilizing the existing wetland for tertiary treatment would likely meet the nutrient reduction goals while costing substantially less than other approaches (i.e., addition of chemical coagulants, modification to the treatment plant, etc.).

1 Funding for this project was provided by the Village of Cooperstown.

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Figure 1. Bathymetric map of the wastewater treatment wetland, Cooperstown, NY (modified from Robb 2012). Rationale for monitoring

Wetlands have been used as water treatment cells for a number of years, but, until recently, only on a very limited basis. Since the mid 1990s, however, the number of constructed wetlands, having a broad range of system configurations and treatment applications, has increased markedly (Kadlec and Wallace 2009). When associated with municipal sewage outfalls, the parameters that are most often targeted for reduction are phosphorus, various nitrogenous compounds (ammonia, nitrate, total nitrogen), suspended solids and biological oxygen demand. The demonstrated effectiveness of the removal of these constituents has been promising, though quite variable, as design and site characteristics are, in practically every case, unique. Because of this, every time a treatment wetland is utilized, the opportunity exists to collect meaningful data which can aid in the design of future systems. More directly, data collection at some level is necessary to evaluate whether or not the goals of the treatment wetland, and the regulated limits of the parameters, are met. For the Cooperstown WWT wetland, the concentration limit requirements of total phosphorus, total nitrogen, ammonia and nitrates are not more stringent under the new SPDES/Chesapeake Bay Nutrient Reduction Strategy than they had been. It is not likely that concentrations leaving the wetland will be any higher than those entering it (excepting some short-term, meteorologically driven events). Ongoing studies of the monitoring of nutrient reduction dynamics could provide insight into, among other things, modification of the

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wetland’s flow patterns, depth, substrate composition, plant assemblages, etc. which might enhance performance.

METHODS

In order to most accurately quantify nutrient export from the wetland, efforts were made to estimate flow moving through the outlet device. A V-notch weir was constructed of doubled ¾” treated plywood (glued and screwed together). The notch was beveled ~30o (with the bevel facing downstream), and a metal 90o edge was fastened to the upstream face, to reduce friction. A scaled gauge was attached to upstream face, off to the side, so that water level could be recorded. An adhesive-backed gasket was used to line the edges of the downstream face of the weir, and the bottom edge, to ensure that no leakage occurred around or under the device. The top four boards were removed from the flood control device and the weir was inserted into the channels. Additionally, a Solinst® Levelogger, a pressure-transducer depth recorder, was purchased and attached to the upstream face of the weir, the intention being to collect a continuous log of water heights above the V-notch for flow determination. However, the flow values logged in this manner exhibited such a discrepancy with the metered flow of the wastewater treatment plant that they were considered unreliable and were not used. Efforts in 2011 focused on direct reading of the gauge on the weir face. Robb (2012) mounted a programmable Reconyx® trail camera so that it would capture images of the gauge at 15-minute intervals. In the absence of moderate rainfall (> ~ 1 cm/24 hr), the mean daily inflow from the wastewater treatment plant equaled the outflow from the wetland. During wetter periods, a small stream entering the west side of the wetland can contribute enough flow so that the outflow exceeds the input from the treatment plant for short periods of time. Efforts to accurately estimate the flow at the outlet structure were further compounded over 2011 by activities of muskrat, which plugged the surface outflow structure, and beaver, which were believed to plug the subsurface pipe leading to the outflow structure. Eventually, efforts to gauge the flow were abandoned and the flow of effluent into the wetland was assumed to equal the flow out of it. Sampling did not coincide with runoff events in order to minimize their influence.

Sampling began in February 2010, and was done monthly through May 2010 to

evaluate nutrient conditions prior to the diversion of effluent to the wetland (which commenced on 17 June 2010). Thereafter, samples were collected two to four times a month from the wastewater treatment plant (effluent), the wetland’s outlet and the stream feeding the wetland (to evaluate contributions from this source). This report summarizes results through December 2011. Samples were processed according to automated methods using a Lachat QuikChem FIA+ Water Analyzer. Samples were analyzed for total phosphorus using ascorbic acid following persulfate digestion (Liao and Martin 2001), total nitrogen using the cadmium reduction method (Pritzlaff 2003) following peroxodisulfate digestion Ebina et.al (1983), ammonia using the phenolate method (Liao 2001), and for nitrate+nitrite nitrogen using the cadmium reduction method (Pritzlaff 2003). Missing values were approximated by using existing data.

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RESULTS

Prior to the wetland receiving effluent, the outflowing concentrations of ammonia were below detection, nitrate averaged 0.28 mg/l, total nitrogen averaged 0.72 mg/l and total phosphorus averaged 0.043 mg/l. For the tributary inflow to the wetland from February 2010 through December 2011, mean nutrient concentrations were 0.02 mg/l (SE= 0.01) for ammonia, 0.28 mg/l (SE= 0.04) for nitrite+nitrate, 0.47 mg/l (SE= 0.05) for total nitrogen and 0.04 mg/l (SE= 0.01) for total phosphorus. The typical low flows and low nutrient concentrations of this tributary indicate that its influence on calculating nutrient retention rates, and investigating nutrient transformations, is minimal.

Summaries of ammonia, nitrite+nitrate, total nitrogen and total phosphorus following the diversion of effluent to the wetland are provided in Tables 1-4. For each parameter, mean monthly concentrations of the wastewater effluent and wetland’s outfall are given (mg/l), as are total monthly nutrient volumes (kg), the volume of nutrients retained (kg) and the mean retention rate (%).

Between June 2010 and December 2011, the total amount of nutrients retained by the

treatment wetland included 600kg of ammonia, 7,100kg of nitrate, 38,00kg of total nitrogen and 500kg of total phosphorus. The monthly rates of retention of ammonia varied much more so than did other nutrients, and this seemed mainly due to high variability of its concentration in the treatment plant effluent (mean= 1.86 mg/l, SE= 0.36); concentrations were lower and less variable at the wetland’s outlet (mean= 1.20 mg/l, SE= 0.17). This temporal variation led to calculated negative retention rates (or release) of ammonia in some months. Overall, the mean retention declined from about 42% in 2010 to 27.4% in 2011. Retention of both nitrate and total nitrogen has been fairly constant, at 28% to 30% retention for both during both years. The retention of total phosphorus declined from about 36% in 2010 to about 15% in 2011. In 2011, retention was lowest in summer months whereas that was when it was highest in 2010 (at the onset of the treatment wetland’s use). Phosphorus removal would be expected to decline if the main mechanism for removal is sediment binding (as the sediments become saturated) as opposed to biological uptake (Kadlec and Wallace 2009).

Given that this wetland was designed more for waterfowl habitat than for water quality improvement, the nutrient removal capacity seems promising. As vegetation densities increase, so should nutrient reduction, both directly though vegetative uptake and enhanced microbial denitrification due to increased microsites (Kadlec and Wallace. 2009). Investigations into phosphorus uptake by rooted plants at the Cooperstown wetland provided conflicting results. Olsen (2011) found elevated phosphorus content in the leaf tissue of reed canary grass (Phalaris arundinacea) within the wetland than that of plants in nearby areas not influenced by the treatment wetland. However, similar investigations in 2011 on reed canary grass and cattail (Typha sp.) did not show meaningful differences in phosphorus uptake (Gazzetti 2012).

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Table 1. Mean monthly concentrations of ammonia in the wastewater effluent and wetland’s outfall (mg/l), total monthly ammonia volumes (kg) entering and leaving the wetland, the volume of ammonia retained (kg) and the mean retention rate (%). Month Eff flow NH4 (kg)

CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET.Jun-10* 1728 4.10 1.41 63.8 21.9 41.8 65.6Jul-10 1692 0.31 1.03 16.1 54.0 -37.9 -235.5

Aug-10 1526 5.35 2.46 252.9 116.2 136.8 54.1Sep-10 1186 2.19 1.17 77.9 41.6 36.3 46.6Oct-10 1476 2.19 1.17 100.2 53.5 46.7 46.6Nov-10 1447 0.60 0.45 26.0 19.7 6.3 24.3Dec-10 1330 0.60 0.48 23.9 19.1 4.9 20.32010 560.9 326.1 234.8 41.9

Jan-11 1222 0.68 0.478 24.9 17.5 7.4 29.6Feb-11 1319 2.68 2.488 98.8 91.8 6.9 7.0Mar-11 2707 4.30 1.995 360.4 167.4 193.0 53.6Apr-11 2824 1.96 1.883 166.2 159.5 6.7 4.0May-11 2816 0.68 1.134 59.6 99.0 -39.4 -66.0Jun-11 2495 2.15 1.816 161.1 135.9 25.2 15.6Jul-11 1862 0.54 0.953 31.1 55.0 -23.9 -77.0


To date 1893.5 1293.1 600.4 31.7* partial month Projected Table 2. Mean monthly concentrations of nitrite+nitrate in the wastewater effluent and wetland’s outfall (mg/l), total monthly nitrite+nitrate volumes (kg) entering and leaving the wetland, the volume of nitrite+nitrate retained (kg) and the mean retention rate (%).

Month Eff flow NO2+NO3 (kg)CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET.

Jun-10* 1728 11.85 8.05 184.3 125.2 59.1 32.1Jul-10 1692 9.37 7.65 491.2 401.0 90.2 18.4

Aug-10 1526 9.13 5.75 432.2 272.1 160.1 37.0Sep-10 1186 10.85 5.80 385.8 206.2 179.6 46.6Oct-10 1476 10.70 6.43 489.6 294.2 195.4 39.9Nov-10 1447 11.38 8.33 493.9 361.4 132.4 26.8Dec-10 1330 9.15 9.65 365.1 385.0 -20.0 -5.52010 2842.0 2045.1 796.9 28.0

Jan-11 1222 13.35 13.150 489.5 482.2 7.3 1.5Feb-11 1319 12.70 11.280 468.9 416.5 52.4 11.2Mar-11 2707 5.31 4.100 445.5 344.0 101.5 22.8Apr-11 2824 6.75 3.707 571.6 314.0 257.5 45.1May-11 2816 8.83 6.665 770.9 581.9 189.0 24.5Jun-11 2495 10.48 5.575 783.9 417.2 366.7 46.8Jul-11 1862 9.44 7.850 545.0 453.2 91.8 16.8


To date 9953.0 7139.4 2813.6 28.3* partial month

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Table 3. Mean monthly concentrations of total nitrogen in the wastewater effluent and wetland’s outfall (mg/l), total monthly total nitrogen volumes (kg) entering and leaving the wetland, the volume of total nitrogen retained (kg) and the mean retention rate (%). Month Eff flow TN (kg)

CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET.Jun-10* 1728 17.30 9.51 269.0 147.9 121.2 45.0Jul-10 1692 14.10 12.50 739.6 655.7 83.9 11.3


Jan-11 1222 16.48 16.375 604.1 600.4 3.7 0.6Feb-11 1319 19.28 14.875 711.7 549.2 162.5 22.8Mar-11 2707 10.20 6.775 855.8 568.4 287.4 33.6Apr-11 2824 9.38 5.942 794.9 503.4 291.6 36.7May-11 2816 11.45 9.075 999.7 792.3 207.4 20.7Jun-11 2495 17.58 8.338 1315.3 624.0 691.3 52.6Jul-11 1862 14.46 11.038 835.0 637.2 197.7 23.7

Aug-11 1859 11.11 12.350 639.8 711.6 -71.7 -11.2Sep-11 2532 11.65 6.275 885.1 476.7 408.4 46.1Oct-11 2120 9.83 7.720 625.1 491.0 134.2 21.5Nov-11 1896 9.97 6.365 567.2 362.1 205.1 36.2Dec-11 1961 11.80 9.045 717.3 549.8 167.5 23.32011 9551.0 6866.2 2684.8 28.1

To date 13391.8 9558.2 3833.6 28.6* partial month Table 4. Mean monthly concentrations of total phosphorus in the wastewater effluent and wetland’s outfall (mg/l), total monthly total phosphorus volumes (kg) entering and leaving the wetland, the volume of total phosphorus retained (kg) and the mean retention rate (%).

Month Eff flow TP (kg)CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET.

Jun-10* 1728 4.36 1.49 67.7 23.2 44.5 65.7Jul-10 1692 1.49 0.81 78.3 42.6 35.7 45.6


Jan-11 1222 2.205 2.030 80.8 74.4 6.4 7.9Feb-11 1319 2.225 1.865 82.2 68.9 13.3 16.2Mar-11 2707 1.168 0.701 98.0 58.8 39.1 39.9Apr-11 2824 1.088 0.700 92.2 59.3 32.9 35.7May-11 2816 1.645 1.160 143.6 101.3 42.3 29.5Jun-11 2495 3.092 2.402 231.4 179.7 51.6 22.3Jul-11 1862 2.807 2.870 162.1 165.7 -3.6 -2.2

Aug-11 1859 3.700 4.125 213.2 237.7 -24.5 -11.5Sep-11 2532 1.419 1.308 107.8 99.3 8.5 7.8Oct-11 2120 4.400 3.950 279.8 251.2 28.6 10.2Nov-11 1896 1.480 0.681 84.2 38.8 45.4 54.0Dec-11 1961 0.996 0.818 60.6 49.7 10.9 17.92011 1635.8 1384.8 251.0 15.3

To date 2333.2 1829.9 503.3 21.6* partial month

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CONCLUSION The bathymetry of the wetland (see Figure 1) implies that much of the wetland is considerably deeper than that recommended for maximum nutrient removal; shallower systems allow for the colonization of suitable plants, preferably emergents (Kadlec and Wallace 2009). Also, work by Robb (2012), considering nutrient concentrations across the standing water and by using fluorescent tracers, indicate that the most suitable portion of the system regarding depth (the southeast arm) is ineffective since it is not in the flow path of the effluent. Efforts to decrease the mean depth, and to modify the flow path to better utilize the system in its entirety, could enhance the growth of desirable plants and improve the rate of nutrient retention by the system.

REFERENCES

ACE. 2001. Upper Susquehanna River Watershed-Cooperstown Area Ecosystem Restoration Feasibilty Study and Integrated Environmental Assessment. Project management Plan. United States Army Corps of Engineers, Planning Division. Baltimore, MD.

Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and

total phosphorus in water using peroxodisulfate oxidation. Water Res.7 (12):1721-1726. Fickbohm, S.S. 2005. Upper Susquehanna River Watershed- Cooperstown Area

Ecosystem Restoration Feasibility Study And Integrated Environmental Assessment: Post-restoration water quality and wildlife analysis of the FABADS sites (2003-2004). In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Gazzetti, E. 2012. Efficacy of emergent plants as a means of phosphorus removal in a treatment

wetland, Cooperstown, New York. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Jackson, M.H. 2009. Wastewater treatment facility modifications engineering report.

Lamont Engineers, Cobleskill, NY. Kadlec, R.H and S.D. Wallace. 2009. Treatment wetlands (second ed.). CRC Press, Boca

Raton. Liao, N. 2001. Determination of ammonia by flow injection analysis. QuikChem ®

Method 10-107-06-1-J. Lachat Instruments, Loveland, CO.

Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem ® Method 10-115-01-1-F. Lachat Instruments, Loveland, CO.

Olsen, B. 2011. Phosphorus content in reed canary grass (Phalaris arundinacea) in a

treatment wetland, Cooperstown, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow

injection analysis. QuikChem ® Method 10-107-04-1-C. Lachat Instruments, Loveland, CO. Robb, T. 2012. Insight into a complex system: Cooperstown wastewater treatment

wetland, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Efficacy of emergent plants as a means of phosphorus removal in a treatment wetland, Cooperstown, New York

E. Gazzetti1

INTRODUCTION

In 2003, a wetland was restored along the outskirts of the village of Cooperstown, NY. Designed as a wildlife habitat, but built with the intention of polishing wastewater from the Cooperstown Wastewater Treatment Facility, effluent was first pumped into the wetland in June 2010. Initial studies suggest that the wetland retained about 35% of the effluent’s phosphorus and nitrogen over the course of its first year of operation (Albright and Waterfield 2011). The purpose of this study is to evaluate and compare the phosphorus content in plant tissue between this treatment wetland and a nearby control wetland.

As water bodies become enriched with nutrients, excess phosphorus can act as a pollutant (National Research Council 1996). Wetlands have the natural ability to remove pollutants from wastewater. Constructed wetlands, used to polish wastewater, have been in operation since the 1950s (Kadlec and Wallace 2009). Many wetland plants strip nutrients, such as phosphorus, from effluent and use them for growth. Biotic uptake accounts for short-term removal of phosphorus from wastewater, while sorption onto soil particles and accretion of wetland soils account for long-term removal (Cronk and Fennessey 2001). The amount of phosphorus a wetland can retain depends a great deal upon the types of vegetation within it. Vegetation in a nutrient-enriched wetland, such as this treatment wetland, has the potential to incorporate more nutrients than the same vegetation would in a natural wetland (Guntenspergen et. al. 1989). This luxuriant uptake causes plants to store more phosphorus in their tissue than is needed for growth (Kadlec and Wallace 2009), allowing them to act as a phosphorus sink.

North America has a rich history of constructing large-scale free water surface treatment wetlands over the last 20 years (Kadlec and Wallace 2009). These wetlands have areas of open water and emulate natural wetlands; however, they are usually engineered to effectively reduce nutrients in wastewater. The treatment wetland in Cooperstown was designed for wildlife habitat rather than for wastewater treatment. As such, it is substantially deeper than those designed for treatment (California Stormwater Quality Association 2003) and the flow regime was not designed to maximize effluent contact with plants. Also, specific plants were not implemented to maximize phosphorus removal from the effluent. The Cooperstown treatment wetland contains many naturally occurring species of plants, including reed canary grass (Phalaris arundinacea) and cattails (Typha spp.). These emergent species are widespread, able to tolerate a range of conditions, and have been shown to be effective in wastewater treatment wetlands (Guntenspergen et. al. 1989).

In the summer of 2010, Olsen (2011) investigated the phosphorus content in reed canary grass leaves within the Cooperstown treatment wetland and at an adjacent site which was not

1 Biological Field Station intern, summer 2011, supported by CRISP. Present affiliation: SUNY Oneonta. Funding provided by the Otsego County Conservation Association.

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influenced by effluent. Her studies suggest a higher percentage of phosphorus in leaves taken from plants in the treatment wetland than in the adjacent site. The research done in this study expands on her work by adding more sample sites, investigating cattails as well as reed canary grass, and by comparing these data to a nearby control wetland which was constructed at the same time as the treatment wetland and does not have effluent being pumped into it.

METHODS

Plant sampling:

Reed canary grass and cattails were chosen for this experiment for several reasons. Both species are abundant at each wetland, allowing for multiple sampling sites. Also, they both reportedly possess the ability to polish wastewater relatively well (Cronk and Fennessey 2001). As displayed in Figure 1, six primary sample sites were chosen at both the treatment wetland (TW) (Figure 1A) and control wetland (CW) (Figure 1B). The primary sites were each 3 m2 and were spread out along the outer edge of the wetlands. Within each primary site, sub-sampling was performed by partitioning the 3 m2 site into thirds, creating a total of 18 sub-samples for each wetland. Within each sub-sample, reed canary grass plants were sampled in triplicate and cattail plants were sampled in duplicate. Plants were collected in their entirety, being cut at their stem (1-2 cm from the ground) and placed into a labeled paper bag. These bags were then loaded into a forced air convection oven and allowed to dry overnight at 105° C. Each sample was then finely ground to a homogenous mixture using a Krupps coffee bean grinder and placed in an 8oz. museum jar for storage and future analysis.

B

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A

Figure 1. A: Sample sites at the treatment wetlandrepresented by stars. The general flow pattern of e2012). Effluent enters the wetland near TW1. The at the control wetland (CW).

(TW). Points of inflow and outflow are ffluent is represented by black arrows (Robb, outfall structure is near TW5. B: Sample sites

Sample Analysis:

Methods for dry ashing, acid extraction and phosphorus concentration determination were taken from Bickelhaupt and White (1982). About 0.5 g of sample was used for analysis. The dry weight was recorded and used to later calculate the percentage of phosphorus in each sample (Bickelhaupt and White 1982). Samples were dry ashed at 475° C for 4 hours in dried, tared crucibles. The weight of the sample subsequent to dry ashing was recorded and used to calculate carbon lost on ignition. 6N HCl was added to the dry ashed samples and they were boiled gently until dried. This was repeated twice more. Ten ml of 6N HCl was added and the ash was scraped onto 110mm diameter Whatman® 42 filters which had been folded into 66mm polypropylene funnels. Filters were rinsed and the samples diluted to 100 mL with deionized water. The vanadomolybdophosphoric acid colorimetric method (Bickelhaupt and White 1982) was used to determine the phosphorus content of each acid extraction. The absorbency of each sample was determined through the usage of a Milton Roy Spectronic spectrophotometer 501 at 440 nm wavelength. The concentration vs. absorbency relationship of standard solutions of known concentration was used to find the phosphorus content of each sample. An equation from Bickelhaupt and White (1982), as seen in below, was employed to express phosphorus in the plant tissue as a percentage of the tissue dry weight.

% P in sample =

Paired t-tests were used to evaluate and compare the phosphorus content between the tissue of plants collected in the treatment and the control wetlands.

RESULTS AND DISCUSION

A comparison of the overall mean phosphorus content of plant tissue of both cattails and reed canary grass at each site is provided in Figure 2. There was no significant difference between percent phosphorus concentration in the plant tissue from the treatment and the control wetland for either species.

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Reed Canary Grass

Figure 2. Average phosphorus concentration of plant tissue in cattails and reed canary grass at both wetlands. Error bars represent standard error.

The general flow pattern of effluent through the treatment wetland can be seen in Figure 1 (Robb 2012). This was determined, in part, by the observed pattern of nutrient concentrations across the wetland. This suggests that spatial distribution of the nutrients across that wetland may be reflected in plant tissue content. Coinciding with nutrient data collected from the treatment wetland (Figure 3), the percent phosphorus concentration in reed canary grass was highest at the site nearest the point at which the effluent entered the wetland (TW1), it trended downward to the site nearest the outfall (TW5), and it was lowest at the site out of the flow path (TW6). Cattail did not display a similar pattern. In the control wetland (Figure 4), phosphorus concentrations were somewhat less variable than they were in the treatment wetland. All data, including the phosphorus content of plant tissue and the percent carbon lost on ignition, for both cattail and reed canary grass at both the treatment and control wetlands, are summarized in Table1.

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Cattail Reed Canary Grass

Figure 3. The average phosphorus concentration of plant tissue in sample sites 1-6 at the treatment wetland. Error bars represent standard error. See Figure 1 for site locations.

Figure 4. The average phosphorus concentration of plant tissue in sample sites 1-6 at the control wetland. Error bars represent standard error. See Figure 1 for site locations.

Cattail Reed Canary Grass

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Cattails Reed canary grass

Control Wetland Treatment Wetland

Control Wetland Treatment Wetland

Site % P of Dry

Weight

C Loss on

Ignition (%)

% P of Dry

Weight

C Loss on

Ignition (%)

% P of Dry

Weight

C Loss on

Ignition (%)

% P of Dry

Weight

C Loss on

Ignition (%)

1a .184 93.3 .338 89.7 .194 96.6 .407 92.6

1b .190 93.2 .310 87.2 .208 96.5 .481 91.3

1c .204 92.9 .296 89.2 .248 95.7 .590 90.8

2a .253 92.0 .205 92.5 .274 95.1 .415 90.2

2b .204 93.1 .191 89.7 .275 94.7 .373 91.4

2c .274 91.8 .275 89.7 .301 94.1 .296 92.5

3a .351 92.4 .271 89.9 .248 94.8 .171 92.1

3b .301 91.4 .263 89.6 .291 95.2 .196 92.5

3c .320 92.6 .317 89.2 .233 95.5 .232 93.3

4a .292 92.0 .248 97.3 .217 96.3 .227 91.6

4b .283 91.6 .339 88.1 .230 96.5 .296 94.0

4c .346 92.1 .409 89.4 .219 96.5 .259 92.9

5a .258 91.8 .328 88.9 .253 96.4 .239 93.2

5b .326 90.8 .255 89.2 .241 96.0 .252 92.9

5c .324 91.4 .285 87.7 .322 95.4 .206 93.8

6a .326 93.3 .182 92.2 .247 96.6 .123 94.0

6b .295 94.6 .201 91.4 .203 96.5 .214 94.6

6c .316 93.4 .249 91.6 .186 96.9 .228 93.0

Table 1. The phosphorus concentration of plant tissue of cattail and reed canary grass at each sub-sample site of the treatment and control wetland (as percent of dry weight. The carbon loss on ignition is the organic mass lost during dry ashing.

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DISCUSSION

A t-test determined there was no significant difference in phosphorus concentrations of plants between the treatment and control wetlands; however, in the treatment wetland there seemed to be a pattern between ambient phosphorus levels in the effluent across the wetland (Robb 2012) and reed canary grass phosphorus concentrations. Percent phosphorus concentrations for plants in the control wetland range from 0.184 to 0.351%. This compares well with a study done by McJannet & Keddy (1995), which analyzed 41 wetland plant species and suggested that phosphorus concentrations can range from 0.20 to 0.40%. In the treatment wetland, there was a wider spectrum of phosphorus concentrations, ranging from 0.123 to 0.590%. These values coincide with Kadlec and Knight’s (1996) reported values of 0.08 to 0.63% phosphorus concentrations for plants in constructed wetlands.

REFERENCES

Albright, M.F. and Waterfield, H.A. 2011. Monitoring the effectiveness of the Cooperstown wastewater treatment wetland. In 43rd Ann. Rept. (2010). SUNY Oneonta Biological Field Station, SUNY Oneonta.

Bickelhaupt, D.H. and E.H. White. 1982. Laboratory Manual for Soil and Plant Tissue Analysis. State University of New York, Environmental Science and Forestry.

California Stormwater Quality Association. Constructed Wetlands, Cabmphandbooks.com. 2003. http://www.cabmphandbooks.com/Documents/Development/TC-21.pdf.

Cronk, J.K. and M.S. Fennessey. 2001. Wetland Plants, Biology and Ecology. Lewis Publishers. Boca Raton, London, New York, Washington, D.C.

Guntenspergen, G.R., Stearns, F. and J.A. Kadlec. 1989. Wetland vegetation. In Constructed Wetlands for Wastewater Treatment. D.A. Hammer, Ed. 73-88. Lewis Publishers. Chelsea, Michigan.

Jaisingh, L.R. 2000. Statistics for the Utterly Confused. McGraw-Hill. New York.

Kadlec R.H. and R.L. Knight. 1996. Treatment Wetlands. Lewis Publishers. Boca Raton, Florida.

Kadlec, R.H. and S.D. Wallace. 2009. Treatment Wetlands, 2nd Ed. Taylor and Francis Group. Boca Raton, Florida.

McJannet, C.L., P.A. Keddy, F.R. Pick. 1995. Nitrogen and phosphorus tissue concentrations in 41 wetland plants: a comparison across habitats and functional groups. Functional Ecology 9: 231-238

National Research Council (U.S.). Committee on Inland Aquatic Ecosystems. 1996. National Academy Press. Washington, D.C.

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http://www.cabmphandbooks.com/Documents/Development/TC-21.pdf

Olsen, B. 2011. Phosphorus content in reed canary grass (Phalaris arundinacea) in a treatment wetland, Cooperstown, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biological Field Station, SUNY Oneonta.

Robb, T. 2012. An Insight into a Complex System: Cooperstown Wastewater Treatment Wetland, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biological Field Station, SUNY Oneonta.

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Insight into a complex system: Cooperstown wastewater treatment wetland, 2011

T. Robb1

Overview The wastewater treatment wetland just south of Cooperstown, New York has been

operational for just over a year at the onset of this study. Beginning in June 2010, effluent from the Cooperstown Wastewater Treatment Plant was diverted to the wetland for additional treatment prior to its discharge into the Upper Susquehanna River (Albright and Waterfield 2010). In the summer of 2010, Olsen (2011) delineated and described the wetland in detail, including reasons for diversion of effluent and anticipated effects of pumping effluent through the system. This 2011 study attempts to characterize some of the effects of the processes occurring within the wetland. The components discussed within this paper are separated into four main topics; brightener survey, detention time (including bathymetric survey), dissolved oxygen survey, and nutrient survey. These topics will be discussed separately for clarity.

Current insights into physical processes within the treatment wetland are based largely on

visual observations and an understanding of the basic flow regime (Figure 1). There is a small intermittent stream with very low flow that enters the wetland on the western side. Just to the east of the stream mouth is a large area of overland flow that radiates from the inflow. This overland flow enters the open-water portion of the wetland at three separate channelized flow points, shown with arrows in Figure 1. The shaded area represents the area of overland flow between the point where the effluent is introduced and the wetland surface. Water level and outflow from the wetland are controlled by a weir located in a stand-pipe in the southeast corner of the wetland; flow enters a submerged drain pipe off-shore, flows over the weir, and is directed to a rip-rap channel for discharge to the Susquehanna River. This study will address characteristics of the open-water portion of the wetland.

Background One portion of this study investigated concentrations of optical brighteners throughout

the wetland and the Susquehanna River up- and down-stream of the wetland’s outflow. Optical brighteners are used in a variety of personal care and cleaning products including shampoo, cosmetics, cleaning agents and detergents. The result is an abundance of these compounds in wastewater effluent. Optical brighteners or fluorescent whitening agents are compounds that are excited (activated) by wavelengths of light in the near-ultraviolet range (360 to 365 nm) and then emit light in the blue range (400 to 440 nm) (Hagedorn et al. 2005). The chemical families that include the brightening formulations that are most widely used by the detergent industry are the carbocycles (mainly the distyrylbiphenyls) and the triazinylaminostilbenes (Ullmans Encyclopedia of Industrial Chemistry 2001). At the molecular level brighteners are fairly unstable and break down when exposed to sunlight. It is claimed that a reduction of more than

1 Biological Field Station intern, summer 2011. Current affiliation: Penn State University. Support provided by the Village of Cooperstown.

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50% occurs over six months ( Hagedorn et al. 2005), however, there have been conflicting studies on this subject. According to Kramer et al. 1996, optical brighteners have displayed photo-decay in a matter of hours when exposed to UV light. In the context of the wastewater treatment wetland, optical brightener concentrations were used as a tracer for effluent, anticipating that higher levels of optical brighteners may correspond to preferred effluent flow paths.

Figure 1. An areal depiction of the wetland and surrounding area showing a small intermittent stream that enters the wetland on the western side. Just to the east of this streams mouth there is a large section of overland flow that radiates from the inflow. Water enters the wetland in three separate channelized flow points, shown with arrows. The checkered area represents a muddy section of the wetland. The drain for the system and the outflow are located in the Southeastern corner represented with circles.

Humic substances, also referred to as tannins, are a complex mixture of organic materials

released from decaying plant matter and soils (Dixon et al. 2005). Humic compounds also have a characteristic fluorescence signature, fluorescing in the entire range between 440nm and 550nm (Dixon et al. 2005). This places them close to the same range as optical brighteners and may lead to some error when interpreting results. Therefore, the levels in the lake were considered as natural background levels.

Detention time was estimated based on flow and wetland volume in order to determine

the amount of time the average molecule of effluent will reside in the wetland. This value

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therefore gives an idea of the effectiveness of the wetland (Kadlec and Wallace, 2009). Both minimum and maximum estimates of detention time were calculated by manipulating the volume variables in the detention time equation based on a perceived difference between active flow volume and total wetland volume. Estimation of detention time is further complicated by the addition of precipitation to the catchment area. This variable adds flow to the system shortening detention time. Due to this combination of variables affecting detention time four calculations will be made. The actual detention time is projected to be between the resulting values.

Another portion of this study was to gain an understanding of the dissolved oxygen

concentrations and diurnal variations occurring within the waste water treatment wetland. Dissolved oxygen (DO) is of interest in treatment wetlands for two principal reasons: it is an important participant in some pollutant removal mechanisms, and it is a regulatory parameter for discharge to surface waters (Kadlec and Wallace 2009). For these reasons several diurnal cycles of DO have been recorded across the surface of the wetland and at depth. The DO is the driver for nitrification and aerobic decomposition; also it is critical for the survival for aquatic organisms in receiving water bodies (Kadlec and Wallace 2009). The amount of DO present in water results from photosynthetic and respiratory activities of aquatic biota and from diffusion at the air-water interface (Odum 1956). The many factors contributing to DO complicate analysis of observed levels and may warrant further study to fully understand the implications of the data recorded.

The primary purpose of the wastewater treatment wetland is to sequester nutrients prior

to the discharge of treated effluent to the upper Susquehanna River. To assess the effectiveness of the wetland, 20 grab samples were taken throughout the system. These samples were analyzed to determine the concentrations of total phosphorous, total nitrogen, ammonia, and nitrate+ nitrite.

METHODS

a. Brightener survey Surveys of Otsego Lake, upper Susquehanna River, and the wastewater treatment

wetland were conducted on 19 July 2011. Data were collected to determine background levels, concentrations within the wetland itself, and impacted concentrations within the stream to which the wastewater treatment wetland empties. Measurements were made at many points throughout the wetland; the same locations were used for the development of bathymetry used in detention time calculations (Figure 2). The Upper Susquehanna was surveyed several hundred meters above and below the outflow of the wastewater treatment wetland to determine the concentration of brighteners in the river.

Brightener concentrations were measured using a CYCLOPS-7® fluorometer

manufactured by Turner Designs. This instrument measures relative concentrations of optical brighteners using fluorescence, or emission of light. This device was calibrated to zero using ultra pure de-ionized water in the lab and was evaluated using several concentrations of commercially available detergent advertised as having optical brighteners, to determine efficiency in detection. This device gives concentrations in relative brightener units or RBUs, a value representative and proportional to the amount of brighteners in the water.

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Waste water treatment wetland- Relative Locations of Brightener and Bathometric Data Points

Figure 2. A representation of the relative locations of data points collected to assess brightener concentration and bathymetry. Triangles represent the shoreline, squares represent the shoreline of the island, and diamonds indicate points of data collection.

b. Detention Time There are two variables associated with detention: volume and flow. The volumes used to

calculate retention time were the result of intensive mapping at the wastewater treatment wetland. Materials included a row boat, inflatable raft, meter stick, Speed Tech® depth finder, Garmin Rino® GPS, and Global Mapper® GIS software. There were many data points collected throughout the wetland in three separate excursions; these locations have been displayed using Excel® using an arbitrary origin (Figure 2). The water level on banks was defined as zero and all the information was plotted as x, y, z point data in Global Mapper®. Global Mapper® was also used to generate contours, calculate volumes, and display bathymetry (Figure 3).

The data collected during the brightener survey implies that a portion of the wetland’s

volume is not involved in active flow, as indicated by lower brightener readings. Considering that there may be “inactive” areas within the wetland, two estimates of volume in the wetland should be calculated in relation to detention time; total and active flow (Figure 4).

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Figure 3. A bathymetric map of the wastewater treatment wetland. Contours in 0.1 m intervals. Figure 4. Areas used to calculate the total volume (left) and active flow volume (right) are indicated by horizontal line striping. Background shading indicates bathymetry, contours show brightener concentrations in 25 unit increments.

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The second variable associated with detention time is the flow; this can be accounted for at times with precipitation as well as during dry times. The outflow has been recorded at a standard 90o weir constructed at the outflow of the wetland (Albright and Waterfield 2011). A Reconyx Hyperfire® HC 600 Trail Camera has been used for observing weir measurement values every 15 minutes. Visual observation of the weir allowed for calibration of a Logger Pro Depth® sensor provided a means by which to recognize periods of obstructed flow (due to animal interference). The depth sensor readings were found to be inaccurate, so visual gauge readings were used to determine outflow for this study. Animals, including muskrats and beaver, freqently plugged both the outlet pipe and the weir, preventing accurate outflow estimates. Debris blockages artificially raised the water level in the outflow weir structure and created inconsistent flow patterns int eh pipe; these blockages introduced error to the estimation of water volume outflow at a given point in time. Over the course of the study almost 5000 data points were recorded to document the outflow of the system.

The following equation, taken from Kadlec and Wallace (2009), has been modified to

account for different variations of detention time: total volume and active volume, under dry and wet conditions.

In Global Mapper software, the

total volume and active flow volume, wrespectively. Figure 4 depicts the areas findicates bathymetry (bottom depth) whbrighteners. The dry outflow rate (Tabletreatment wetland during periods withourecent rain event. The wet outflow rate (received notable precipitation.

Table 1. Volume and outflow rates used

Total volume (m3), (figure 4 ) Active volume (m3), (figure 4)

Dry outflow rate (m3/day) Wet outflow rate (m3/day)

V=Qi=

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II. III.

IV. Results

Equation 1: detention time τn = detention time, days

volume of water in cubic meters. Daily average out-flow, cubic meters/ day.

bathymetric profile was used to calculate estimates of hich were estimated to be 4564 m3 and 3357 m3 (Table 1) or which volumetric calculations were made. Shading ile contour lines illustrate the concentrations of optical 1) is an average of daily outflows from the wastewater t precipitation occurring at least one day after the most Table 1) refers to an average outflow of days that

to calculated the various estimates of detention time.

4564.18 3357.14 2311.4 2503.7

c. Dissolved Oxygen survey Before the initiation of this study, ten Eureka Midge® dissolved oxygen loggers were

rigorously calibrated and tested five times for competence, resulting in seven seemingly accurate and functional probes. The eight units that seemed most reliable were selected for use, though one, Midge® E, performed marginally; it displayed repeatedly that it was functional at recording changes in magnitude similar to the other probes, however these changes were at different concentrations.

On 14 July 2011 the eight Midges® were placed across the wetland at 14:15 in the afternoon (Figure 5). The Midges® were deployed to record data for several days in order to observe the dynamics of dissolved oxygen conditions over a continuous period of time. This time period was selected in order to limit variables influencing DO in that there was no rain for several days previous, limiting the amount of atmospheric mixing. The midges that were designated surface monitors were placed suspended from floats approximately .08 meters from the surface of the wetland. The units that were designated deep monitors were also suspended from floats but were placed approximately .08 meters from the bottom of the wetland. All of the units were programmed to sample temperature and DO at the same fifteen minute intervals throughout the day.

Figure 5. A map showing the sample locations for the dissolved oxygen probes placed around the wetland, both at the surface and at depth at two locations.

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d. Nutrient survey Twenty locations were identified to characterize the spatial distribution of nutrient concentrations through the wetland (Figure 6). These points represent six transects perpendicular to perceived flow and one end point in the shallows, G1. Grab samples were taken from the surface and at depth using a VanDorn water sampler on 12 June at 14:00, preserved and stored in 125 ml containers. Samples were analyzed for Ammonia, nitrate +nitrite, total phosphorous, and total nitrogen according to automated methods using a Lachat QuikChem FIA+ Water Analyzer. Concentration data were plotted in Global Mapper at the location in which it was collected. Concentration data points are displayed with proportional symbols.

F

D

E

A B

C

G

Figure 6. A map depicting the data points and point IDs used in the nutrient analysis of the wetland.

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RESULTS

Brightener survey A survey of optical brighteners in Otsego Lake indicates that average levels are around18

RBUs, with slightly higher concentrations (24 RBUs) in close proximity to populated areas. Brightener concentrations in the Susquehanna River downstream of the Village of Cooperstown are elevated to 50 RBUs. Effluent leaving the wastewater treatment plant contains about 350 RBUs, while concentrations in the treatment wetland’s outflow range from 300 to 350 RBUs. 150 meters downstream in the river, after adequate mixing, optical brightener concentration decreases to 70 RBUs. Figure 7 displays brightener concentrations across the wastewater treatment wetlands. Contours of 25 RBUs have been generated via interpolation using Global Mapper; “m” represents the relative measurement.

Figure 7. A graphic display of brightener concentrations across the wastewater treatment wetland. Contours of 25 RBUs have been generated via interpolation using Global Mapper®; “m” represents the relative measurement.

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Detention Time Estimates of detention time range from 1.2 to 2 days (Table 2). The minimum detention time

was calculated for the estimate of active flow volume under rainy conditions. The maximum detention time (2 days) was estimated for the total volume of the wetland during dry conditions. See Figure 4 for the delineation of total volume vs. active flow volume.

Table 2. A summary of results for detention time, comparing total and active flow and wet compared with dry conditions. The values were derived from equation 1 combined with Table 1.

Total volume

detention time (days) Active volume

detention time (days) Wet detention time (days) 1.6 1.2

Dry detention time (days) 2.0 1.5

Dissolved Oxygen (DO) survey

Dissolved oxygen concentrations recorded by the deployed Midges are displayed in Figure 8. As noted earlier, the absolute concentrations presented are suspect, as problems were encountered when attempting to calibrate the probes. However, the relative differences between the readings may provide some insight into the daily fluctuations in concentration. The majority of the sample sites (A, E, F, and J) represented classic diurnal cycling, with lower values at night and higher values during the day. Kadlec and Wallace (2009) state that photosynthetic and respiration cycles are the cause of such variations. Sample sites B and D showed signs of diurnal cycling, though the peak times are offset from the norm, in that they were elevated at night. Midges H and I are the probes that were monitoring the deepest portions of the wetland (~2 m deep). Waters there were essentially anoxic. Midge E has recorded classic diurnal cycling, though recorded concentrations were substantially elevated in comparison to the rest of the Midges in the wetland.

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Wastewater Treatment Wetland DO Over Time

Calendar Decimal Days

Figure 8. Wastewater treatment wetland dissolved oxygen concentrations over two days of samples recorded by eight probes every 15 min. The positions of these probes throughout the wetland are depicted in Figure 5.

The amplitudes of the two day DO diurnal cycle are represented in Table 3. Midges H and I positioned on the bottom of the wetland show very little variation in oxygen, whereas Midge D displayed the largest variation over the course of the sample period.

Table 3. The values represented in this table account for the amplitude of change that the midges recorded over a two day period in the waste water treatment wetland.

Midge DO (mg/L)A 3.2B 4.26D 12.5E 7.34F 2.38H 0.3I 0.31J 2.58

Amplitude of Diurnal Cycle

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Nutrient survey

Total phosphorous In general phosphorus concentrations decreased from the effluent inflow to the wetland outflow, excepting the area near the outflow, which had high TP concentrations. The lowest concentrations of phosphorous are found along transect F and at point G, in areas which were thought to be outside of the wetland’s active flow path. Phosphorus concentrations in mg/L are depicted in Figure 9, with the symbol size being proportional to concentration values.

F

G

A B

C

D

E

Figure 9. Total phosphorous concentrations (mg/L) in the wastewater treatment wetland. Symbol size is proportional to the TP concentration at each sampling location. Total nitrogen Figure 10 depicts concentrations in mg/L numerically as well as with symbols proportional in size to the nitrogen concentrations. Total nitrogen appears to initially increase as effluent enters the wetland. The concentrations decrease slightly along transect D and then rise again along E, near the drain pipe. Transect F and point G exhibited lower concentrations, again, outside of the active flow path. The highest concentrations were found along transect E, near the drain pipe.

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G

A B

D

C

F

E

Figure 10. Total nitrogen (mg/L) concentrations in the treatment wetland. Symbols are sized proportionally to the N concentration, which is also given numerically, for each sampling location. Nitrate + nitrite In Figure 11, concentrations of nitrate + nitrite are shown in mg/L with stars sized proportionally to the concentrations determined for each sample site. These concentrations display similar patterns to those of ammonia (see below), with concentrations initially increasing and then decreasing as the effluent moves through the wetland. The highest concentrations in the wetland were found along transect C. The lowest concentration values were again found to be along transect F and at point G.

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G

A B

C

D

E

F

Figure 11. Nitrate+nitrite (mg/L) concentrations in the treatment wetland. Symbols are sized proportionally to the nitrate concentration, which is also given numerically, for each sampling location. Ammonia The concentrations of ammonia initially increased from transects A through C and then dropped off considerably by transect E. Figure 12 shows concentrations of ammonia in mg/L with circles proportionally sized to concentrations at collection points. The highest values were observed along transect C and the lowest were found at point G.

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E

F

C

D

A

B

G

Figure 12. Ammonia (mg/L) concentrations in the treatment wetland. Symbols are sized proportionally to the ammonia concentration, which is also given numerically, for each sampling location.

Nutrient concentrations were also measured at depth and appeared to be similar to those concentrations measured at the surface locations, with the exception to this being ammonia, for which the highest levels were recorded in the deepest portions of the wetland along transect D. Higher ammonia levels would be expected in this reducing, anoxic environment. Average surface and at-depth nutrient concentrations are displayed in Table 4.

Table 4. Average nutrient concentrations for surface and at-depth samples collected throughout the wetland.

ammonia

(mg/L) nitrate+nitrite

(mg/L) total nitrogen

(mg/L) total phosphorus

(mg/L) Surface average 0.85 6.33 7.58 1.33 Depth average 1.84 6.06 7.64 1.72

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DISCUSSION

Brightener survey

Higher concentrations of optical brighteners in close proximity to populated areas along Otsego Lake are perceived as being the result of humic and fabric materials leeching fluorescent compounds into the water. Dynamics within the Susquehanna River are interesting and should be investigated further.

The observed concentrations of optical brighteners in the wastewater treatment wetland

indicate what is assumed to be the preferred pathway for effluent flow. The higher concentrations approximately follow the shortest pathway from the inflow to the outflow. These concentrations helped to determine the location of the drain pipe and imply that only a portion of the wetland is involved in active flow, as effluent is taking the shortest pathway from in flow to outflow. This likely results in reduced effectiveness of the wetland as a tertiary treatment for wastewater effluent, though it seems there is potential for further treatment if the entire wetland was utilized.

Other research has indicated that no optical brighteners should be produced by waste

water treatment plants using disinfection procedures such as chlorination and UV light (Tavares 2008). However slightly higher levels of RBUs after UV filtration have been observed during the course of this study. This is believed to be caused by the excitement of the brightener compounds, due to their absorption of UV radiation, leading to heightened level detection by the fluorometer.

Detention Time

Concentrations of brighteners and nutrients indicate a preferential flow path through the

wetland; this shortened flow path reduces the area of the wetland that contributes to effluent treatment. The bathymetric survey revealed that the treatment wetland is considerably deeper than recommended by Kadlec and Wallace (2009); this text indicates that a treatment wetland should be designed to accommodate and foster plant growth at all depths. The treatment wetland has an average depth of 0.7 meters (2.3 feet) which may encourage a large amount of plant growth due to the availability of sunlight. However, the maximum depth is 2.4 meters (almost 8 feet). Most of the wetland’s open-water area appears to lack rooted plants. The detention time is greatly increased by the depth of the wetland, though this may not be as important as encouraging plant growth throughout the system. It seems likely that the wetland would greatly benefit from shallower depths.

Dissolved Oxygen survey

Oxygen is released into the water as the result of photosynthetic primary production

during the day, and is taken up throughout both the night and the day by autotrophic and heterotrophic organisms and by chemical oxidation (Cronk et al. 2001). These factors directly impact the productivity of the wetland and its ability to mitigate effluent. The DO concentrations and daily fluctuations overall are fairly low. DO concentrations may be reduced due to the thick

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coverage of Lemna (duckweed) isolating the wetland from atmospheric deposition of oxygen. The suppression of the diurnal DO cycle is characteristic of all wetlands receiving moderate to high loads of nutrients (Kadlec and Wallace 2009). The extremely low values persistent at the bottom of the wetland indicate persistent stratification. This stratification indicates that there is little vertical mixing throughout the wetland. Case studies indicate that there are several approaches to mitigate these effects including aeration with compressed air bubbles and controlled intermittent vertical flow.

Nutrient survey

Overall it appears that the treatment wetland is indeed retaining nutrients. Ammonia as

well as nitrate and nitrite concentration values increased initially and then decreased as the flow progresses through the wetland. Total nitrogen and total phosphorous show similar trends initially but indicate elevated levels near the drain pipe. In all cases the lowest concentrations were found to be at point G. This section of the wetland is positioned after the projected flow has passed the drain pipe and outside of the preferential flow path indicated by the brightener survey. These results indicate that perhaps the whole wetland is not being utilized to sequester nutrients.

CONCLUSION

The data presented here provide insight into the processes that occur within this treatment wetland. Several unexpected things were found that may warrant further research. The dissolved oxygen readings were considerably different than what was be expected (though some problems existed with the probes used). Also the total nitrogen and total phosphorous concentrations are elevated near the drain pipe. There may be several explanations for this phenomena, further research is required to formulate adequate conclusions. The nutrient data, as well as the brightener survey, indicate that only portions of the wetland are acting as nutrient sinks (that is, there are some preferential flow paths through the system). The active flow volume calculated implies that about 1,200 m3 of the wetland (25% of its volume) receives less flow than the rest of the system.

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REFERENCES

Albright, M. F., and H. A. Waterfield. 2011. Monitoring the effectiveness of the Cooperstown wastewater treatment wetland. In 43rd Ann. Rep. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cronk, J. K., and M. S. Fennessy. 2001.Wetland plants: Biology and ecology. CRC Press.

Boca Raton, FL.

Dixon, L. K., H.M. Taylor, E. Staugler and J. Scudera. 2005. Development of a fluorescence method to detect optical brightener in the presence of varying concentrations of fluorescent humic substances: identifying regions influenced by OSTDS in the estuarine waters of Charlotte Harbor 1045. Mote Marine Laboratory Technical Report.

Hagedorn, C., M. Saluta, A. Hassal, J. Dickerson. 2005. Fluorometric detection of optical brighteners as an indicator of human sources of water pollution. Part I: Description and detection of optical brighteners. Crop and Soil Environmental News. Online periodical, available at: (http://www.ext.vt.edu/ cgi-bin/webobjects/Docs.woa/wa/getnews?cat=tt-news-cses&issue=200511) (verified 25 October 2007).

Kadlec, R. H. and S. Wallace. 2009. Treatment Wetlands. CRC Press. Boca Raton, FL.

Kramer, J.B., S. Canonica, L. Hoigne, and Kaschig. 1996. Degradation of fluorescent whitening agents in sunlit natural waters. Enviro. Sci. and Tech. 30:2227-2234.

Odum, H. T. 1956. Primary production in flowing waters. Amer. Soc. of Limnol. and Oceanog. 1(2):102-117.

Olsen, B. 2011. Phosphorus content in reed canary grass (Phalaris arundinacea) in a treatment wetland, Cooperstown, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Tavares, M.E., M.I.H. Spivey, M.R. McIver and M.A. Mallin. 2008. Testing for optical

brighteners and fecal bacteria to detect sewage leaks in tidal creeks. Journal of the North Carolina Academy of Science 124:91-97.

Ullmans Encyclopedia of Industrial Chemistry. 2001 Electronic release, 6th Edition. Wiley-VCH Interscience. http://www.wiley-vch.de/contents/ullmann/ull_10518.html

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http://www.wiley-vch.de/contents/ullmann/ull_10518.html

Treatment performance of advanced onsite wastewater treatment systems in the Otsego Lake watershed, 2008-20111

Holly Waterfield2

EXECUTIVE SUMMARY

This report documents the treatment performance of four advanced onsite wastewater treatment systems based on monitoring during the summers of 2008 through 2011. All four systems are installed in the Otsego Lake watershed; three were installed as part of a NYS DEC grant to demonstrate the use of advanced onsite wastewater treatment systems. Three systems have been monitored since 2008 (Waterfield and Kessler 2009, Waterfield 2010, Waterfield 2011); OWTS 1 and OWTS 2, funded by the grant, and the UIC system (serving BFS Upland Interpretive Center). Another system, also funded by the grant, was installed in the spring of 2009 at the BFS Thayer Farm; this system serves three buildings; the Hop House, Boat House, and a rented residence. Many of these enhanced treatment technologies are new to the region, and thus are unfamiliar to industry professionals, regulators, and residents. For this reason, a DEC grant was sought and obtained to fund a demonstration project to install and monitor the treatment performance of six shared advanced treatment systems. The scope of the grant has since been amended, changing the total number of treatment systems to four, with the last installed in early 2011 to serve SUNY Oneonta’s newly renovated Cooperstown Campus, which houses the Biological Field Station and the Cooperstown Graduate Program. The grant did not fund the installation of the system, though the treatment technologies used were chosen by the demonstration project’s coordinators.

Treatment performance was assessed based on the following analyses: biochemical oxygen demand (BOD or CBOD), total suspended solids (TSS), nitrate (NO3), ammonium (NH3), and total phosphorus (TP). Systems were sampled a total of about 31 occasions, though all four systems weren’t necessarily sampled on each collection date. Detailed analysis of each system’s performance is provided in the System Performance, Operation, and Maintenance section of the 2008-2011 report. Overall, treatment systems performed well, but mainly because they were actively managed and serviced by qualified professionals. The systems incorporating textile filters received the most consistent use with the incoming effluent being of typical household strength (higher than the other systems monitored). Outgoing effluent from these units was of the highest quality, achieved the best nitrogen transformation rates, and was the least variable of the systems monitored. The aerobic treatment unit (ATU) serving the UIC produced effluent of consistent quality, though the system saw very low use compared to its designed capacity. It handled typical UIC functions and events (field trips, workshops, etc.) and long periods of low use very well without compromising effluent quality. The foam filter’s treatment was most variable of the four systems and produced effluent of lower quality than the other units. The configuration and dosing regime of this system may play a role in the variability observed throughout this monitoring program.

1 Funding provided by NYSDEC grant #49298. This report served as a final report to the granting body. 2 Research Support Specialist, SUNY Oneonta Biological Field Station.

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In the end, most treatment performance issues were improved by communicating with the trained service provider contracted for each system. As the manufacturer’s recommend, regular maintenance is needed in order for these systems to operate as they are intended and produce high quality effluent. Homeowners should be encouraged (and potentially regulated) to prioritize such maintenance as they would for other major investments (heating systems, vehicles, etc.).

INTRODUCTION

This report serves to document the treatment performance of four advanced onsite wastewater treatment systems monitored during the summers of 2008 through 2011. All four systems are installed in the Otsego Lake watershed; three were installed as part of a NYS DEC grant to demonstrate the use of advanced onsite wastewater treatment systems. Three systems have been monitored since 2008 (Waterfield and Kessler 2009, Waterfield 2010, Waterfield 2011); OWTS 1 and OWTS 2, funded by the grant, and the UIC system (serving BFS Upland Interpretive Center). Another system, also funded by the grant, was installed in the spring of 2009 at the BFS Thayer Farm. This system serves three buildings; the Hop House, Boat House, and a rented residence. Due to operation and maintenance issues, OWTS 2 was not monitored in 2010 or 2011. Treatment performance was assessed based on the following analyses: biochemical oxygen demand (BOD or CBOD), total suspended solids (TSS), nitrate (NO3), ammonium (NH4), and total phosphorus (TP).

Otsego Lake is located in northern Otsego County, New York. According to the historical overview by Harman, et al. (1997), the monitoring of Otsego Lake’s water quality dates back to a 1935 NYS Department of Environmental Conservation (DEC) study. Routine water quality monitoring efforts began subsequent to the establishment of the Biological Field Station (BFS) in 1968 (Harman, et al. 1997). Comparisons to these and other historical datasets had shown overall decreasing water quality conditions, noting in particular increased phosphorous concentrations likely tied to loading from watershed activities (agriculture, road maintenance, onsite wastewater treatment, etc.). Onsite wastewater treatment (septic) systems are estimated to contribute only 7% of the total phosphorus load (Albright 1996), though the combination of the bio-available form and time of greatest loading at the height of the growing season is likely to lead to stimulation of algal production (Harman, et al. 1997). The cascading effects of such nutrient loading on the lake’s ecosystem are far-reaching, and began to concern lake users and the Village of Cooperstown, which uses Otsego Lake as its source of drinking water. In 1985, the Village implemented public Health Law 1100 in order to give them legal grounds to protect the lake as their source of drinking water (Harman, et al. 1997). Additional actions to curb further water quality degradation in the lake culminated in the formation of a watershed management plan in 1998, which identified nutrient loading as the greatest threat to the health of Otsego Lake. Wastewater treatment via onsite treatment systems were listed second on a prioritized list of action areas (Anonymous 1998), and efforts to manage the effectiveness of these treatment systems began with a 2004 inventory of all systems in the established Lake Shore Protection District followed by the inception of the inspection program in 2005 (Anonymous 2007). Under the program, any system found to be in failing condition is to be replaced within one calendar year. Such replacement systems generally make use of advanced or enhanced treatment technologies due to conditions that constrain the use of conventional designs, such as setback to the lake or a tributary, soil depth to bedrock or

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groundwater, percolation rate, etc. Many of these enhanced treatment technologies are new the region, and thus are unfamiliar to industry professionals, regulators, and residents. For this reason, a DEC grant was sought and obtained to fund a demonstration project to install and monitor the treatment performance of six shared advanced treatment systems. The scope of the grant has since been amended, changing the total number of treatment systems to three, with the last installed in December of 2008.

Biochemical oxygen demand (BOD or CBOD) and total suspended solids (TSS) are typical metrics used to characterize the strength of residential wastewater (Crites and Tchobanoglous 1998). BOD is an analysis used to determine the relative oxygen requirements of wastewater, effluents, and polluted waters, by measuring the oxygen utilized during a given incubation period (APHA 1992). It is expected that organic material is broken down as wastewater progresses through a treatment system, thus decreasing the oxygen requirements of highly-treated wastewater and in turn resulting in lower BOD concentrations over the course of the treatment system (APHA 1992). TSS analysis measures the total amount of suspended or dissolved solids in wastewater. Solids may negatively affect water quality for drinking or bathing and potentially clog a drain field. As with BOD, the amount of solids in treated effluent should be lower than that of raw wastewater (APHA 1992).

Nitrate and ammonia concentrations will provide insight into the physio-chemical conditions along the treatment train, as the transformations between various nitrogen forms are dependent on oxygen availability, alkalinity, temperature, and the presence of specific bacterial populations. Nitrogen is a dynamic component of wastewater treatment systems, which are often designed to facilitate specific transformations of nitrogen species. Advanced treatment systems most often incorporate a secondary treatment step that involves aerating the wastewater in order to create favorable conditions for the bacterial transformation of ammonia to nitrate, called nitrification. Nitrogen can be completely removed from the waste stream through the process of denitrification, during which nitrate is converted to nitrogen gas (N2), which is released to the atmosphere. Nitrification is generally considered the most limiting step of this overall nitrogen removal process, as it supplies the nitrate that is converted to N2 gas.

Phosphorus, as previously mentioned, is the nutrient of greatest concern with regards to vulnerable freshwater bodies. The removal of phosphorus from the waste stream prior to subsurface disposal will be of great benefit to lake management efforts should the technologies installed prove to be successful. The nutrient removal units installed in all four systems are of the same, or very similar design, sourced from a single manufacturer. Phosphorus removal occurs via adsorption of P onto active sites of an iron-oxide based reactive media; this design results in the gradual reduction in performance as active adsorption sites on the media surface become occupied. Eventually the adsorption capacity of the media is exhausted and the media must be replaced in order to restore the treatment unit’s ability to effectively reduce the phosphorus concentration leaving the treatment system.

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METHODS AND MATERIALS

Four onsite wastewater treatment systems (OWTS) were monitored in this study and are illustrated and described in Figure 1; these include the systems serving the SUNY Oneonta BFS Thayer Farm Upland Interpretive Center (UIC) and Hop House (HH) and two shared homeowner systems, OWTS 1 and 2. The UIC system has relatively high treatment capacity, as the UIC was built to accommodate large groups for field trips and meetings. However, typical water usage is relatively low due to the short duration of most events (<4 hours); actual flow has not been measured. The system was installed and use commenced in fall of 2005. The system has been in continuous operation, though initially the main tank was not sealed adequately and as a result proper function did not begin until fall of 2007. Use of this facility increased during the summers of 2009 and 2010, when typical BFS operations were moved temporarily to the Thayer Farm. A period of intensive use occurred in 2011 and is reflected in the performance results. OWTS1 and OWTS2 are located within 100 feet of the western shore of Otsego Lake off of State Highway 80, and are used mainly on weekends during the summer. Each system is shared by two adjacent residences and they are designed to receive daily flows of 440 gallons and 550 gallons respectively. Actual flow for OWTS1 was not measured. Flow through OWTS2 was measured by the service provider. OWTS1 has been in use since 1 June 2006. OWTS2 has been in use since 1 June 2007; this system was not monitored in 2010 or 2011 due to operational issues, which have since been resolved. The HH system was installed at the BFS Thayer Farm to serve the Hop House (BFS temporary main offices and labs), the Thayer Boat House, and the Thayer Farm House (a residential rental) and operation began in April 2009 with waste from the Hop House and Farm House. Flow from the Boat House began in August 2009. The system receives consistent domestic flow from the Farm House, which is anticipated to be beneficial to the treatment system especially during the winter months, which is a low-occupancy period at the BFS.

Preliminary sampling efforts were conducted during the summer of 2007 in order to assess the concentrations of various chemical and nutrient parameters. Regular grab samples were collected between May and August 2008, and June through September 2009. Weekly samples were collected between 9 June and 13 August 2010 and 6 June and 3 August 2011. During each sampling event, approximately 600 mL of wastewater were collected following each treatment component of all systems. Each sample site is shown in Figure 1 as “S#”. Samples were tested for BOD5 using methods summarized by Green (2004). This method involves determining initial dissolved oxygen (DO) concentration of the sample and nutrient buffer followed by incubation at 20°C for five days and determination of the final DO concentration. Samples were diluted to obtain target DO values such that the 5-day DO concentration would be lower than the initial by at least 2 mg/L but with a final concentration greater than 1 mg/L. These conditions were not always achieved, thus valid BOD values were not obtained for every sample collected. Because a nitrification inhibitor is used during incubation, results are presented as values of CBOD, and are associated with the carbonaceous oxygen demand rather than the total oxygen demand (APHA 1992). Overall CBOD reduction rates for each secondary treatment unit (OWTS 1, 2 and HH filters, UIC 1-3) were calculated based on the average CBOD concentrations observed over the monitoring period, presented in Table 6.

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Figure 1. Onsite wastewater treatment system configurations. “S#” indicates a sampling point.

A) The UIC system is comprised of a 2-compartment tank, a phosphorus removal unit, a pump tank, and gravel bed drainfield. Wastewater is circulated and aerated in the first chamber (UIC1 and 2), and settles in the clarification chamber for final solids settling (UIC3). It then flows through the phosphorus removal unit, on to a pump chamber (UIC4), from which it is pumped in to the drain field. B) OWTS1 provides primary treatment in a septic tank and processing tank (PTE) which flow into an equalization tank, then to a pump tank where the wastewater is pumped and sprayed over an open-cell foam media filter (BFE). In this case the foam media filter aerates the wastewater and provides surface area for beneficial bacteria, increasing organic digestion. 25% of flow is returned to the headworks of the processing tank to facilitate the removal of nitrogen from the waste stream, and 50% flows to the P removal unit (PRE) and on to the drainfield via gravity. C) OWTS2 provides primary treatment in 2 septic tanks which flow to a two-compartment processing tank. Effluent flows from the processing tank to a pump tank which periodically doses a textile media filter. Filter-effluent (AXE) is split between the processing tank (PTE) and the P removal unit (PRE). A portion of effluent from the textile media filter is returned to the processing tank to facilitate the removal of nitrogen from the waste stream. D) HH provides primary treatment in 2 septic tanks (STE) which flow to a two-compartment processing tank (PTE). Effluent is pumped from the processing tank to a textile media filter. Filter-effluent (AXE) is split between the processing tank (PTE) and the P removal unit (PRE). A portion of effluent from the textile media filter is returned to the processing tank to facilitate the removal of nitrogen from the waste stream.

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Total suspended solids (TSS) concentration was determined according to the standard method (APHA 1992). A recorded volume of wastewater was filtered through a rinsed, dried, pre-weighed glass fiber filter. Filters were dried for a minimum of 24 hours at 105°C in a gravimetric oven and then removed to a desiccator to cool before being weighed. The concentration of solids in each sample was calculated from the weight of the filtered solids and the volume of sample filtered; concentrations are reported in mg solids/L. Overall TSS reduction rates for each secondary treatment unit (OWTS 1, 2 and HH filters, UIC 1-3) were calculated based on the average TSS concentrations observed over the monitoring period, presented in Table 6.

Total phosphorus concentrations were determined using the ascorbic acid following persulfate digestion method run on a Lachat QuikChem FIA+ Water Analyzer (Laio and Marten 2001). Nitrate and ammonia concentrations were also determined for most samples, using Lachat-approved methods (Pritzlaff 2003, Liao 2001). All reduction and transformation rate estimates are calculated based on average concentrations observed over the duration of the monitoring period (Table 6). Total nitrogen concentrations were not determined and are not presented here due to incomplete oxidation of ammonia to nitrate during the digestion process, which results in underestimation of TN concentration.

SYSTEM PERFORMANCE, OPERATION, AND MAINTENTANCE

Monitoring results for each sampling location in all treatment systems are presented in tabular and graphical form for all parameters monitored (Tables 1-6, Figures 2-5). The tables summarize the testing results for each year (2008-2011) and over the entire monitoring period, including calculated standard error and the sample size. Figures for CBOD, TSS, TP and NO3/NH4 include standard error bars. The overall performance of the systems can be assessed by comparing the first stage of treatment with the last. Typical CBOD concentrations associated with raw wastewater vary greatly (100 – 600 mg/L) depending on per capita water usage and inputs of solids to the system (i.e. garbage grinder waste) (Crites and Tchobanoglous 1998). The industry standard for BOD5 and TSS in effluent from secondary treatment units is 30 mg/L (NSF 2007).

Each system will be discussed individually in the following sections; the treatment performance of each is assessed in addition to a description of operation and maintenance issues encountered over the course of the monitoring period. At the time of installation and design, phosphorus removal units were available from single manufacturer, and so the same treatment unit is used in all four systems; the results obtained for each treatment system expose the same performance and maintenance issues for this specific treatment unit, which are addressed in the last section, Phosphorus Removal Components.

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Upland Interpretive Center (UIC) Typical flow through the system was greatly below the design flow capacity for the

majority of the monitoring period; throughout the monitoring period the system produced high quality effluent, meeting the NSF Standard 40 for Class 1 ATUs (30mg/L CBOD and TSS). In 2010 the system saw more consistent usage and monitoring results indicate enhanced reduction of CBOD and TSS, with high quality effluent produced (final CBOD < 11 mg/L, TSS = 11 mg/L). In 2011, the system experienced a period of intense use, which may have been beyond the treatment capacity of the system. Though this period was relatively short in comparison to the monitoring period (10 days of use by 19 individuals), average 2011 effluent CBOD and TSS concentrations increased substantially, to 54 mg/L and 22 mg/L, respectively (Tables 1 and 2). Over the 4-year monitoring period, the system proved to handle long periods of low usage well. The size of the system is able to accommodate sporadic short-duration heavy-use events without noticeable influence on the quality of final effluent.

Though nitrogen reduction is not a priority of treatment in the Otsego Lake watershed’s wastewater management program, the nitrogen transformations that take place in advanced treatment systems are notable and give insight into the conditions within the treatment system. The final effluent from the UIC system contains relatively high nitrate to ammonium ratio, indicating that the aeration provided in the unit is sufficient for nitrification to take place. System-wide over the 4-year period, nitrogen was reduced by 37%; better removal rates occurred during years where use of the system was higher (without exceeding the design-capacity) (Table 6). Operational Notes

The only major issue encountered with the UIC system was related to its installation. The mid-seam of the 3-compartment tank was not properly sealed at the time of installation. For the first season of its use, the full operating level was never attained (i.e. the tank remained approximately half-full). The problem was not immediately diagnosed because of the low use of the system during non-summer months. Following repair the system has maintained an appropriate operating level.

The blower/aerator by design runs full-time (24/7) and has had no mechanical problems to date. The microbiological inoculant must be replaced on occasion; this doesn’t seem to be critical in the overall functionality of the system. As with all four monitored systems, the nutrient removal unit’s reactive media must be replaced regularly to maintain high phosphorus removal rates and sufficiently low final P concentrations. This is likely more important for units serving systems in close proximity to P-limited water bodies. Onsite Wastewater Treatment System 1 (OWTS 1)

The configuration of this system seems to be less robust than others for seasonal-use situations, due in large part to the above-ground installation of the media filter combined with summer-only use and the long start-up time for the microbiological community that lives in and on the foam media. The foam media comprising the filter in this system is susceptible to settling over time, especially during periods of freeze and thaw. This particular system is installed above ground, and therefore is subjected more extreme temperature variation than its below-ground counterparts. Extreme temperature fluctuations and long period of dormancy (without nutrient, carbon, and water supply) also influence the microbial community, contributing to the long

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period of time required for treatment performance to reach a consistent level following dormant periods. Treatment performance of this particular installation did not meet the manufacturer’s expectation (Jowett 2010) nor was it consistent with the results of other field testing studies (ETV 2003, MASSTC 2004). This discrepancy is likely due to the difference in both configuration and actual use of the system.

Treatment of BOD and TSS improved steadily over the duration of the monitoring program and treatment proved to be enhanced by spring maintenance to combat settling of the foam media that may have occurred during the winter. BOD and TSS concentrations averaged 43 and 33 mg/L, respectively, following treatment in the foam filter. This does not meet the industry standard of 30 mg/L for each parameter (for secondary treatment performance as Class 1 Aerobic Treatment Unit, media filter, etc), though the system was likely still in the “start-up” phase for the majority of the monitoring period each summer. Monitoring protocols used in this study are also different than those used by the National Sanitation Foundation when testing advanced treatment systems again performance criteria (NSF 2007).

Nitrogen concentrations were in line with the other systems monitored, though the incoming ammonium concentration was generally greater than the other systems. This is likely due to the fact that the system was being used on a regular basis and with water conservation in mind, producing a more concentrated waste. Over the entire monitoring period, nitrogen removal averaged about 33%. The reduction of ammonium concentration before and after treatment by the foam filter unit (54%) was less than that achieved by the other systems; this indicates a less effective conversion of ammonium to nitrate within the foam filter itself. Following a service visit in early 2010, the ammonium reduction rate increased (to 77%), indicating that the environment within the filter was better suited to facilitate the nitrification process. Operational Notes

Operation and maintenance issues were related to settling of the foam media over time. Spring maintenance was effective at restoring the treatment performance for all parameters. This servicing involved redistribution of the foam to restore the original packing density and eliminate any preferential flow paths that had allowed wastewater to short-circuit the media. Ideally, wastewater should trickle in a thin film through and around the foam cubes.

Odor coming from this system was also a major issue for the property owners, though it was a design flaw that did not directly impact the treatment performance and was independent of the manufacturers of the treatment components. Three sources of odor were identified; one was the system’s vent stack, another was the lid of the equalization tank, which receives processing tank effluent (mix of septic tank of effluent and foam filter effluent), and the third was the electrical conduit connecting the pump vault to the control panel. All three sources were remedied, though these should be considered by the design engineer prior to installation. The vent stack was extended above the roof-line in order to physically move it away from the patio and deck areas of the two camps served by the system. This pipe was also capped with a carbon-filter assembly to reduce the final odor. The equalization tank’s cover is of poor design and does not provide an air-tight or water-tight seal at the surface. The odor was greatly reduced by weighting the lid down; ideally, this lid should be replaced with a model that will provide a more secure seal. The conduit from the pump vault to the control panel was left unsealed by the installer, and so proved to be the preferential flow path for gas exchange. This conduit was

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sealed with a caulking agent, eliminating the odor problem. All-in-all, while the odor problem did not directly affect treatment performance, public perception and acceptance of advanced treatment systems can be negatively impacted by such oversights. Onsite Wastewater Treatment System 2 (OWTS 2)

Overall treatment performance met expectations in 2008 and most of the 2009 monitoring period compared to the performance of other systems of this type. Prior to the operational problems that began in 2009, OWTS 2 produced high quality effluent containing less than 15 mg/L BOD and TSS on average (Tables 1 and 2) with nitrogen removal between 42 and 50% (Table 6). As a result of the operational issues and subsequent maintenance that was required this system was not monitored in 2010 or 2011. Operational Notes

This system experienced periods of poor treatment unrelated to the design or the treatment processes employed in the system. One of the camps served by the system underwent major renovations, during which time electrical power to the system was inadvertently shut off; this system does not operate by gravity-flow, and so relies on timers, switches, and pumps for proper cycling of wastewater between the treatment components. Although no one was living in the renovated camp, the other camp served by the system was still occupied and sending wastewater to the system. Wastewater was not treated properly and resulted in fouling of the nutrient removal device. The problem persisted though 2011 due to lack of communication between the main service provider to the system and the homeowner, as well as between the main service provider and the manufacturer/service provider for the nutrient removal unit.

This issue highlights a number of areas where more work is needed to ensure that advanced treatment systems are operating properly and to the best of their ability; (1) the need for effective communication between involved parties (regulators, homeowners, and service providers) to ensure that maintenance contracts are in place and carried out according to the manufacturer’s guideline (2) the challenges associated with effectively operating a shared system and (3) the need for homeowners to be aware of the system’s function and operation. All users of the structure must be aware of “good practices” for disposal of wastes in the system – this includes tenants, contractors, guests, etc. These systems are highly engineered and treatment often relies on the presence of beneficial microbial communities. Disposal of chemicals, paints, disinfectants, etc. can reduce or eliminate the populations of such microbes and may also cause fouling of or reduced longevity of other physical and mechanical components of the system (e.g. textile fabrics, coarse filters, pumps, etc.). Hop House (HH) Treatment performance has consistently been at a high level and no major maintenance issues have occurred to date aside from the high media replacement rate for the nutrient removal unit. Incoming waste was of typical strength (100-600 mg/L) for American households. CBOD and TSS concentrations averaged 3 mg/L following treatment in the textile filter (Tables 1 and 2); this is an exceptional level of treatment and standard error indicates a low degree of variability with respect to fluctuations in the concentration of these two parameters. Ammonium concentration was reduced to less than 1 mg/L on average (Table 4), a 99% reduction from the septic tank effluent to textile filter effluent. Nitrogen removal averaged around 34%, which is

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lower than seen in OWTS 2, and may be enhanced by altering the system dosing cycles based on the actual flow received; this is discussed further in the Operational Notes. Operational Notes

No major treatment or mechanical issues were encountered during the monitoring period; all pumps and controls are functioning properly. This particular system has a larger design capacity than a typical residential situation (the Hop House and Boat House are served in addition to a residence); however, the actual flow through the system has generally been less than anticipated. Actual flow through the system can be calculated, but to date this information has not been used to adjust the rate at which wastewater is cycled from the processing tank to the textile filter. As a result, the textile filter is dosed more often than is necessary to adequately treat the waste and therefore the processing tank does not consistently maintain an anaerobic environment to facilitate denitrification (final step of nitrogen removal) of effluent coming in from the textile filter. Treatment would be enhanced by increased oversight of the system by the service provider. Phosphorus Removal Components

The nutrient removal devices are designed to remove phosphorus from the wastewater via chemical adsorption of phosphorus onto the surface of a reactive porous media. Over time the active sites are occupied by adsorbed phosphorus and the efficiency declines until no active sites remain. These work well but require frequent replacement in order to maintain high degree of phosphorus removal, as a result of the relatively small volume of reactive media in each unit. Larger media canisters would reduce the frequency of media replacements. The size of each unit was not scaled to correspond to the designed treatment capacity of the system with which it was installed. In the case of the Hop House system, following replacement of the reactive media, acceptable treatment was documented for less than 3 months before the adsorptive capacity of the media was reached. Frequent sampling and analysis for total phosphorus concentration is the only way to determine the efficacy of each unit; it is unlikely that such sampling would be done more than once per year in a typical residential situation.

CONCLUSIONS

Treatment Technologies Media Filters (Textile, Foam, Dosing Regime) Textile filters provided the most consistent and effective treatment of the three types installed in the demonstration systems. CBOD and TSS were consistently below 15 mg/L and showed little variation over the sampling period under normal operating conditions. The filter media are arranged in hanging sheets, and so are not subject to settling or compaction over time; it seems that this arrangement, combined with an insulated cover and below-ground installation, result in a short start-up period at the beginning of the occupancy season. The foam filter’s performance was variable and frequently fluctuated above the industry standard for this class of system. When installed for seasonal use, spring maintenance is needed to ensure that the media is properly distributed in the baskets, as settling may have occurred due

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to freeze and thaw during the winter. A long period of time (upwards of 8 weeks in some cases) was required at the start of each summer occupancy season for the establishment of a sufficient microbial community such that consistent and acceptable treatment was documented. Microbial populations are greatly reduced during periods without flow (i.e. winter) and are likely further reduced during periods of extreme cold. This should be considered in the design process if this technology is to be used at other seasonal installations; installing the media filter underground may provide enough thermal buffering to reduce the temperature fluctuation and in so doing, reduce the settling and start-up period.

Differences observed in the treatment performance of the foam and textile filters may be related more to the dosing regimens rather than the ability of either media to provide a favorable treatment environment. Dosing regimes are typically based on either time or demand (flow).

• A Timed Cycle: A predetermined volume is dosed at a regular time interval. Both systems incorporating textile filters (OWTS 2 and HH) were time-dosed (a requirement of the manufacturer).

o Storage capacity is built-in to allow for holding of wastewater for later processing based on default schedule

o Flow is distributed over a 24-hour period Eliminates potential inundation of treatment components and the

drainfield; • Holds water during high-use periods (shower-time, laundry,

etc.) • Cycles wastewater throughout the day and night, providing

consistent flows to the treatment technologies and the drainfield during lower-use periods

Allows for alternation between unsaturated and saturated flow, and thus, aerobic and anaerobic conditions

• Facilitates gas exchange • Facilitates activity of both aerobic and anaerobic microbial

populations – together yield more effective and complete breakdown of wastewater constituents

o Floats detect high-flow conditions and can trigger the over-ride of default timing cycle to more quickly process wastewater, accommodating extreme events without compromising the integrity of system components.

o In seasonal-use or weekend-use situations, cycling of wastewater between a processing tank and the filter continues even during periods where no new water enters the system, maintaining nutrient and water supply to the microbial populations.

• Demand (flow through the system): A predetermined volume is transferred every time that specific volume accumulates in a dosing chamber. The foam filter (OWTS 1) operated on demand-dosing.

o During high flow periods, wastewater may be dosed without a time delay in order to keep up with incoming flow. This may result in the inundation of subsequent treatment components (such as a nutrient removal device) that have a limited volume capacity and require a longer period of time for wastewater to pass through.

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o During periods with little or no use, no water is dosed to the filter unit, potentially resulting in a reduction in the microbial population.

. Aerobic Treatment Unit The aerobic treatment unit (ATU) serving the UIC produced effluent of consistent quality, though the system saw very low use compared to its designed capacity. CBOD and TSS were generally below 15 mg/L and nitrogen was removed at moderate rates. It handled typical UIC functions and events (field trips, workshops, etc.) and long periods of low use very well without compromising effluent quality. Phosphorus Removal Devices

The effective life-span of the reactive media within the phosphorus removal devices was disappointing, especially given the cost of the units and fees associated with media replacement. These units work well but require frequent replacement in order to maintain high degree of phosphorus removal as a result of the relatively small volume of reactive media in each unit. Larger media canisters would reduce the frequency of media replacements. In order to adequately address the need for phosphorus removal in certain locales, a more affordable, longer-lasting design is essential. Monitoring Procedures

Sampling protocols can influence the observed treatment performance and varies with the type and configuration of each system. Comparisons between monitoring and assessment efforts should acknowledge such details.

• Grab samples are likely to be more variable and have a higher associated standard error if the quality of effluent is variable over the course of a day.

• Composite samples capture the range of conditions encountered throughout the day, providing flow-weighted results of effluent quality produced by the system.

• The potential for sampling protocol to influence results will vary with the configuration of the system.

o Some systems continuously mix wastewater and yield more consistent results over the course of a 24-hour period, whereas a system with discrete treatment components will experience variation over the course of a day, depending on use of the system, in which case a grab sample may yield non-representative results if such factors are not considered.

• Sufficient sample size should allow for a range of conditions to be encountered, providing an average that is representative of the effluent quality that typically leaves the system, though this cannot be guaranteed.

Lessons Learned Oversight of Operation & Maintenance

Communications with service providers and manufacturers resulted in remedied issues and increased treatment performance. Vigilance in the maintenance of advanced treatment systems is of the utmost importance if these systems are to be relied upon to reduce human

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impacts to sensitive environments, especially considering that the vast majority of systems are not monitored once they are installed, as they were with this project. Property Owner Awareness & Proper Use

Homeowners, as the primary users of such systems, are the key to ensuring proper use and maintenance. Steps should be taken to stress the importance of their participation as a means of protecting their investment in addition to protecting public health and their surrounding environment. In a few instances, as outlined in the system performance section of this report, operational issues occurred due to a lack of communication between the property owners of shared systems, or between the property owners and others that were renting or working on the property. Owners failed to recognize the importance of informing the other users as to the requirements of the system (i.e. electrical power) and best practices for disposal of materials to the system.

REFERENCES

Albright, M.F. and H.A. Waterfield. 2010. Evaluation of phosphorus removal media for use in onsite wastewater treatment. In: 42nd Ann. Rept. (2009). SUNY Oneonta Bio. Fld. Sta. Cooperstown, NY.

Albright, M.F., L.P. Sohaki, and W.N. Harman. 1996. Hydrological and nutrient budgets for Otsego Lake, N.Y. and relationships between land form/use and export rates of its sub-basins. Occ. Paper #29, SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Anonymous. 1998. A plan for the management of the Otsego Lake watershed. Prepared by:

Otsego Lake Watershed Council. Anonymous. 2007. A plan for the management of the Otsego Lake watershed. Prepared by:

Otsego Lake Watershed Council (1998). Updated by the Otsego County Water Quality Coordinating Committee.


17th ed. American Public Health Association. Washington, DC. Crites, R. and G. Tchobanoglous. 1998. Small and Decentralized Wastewater Management

Systems. McGraw-Hill, p183 Environmental Technology Verification Program (ETV). 2003. ETV Joint Verification

Statement: Waterloo Biofilter® Model 4-Bedroom. National Sanitation Foundation and US Environmental Protection Agency.

Green, L. 2004. Standard Operating Procedure 011: Biochemical Oxygen Demand (BOD)

Procedure. University of Rhode Island Watershed Watch. Harman, W.N. 1997. The state of Otsego Lake 1936-1996. Occ. Paper #30, SUNY Oneonta Bio.

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Fld. Sta., SUNY Oneonta. Jowett, C. 2010. Personal Communication. February 2010. Knight Treatment Systems. 2007. The knight nutrient removal device. http://www.knighttreatmentsystems.com. Accessed March 2011. Liao, N. 2001. Determination of ammonia by flow injection analysis. QuikChem®Method 10-

107-06-1-J. Lachat Instruments. Loveland, Colorado. Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis

(colorimetry acid persulfate digestion method). QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

MASSTC. 2004. US EPA Environmental Technology Initiative Onsite Wastewater Technology

Testing Report: Waterloo Biofilter®. Massachusetts Alternative Septic System Test Center, Cape Cod, MA.

National Science Foundation (NSF). 2007. NSF wastewater programs update and NSF/ANSI standards 40 and 245. (presentation). www.nsf.org

Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow injection

analysis.QuikChem®Method 10-107-04-1-C. Lachat Instruments, Loveland, Colorado.

Waterfield, H.A. 2010. Treatment performance of advanced onsite wastewater treatment systems in the Otsego Lake watershed, 2009 results update. In: 42nd Ann. Rept. SUNY Oneonta Bio. Fld. Sta. Cooperstown, NY.

Waterfield, H.A. 2011. Treatment performance of advanced onsite wastewater treatment systems

in the Otsego Lake watershed, 2010 results update. In: 43rd Ann. Rept. SUNY Oneonta Bio. Fld. Sta. Cooperstown, NY.

Waterfield, H.A. and S. Kessler. 2009. Treatment performance of advanced onsite wastewater

treatment systems in the Otsego Lake watershed, 2008 results. In: 41st Ann. Rept. SUNY Oneonta Bio. Fld. Sta. Cooperstown, NY.

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http://www.knighttreatmentsystems.com/

http://www.nsf.org/

Baseline water quality assessment of aquatic benthic macroinvertebrates in streams prior to natural gas extraction; Otsego County, NY

K. Whitcomb1

INTRODUCTION

Otsego County, New York lies on the Allegheny Plateau forming the headwaters of the Susquehanna River drainage basin. The northern portion of the county is underlain by limestone bedrock with formations typical of karst topography. Moving southward, shale bedrock is exposed at the surface (Harman, 1997). With the exception of the extreme northern reaches, the county overlies the Marcellus shale formation. Otsego County has a long history of agriculture-dominated land use. Stream impacts are generally related to agricultural practices, road ditching, residential development, and small-scale forestry operations. These land use practices have been relatively stable over the past few decades, though new developments in the energy industry have the potential to increase activities related to the exploration for and extraction of natural gas. Although horizontal drilling of Marcellus Shale has yet to begin in Otsego County, hydrofracturing, a natural gas extraction method, poses a water quality contamination threat to the county because of the chemicals and salts involved in the procedure (Swarthmore 2011). Because of the possible threat to surface and groundwater quality, the Otsego County Soil and Water Conservation District (SWCD) took action to document the current state of water quality and stream health throughout the county based on benthic macroinvertebrate community composition in addition to standard physical and chemical water quality parameters.

The benthic macroinvertebrate community present in a stream can be used to gage water quality and stream health (Hilsenhoff 1988), and thus provide an indication of impairment caused by land uses in the watershed or pollutant discharge upstream of the sampling location. Benthic stream macroinvertebrates are generally made up of 17 potential taxonomic orders and exhibit a wide range of tolerances to stream impairment (Zimmerman, 1993). For example, hoverflies (Diptera, Syrphidae) are very tolerant to pollution, while midges (Diptera Blephariceridae) are extremely sensitive to pollution even though they both belong to the order Diptera. Therefore the taxa present within a stream can be used to determine the extent of pollution. A reduction in water quality would be expected to be associated with a reduction in species diversity and richness due to the loss of sensitive taxa. Other parameters were also collected for a baseline of current water quality including; dissolved oxygen, turbidity, pH, conductivity, total dissolved solids, salinity, and temperature.

MATERIALS AND METHODS

Benthic macroinvertebrates were collected from 20 different streams throughout Otsego County between 27 June and 7 July 2011 (Figure 1). Table 1 shows a list of the Hydraulic Unit Code (HUC) identification numbers along with the corresponding stream names. The sampling locations were taken as a subset of the 50 SWCD stream monitoring sites. Sites were chosen 1 Biology Department Intern. Present Affiliation: SUNY Oneonta. Funding provided by the Otsego County Conservation Association.

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based on ease of access and stream structure; samples were only collected within riffles to be consistent with established macrobenthic sampling protocols (NYSDEC 2009). Samples were collected using a Wildco Hess®Sampler (13”ID x 16”) with a 600µm mesh sock and sample cup. The sampler was inserted approximately 6 inches into the substrate and stones and substrate contained within were rubbed to wash any organisms into the sample cup. On average 10-15 minutes were spent collecting at each field site depending on velocity of stream flow and size of substrate present. Organisms collected on site were put into a Nasco WHIRL-PAK® and preserved in 70% ethanol. Samples were then brought back to the lab where they were identified to family level (Peckarsky 1995, Voshell 2002). Conductivity, total dissolved solids, pH, temperature, and time/date data for each site was collected using a Professional Series YSI® probe, provided by the Otsego County Soil and Water Conservation District. Dissolved oxygen data was collected using an EcoSense® DO200 meter, and salinity with an OAKTON® SALT 6 Acorn series Salinity Meter, each provided by the Geography Department of SUNY College at Oneonta.

Four commonly used indices were calculated to evaluate the benthic community at each site. These indices were Family-level Biotic Index (FBI), Percent Model Affinity (PMA), Taxa Richness, and Ephemeroptera-Plecoptera-Trichoptera (EPT) Richness. These indices were chosen for their simplicity and accuracy in accordance with the NYS-DEC Biological Assessment of Water Quality. Both Taxa Richness and Family-level Biotic Index were substituted for Species Richness and Hilsenhoff’s Biotic Index (Hilsenhoff 1988), following the methods of previous sampling (Bailey 2011) so that lab identification would only need to be done to family level. Table 1. List of stream sites and their Hydraulic Unit Code (HUC) numbers. * indicates samples collected in 2010 by Bailey (2011).

HUC Site HUC Site 101 Otsdawa Creek, Otsego Trout* Trout Brook, Richfield

1102B Brier Creek, Otego 102D* Ocquionis Creek, Richfield 703B Mill Creek, Edmeston 605B Spring Brook, Milford

501 West Branch Otego Creek,

Laurens 304C Moorehouse Brook, Maryland 803D Cahoon Creek, Butternuts 603D Trout Brook, Springfield 503C Lake Brook, Laurens 304B Potato Creek, Maryland

204B Unnamed Blue Line Lower CV,

Middlefield 504C Harrison/Cooper Creeks, Laurens 604D Red Creek, Middlefield 1103B Indian/Sand Hill Creeks, Unadilla 203C Shellrock Brook, Middlefield 910B Rogers Hollow Brook, Unadilla 203B O'Connel Brook, Middlefield 303E Decatur Creek, Worcester 102B* Herkimer Creek, Exeter 302 Elk Creek, Maryland 102C* Hyder Creek, Richfield 103B Fly Creek, Otsego

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Figure 1. Map of Otsego County showing 2010-2011 sample collection sites.


Table 2 summarizes the average values of dissolved oxygen, pH, conductivity, total dissolved solids, and temperature at each sample location for the summer. The variations in conductivity and total dissolved solids were consistent with the known variations in geologic gradients throughout the county. All pH values were within expected ranges. Specific numerations were not found for salinity because freshwater has a near zero value for salts, but each site was determined to have a value of less than 1.5 ppt NaCl due to the sensitivity of the probe used.

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Table 2. Averages of dissolved oxygen, turbidity, pH, conductivity, total dissolved solids (TDS), and temperature of each sample site for the summer. See Figure 1 for site locations.

Site DO

(ppm) pH Conductivity

(mS/cm) TDS

(mg/L) Temp (oC)

Otsdawa Creek, Otsego 8.93 7.83 0.106 113.85 20.7 Brier Creek, Otego 8.55 7.77 0.091 81.18 21.2

Mill Creek, Edmeston 9.42 7.93 0.127 145.53 18.7 West Branch Otego Creek, Laurens 10.26 7.52 0.088 98.01 19.3

Cahoon Creek, Butternuts 7.97 7.49 0.131 141.57 20.8 Lake Brook, Laurens 9.9 7.44 0.089 99.99 18.6

Unnamed Blue Line Lower CV, Middlefield 9.86 7.84 0.102 122.76 15.5

Red Creek, Middlefield 8.92 8.16 0.167 193.05 23 Shellrock Brook, Middlefield 9.63 8.32 0.11 116.82 21.4 O'Connel Brook, Middlefield 8.7 7.33 0.126 139.54 19.1

Herkimer Creek, Exeter 8.32 8.17 0.31 325.71 21.9 Hyder Creek, Richfield 8.49 8.07 0.448 459.36 23.2

Ocquionis Creek, Richfield 9.03 8.19 0.006 5.94 21.7 Spring Brook, Milford 9.76 8.16 0.091 103.95 18.3

Moorehouse Brook, Maryland 9.89 7.51 0.083 97.02 16.9 Trout Brook, Springfield 9.54 8.6 0.28 328.68 16.9 Potato Creek, Maryland 9.87 7.85 0.046 54.45 16.7

Harrison/Cooper Creeks, Laurens 9.68 7.45 0.133 144.54 20.3 Indian/Sand Hill Creeks, Unadilla 8.62 7.91 0.091 98.01 20.4 Rogers Hollow Brook, Unadilla 9.52 8.29 0.076 82.17 20.8

Decatur Creek, Worcester 9.56 8.32 0.13 138.6 21.3 Elk Creek, Maryland 10.22 7.67 0.104 115.83 18.9

Fly Creek, Otsego 9.17 8.23 0.23 242.5 21.9

EPT Richness represents the total number of families within the orders Ephemeroptera, Plecoptera and Trichoptera. These three orders are used because they are generally ubiquitous, and most of the families are intolerant of organic pollution. Therefore, a high EPT richness indicates relatively good water quality. Taxa Richness characterizes the total number of different families within all orders of invertebrates collected. Since it is not limited to the orders of EPT, taxa richness gives a more complete idea of water quality when considered along with the results of EPT richness. Figure 2 provides EPT Richness and Taxa Richness for all sites evaluated. Elk Creek and Decatur Creek had the highest values for both EPT and taxa richness, showing the greatest amount of diversity, indicating good water quality. Herkimer Creek, Hyder Creek and Trout Brook, all in the Canadarago Lake watershed, had the fewest EPT taxa present, though the total number of taxa present there was more in line with most other streams.

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Figure 2. Comparison of Taxa Richness and Ephemeroptera-Plecoptera-Trichoptera Richness at 20 sample sites in Otsego County collected between 27 June and 7 July 2011, and 4 sites previously sampled (Bailey, 2010).

Family-level Biotic Index is calculated using an adapted equation from Hilsenhoff’s original species-level biotic index. Based on a 1-10 scale, families with greater tolerance to pollution receive higher values, while the intolerant families hold lower values. Consequently a lower overall biotic index value indicates healthier water quality (Table 3). Although more than half of the sampled streams fell into the excellent or very good categories of the Familial Biotic Index (Figure 3), both Hyder Creek and Herkimer Creek fell within the poor quality range indicating very significant organic pollution with scores of 7.52 and 7.70 (Zimmerman 1993). All 4 of the streams within the Canadarago Lake watershed scored the highest on the FBI scale, suggesting that the area has more degraded surface water than the rest of the county.

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Table 3. Scale of Familial Biotic Index values from 1-10 where 0 represents no organic pollution and 10 represents harsh organic pollution.

0.00–3.50 Excellent; No apparent organic pollution 3.51–4.50 Very good; Possible slight organic pollution

4.51–5.50 Good; Some organic pollution 5.51–6.50 Fair; Fairly significant organic pollution 6.51–7.50 Fairly poor; Significant organic pollution 7.51–8.50 Poor; Very significant organic pollution

8.51–10.0 Very poor; Severe organic pollution

Figure 3. Family level Biotic Index values for 24 stream sites in Otsego County collected between 27 June and 7 July 2011. Table 3 outlines the 1-10 value scale used in this figure. The higher the value, the more severe the organic pollution; darker bars indicate more stressed sights.

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Percent Model Affinity (PMA) calculates the percentage similarity of a sampled community to an ideal community according to taxa present and their relative abundance according to calculation methods set by Hilsenhoff 1988. Figure 4 summaizes PMA values for each sampled stream and Table 4 represents the percentage make up of the model community. More than half of Otsego County was within the excellent quality to slightly impacted range of percentages, while the streams within the Canadarago Lake watershed along with Harrison/Cooper Creeks in Laurens and the Springfield Trout brook all scored within the moderately to severely impacted range.

Figure 4. Percent Model Affinity indicates a community’s similarity to the model community based upon the percentages of the orders Oligochaeta, Ephemeroptera, Plecoptera, Coleoptera, Trichoptera, Chironomidae, and other families present. The lower percentages indicate lower quality water. Anything higher than 64 percent indicates excellent water quality, while 50-64 is slightly impacted, 35-49 is moderately impacted, and less than 35 is severly impacted. Darker bars highlight more stressed sights.Table 4 presents the model community.

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Table 4. Percentages of orders that make up the model stream benthic macroinvertebrate community used in the Percent Model Affinity index (NYSDEC 2009).

Order

NYS DEC Model

Community Ephemeroptera (Mayfly) 40%

Plecoptera (Stonefly) 5% Trichoptera (Caddisfly) 10% Chironomidae (Midge) 20%

Coleoptera (Beetle) 10% Oligochaeta (Worms) 5%

Other 10%

CONCLUSIONS Table 5 summarizes the relative inferred water quality when the macrobenthic communities were evaluated by each macrobenthic index considered. Generally, the different indices provided consistent evaluations of water quality, though the Percent Model Affinity index was most often in disagreement; it often overestimated the quality of conditions relative to the other indices, and in some instances ranked conditions as being high when the others indicated that they were degraded. Several streams consistently ranked as having high water quality (Fly Creek, Elk Creek, Decatur Creek, Rogers Hollow Brook, Moorehouse Brook and Red Creek). Others were consistently ranked as being degraded (Ocquionis Creek, Trout Brook (Richfield), and Herkimer Creek). Other streams were either consistently ranked as having marginal impairments, or the indices provided conflicting results.

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Table 5. Relative rankings of water quality based on macrobenthic communities present at each Otsego County stream site when evaluated by the benthic indices used (EPT Richness, Total Taxa Richness, Familial Biotic Index and Percent Model Affinity).

EPT Taxa Richness Richness FBI PMA Fly Creek, Otsego + + 0 + Elk Creek, Maryland + + + 0 Decatur Creek, Worcester + + 0 + Rogers Hollow Brook, Unadilla + 0 + 0 Indian/Sand Hill Creeks, Unadilla - - + 0 Harrison/Cooper Creeks, Laurens - - + - Potato Creek, Maryland 0 0 - + Trout Brook, Springfield - - + - Moorehouse Brook, Maryland + + + + Spring Brook, Milford 0 0 - 0 Ocquionis Creek, Richfield 0 + 0 - Trout Brook, Richfield - - - 0 Hyder Creek, Richfield - - - - Herkimer Creek, Exeter - - - - O'Connel Brook, Middlefield + 0 0 0 Shellrock Brook, Middlefield 0 0 + 0 Red Creek, Middlefield + 0 + + Unnamed Blue Line Lower CV, Middlefield 0 0 0 0 Lake Brook, Laurens 0 - + 0 Cahoon Creek, Butternuts 0 - 0 + West Branch Otego Creek, Laurens 0 0 0 + Mill Creek, Edmeston 0 - 0 + Brier Creek, Otego + 0 0 + Otsdawa Creek, Otsego - - 0 +

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REFERENCES

Bailey, C. 2010. Macroinvertebrate survey and biological assessment of water quality: tributaries of Canadarago Lake; Otsego County, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W. Sohacki, L. Albright, M. Rosen, D. 1997. The State of Otsego Lake, 1936-1996.

Occasional Paper No. 30. Jan. 1997. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Hilsenhoff, W.L. 1988. Rapid field assessment of organic pollution with a family-level biotic

index. Journal of the North American Benthological Society, Vol. 7 No. 1 pp. 65-68. New York State - Department of Environmental Conservation. 2009. Standard operating

procedure: Biological monitoring of surface waters in New York State. Albany NY. Peckarsky, B.L., Fraissinet, P.R., Penton M.A., Conklin, D.J. 1995. Freshwater

macroinvertebrates of Northeastern North America. Comstock Publishing Associates-Cornell University Press. Ithaca, NY.

Swarthmore College of Environmental Sciences. 2011. Natural Gas Drilling in the Marcellus

Shale. Human Health Risks. http://www.swarthmore.edu/x29633.xml Voshell, J.R. 2002. A guide to common freshwater invertebrates of North America. McDonald &

Woodward Publishing Company. Blacksburg, VA. Zimmerman, M.C. 1993. The use of the biotic index as an indication of water quality. Tested

studies for laboratory teaching, Vol. 5. pp. 85-98.

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Difference in the aquatic micro-invertebrate fauna of two common foliose epiphytic lichens

Benjamin P. German1 and John R. Foster2

Abstract: The aquatic micro-invertebrate fauna of common greenshield lichen (Flavoparmelia caperata) and rough speckled shield lichen (Punctelia rudecta) from the same individual red oak (Quercus rubra) trees, in Otsego County NY, were examined to determine if there were differences between their respective micro-invertebrate communities. Paired 2g lichen samples from the same tree were soaked in individual 50 mL baths of de-chlorinated water, sprayed off and the wash water was examined for aquatic micro-invertebrates. While the aquatic micro-invertebrate fauna of the two species of lichens consisted of the same three metazoan phyla: Tardigrada (water bears), Rotifera (rotifers), and Nematoda (roundworms), the common greenshield supported several times the density of water bears, twice the density of rotifers, and more roundworms. Species occurrence, richness, and community composition also differed. Difference found between aquatic micro-invertebrate communities of two similar lichen species on the same tree, indicate lichens may present some exceptional opportunities for ecological research.

INTRODUCTION

Epiphytic tree lichens, also referred to as corticolous lichens, are common throughout the world’s forests. Over 100 species of corticolous lichens have been reported from New York State alone (Harris 2004). They have been the subject of numerous studies in New York (Brodo 1966), North America (Culberson 1955, Carmer 1975, Schutte 1977) and around the world (Harris 1971, Wolseley & Aguirre-Hudson 1997, Mistry 1998).

Corticolous lichens provide unique aquatic micro-habitats, which are widely dispersed

throughout the terrestrial forest. These micro-aquatic ecosystems undergo frequent desiccation and exposure to the elements allowing only the hardiest organisms to survive. Three aquatic micro-invertebrate phyla commonly occur on epiphytic lichens: Bdelloid rotifers, round worms and water bears (Culberson 1955; Gerson and Seward 1977). The abundance of these micro-invertebrates on corticolous lichens appears to be correlated with lichen biomass (Stubbs, 1989) and humidity (Meininger et al. 1985).

While the occurrence of micro-invertebrates on corticolous lichens has been known for

decades, the distribution of aquatic micro-organisms among the many different species of epiphytic tree lichens has not been studied. In this study two corticolous lichens, common greenshield lichen (Flavoparmelia caperata) and rough speckled shield lichen (Punctelia 1 Robert C. MacWaters Internship in the Aquatic Sciences, summer 2011. Present affiliation: Dept. of Fisheries and Wildlife Technology, SUNY Cobleskill. 2 BFS visiting Researcher. Dept. of Fisheries and Wildlife Technology, SUNY Cobleskill.

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rudecta) were examined to determine if there were any differences in the aquatic micro-invertebrate community they supported.

MATERIALS & METHODS

Common greenshield (F. caperata) and rough speckled shield lichen (P. rudecta) were utilized for this study (Figure 1). These two epiphytic lichens were selected because they were not considered to be sensitive or rare (Walewski, 2007; Brodo, Sharnoff & Sharnoff, 2001). These two species also shared the same habitat growing in close proximity on the same trees. These qualities made these lichens ideal candidates for a community association study.

Figure 1. Common greenshield (Flavoparmelia caperata) and rough speckled shield lichen (Punctelia rudecta) utilized in this study.

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This study was conducted in Otsego County, NY outside the city of Oneonta (42.4711, -75.0253). All samples were collected from a single stand of red oak (Quercus rubra) that had been logged within the last thirty years. Elevation of the collection site was approximately 1800 feet above sea level. Red oak trees were chosen because they supported an abundance of epiphytic lichens. The two lichens chosen for this study were the most abundant species in the sample area and therefore represented the least chance for harvesting impact.

Winter data were collected from 15 paired samples made during January-March 2011.

Summer data was collected from June-July 2011, and also consisted of 15 paired samples. This study used a variation of Romano’s (2003) techniques for the collection of water

bears. Trees were selected that supported colonies of both lichen species so that the lichens could be collected in pairs, one of each species from the same tree. Lichens were scraped off the tree with a pen knife. Samples were then placed in individual sealable plastic bags.

In the lab, 2 grams of lichen were removed from each sample and weighed on a digital

scale. Each sample was then placed in a glass finger bowl filled with 50 ml of de-chlorinated water. After soaking for one hour the lichen samples were sprayed off and removed from the water. The water remaining in the finger bowl was examined for aquatic micro-organisms with a dissecting microscope. All micro-organisms found in the wash water were then transferred to a glass slide, examined under a compound microscope and identified utilizing Pennak (1989).

RESULTS

Community Composition

The aquatic micro-invertebrate fauna occurring on greenshield and rough speckled lichen were dominated by rotifers (Figure 2). Overall, the aquatic micro-invertebrate community on these two lichens consisted of 73.1% rotifers, 16.6% round worms and 10.2% water bears. However, the community composition of aquatic micro-invertebrate fauna of greenshield lichens differed significantly from rough speckled lichen in both the winter and summer (Chi Square Test P < .001).

Density

The density of micro-organisms per gram on greenshield lichen (16.4/g) was significantly higher than the density on rough speckled lichen (10.1/g, Chi Square test P < .001). Greenshield lichen had a significantly greater density of water bears and rotifers than rough speckled lichen in both winter and summer samples (Chi Square Test P < .001). Round worm density was comparable in the winter, but the rough speckled lichens had significantly more round worms than greenshield lichen in the summer sample (Chi Square Test P < .05).

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Figure 2. Density of rotifers, water bears and round worms collected on greenshield and rough speckled lichens during the winter and summer.

Rotifer density was nearly identical between the winter and summer samples on greenshield lichen (6.13/g winter, 6.22/g summer) and rough speckled lichen (3.45/g winter, 3.53/g summer). Water bears showed a significant increase in density from winter to summer, on both greenshield lichen (0.8/g winter, 1.23/g summer) and rough speckled lichen (0.15/g winter, 0.52/g summer). Round worms showed the sharpest increase in density from winter to summer samples. Round worm density increased from 0.42/g in winter to 1.57/g summer on greenshield lichen and from 0.37/g (winter) to 2.05/g (summer) on rough speckled lichen. The high density of round worms in the summer data for rough speckled lichen can be partially attributed to a single sample that contained over fifty individuals (nearly half of the total for all 15 samples).

Population Correlations

Paired samples of greenshield and rough speckled lichens were collected from the same tree. Because of this close physical association and microclimate similarity a strong correlation was expected in the aquatic micro-fauna of each paired sample. However, this was not the case. There was no significant correlation between water bear density (r = .396) and nematode density (r = .348) on paired samples of greenshield and rough speckled lichen from the same tree (P > .05). Rotifer density on greenshield lichen was significantly correlated to rotifer density on rough speckled lichens (Figure 2) in the winter (r = .785, P < .001), but not in the summer (r = .475, P > .05). These data indicate that in spite of the close proximity between greenshield lichen and rough speckled lichen on the same tree, population density of rotifers in the summer, and nematodes and water bears in the winter and summer were independent of each other.

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Figure 3. Correlation of rotifer density (number per gram) on samples of greenshield lichen and rough speckled lichen collected from the same tree. Species Richness

Species richness was difficult to measure. Philodina was the only genus of Rotifera found in the samples and round worms were particularly difficult to identify. Permanent slides of round worms did indicate that they belonged to at least two different families (Reyda, pers. Comm.). Only water bears provided enough data to examine species richness.

Greenshield lichen had more species of water bears (4) compared to rough speckled

lichen (3). This was because Hypsibius sp. was found exclusively on rough speckled lichen (Figure 4). Overall, the water bear community was quite different between the two species of lichens and between the winter and summer months (Figure 4).

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Figure 4. Density of water bear genera on greenshield and rough speckled lichens during the winter and summer. Relative Abundance

Macrobiotus sp. was the most abundant water bear on winter samples of rough speckled lichen, but was the least abundant species on common greenshield lichen in the winter (Figure 4). In the summer Milnesium tartigrada, a predatory water bear, was most numerous on both species of lichen.

In the winter Echiniscius sp., Hypsibius sp. and Milnesium tartigrada were significantly

more abundant on greenshield lichen than rough speckled lichen (P < .01, Chi Square Test). In the summer the densities of all species of water bears were higher on the greenshield lichen than on the rough speckled lichen. However, in the summer only the Echiniscius sp. (P < .01) and Hypsibius sp. (P < .05) were significantly more abundant on greenshield lichen, although both Macrobiotus sp. and Milnesium tardigradum were close with a P value of < .06).

The density of Echiniscius sp. and Hypsibius sp. was lower in the summer than in the

winter samples on both lichens (Figure 4). However, summer densities of Macrobiotus sp. were signficantly higher on greenshield lichen (P < .001, Chi Square Test) and Milnesium tartigrada densities where higher on both lichens (P < .001, Chi Square Test) in the summer.

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DISCUSSION

Significant differences were found in community composition, density, species

occurrence, species richness and relative abundance, between common greenshield lichen and rough speckled shield lichen. The hypothesis that two lichens with similar growth forms, identical habitats, and the same microclimate would support similar communities of aquatic micro-fauna was not supported by the results of this study. Some other variables, besides those previously mentioned, are responsible for the differences observed in the aquatic micro-fauna of these two species of lichens. Although the two lichen species share the same habitat and form (foliose), the micro topography of the lichen surface does differ. This could offer micro-communal advantages/disadvantages (Brodo et al. 2001, Walewski, 2007). Some micro-invertebrate populations have been known to undergo large population fluctuations throughout the year (Little, 1986). However, rotifer populations did not act this way on lichens. Rotifer density was remarkably constant between winter and summer samples on both common greenshield lichen and rough speckled shield lichen. Also, rotifers were the only taxa to demonstrate a correlation in density on paired lichen samples found on the same tree. Future research is needed to gather more population data.

Differences found between aquatic micro-invertebrate communities of two similar lichen species on the same tree indicate that the study of the aquatic micro-invertebrate fauna of epiphytic tree lichens may present some exceptional opportunities for ecological research. While the aquatic micro-invertebrate fauna of the two species of lichen consisted of the same three metazoan phyla: Tardigrada (water bears), Rotifera (rotifers), and Nematoda (round worms), the common greenshield supported three times the density of water bears, twice the density of rotifers and slightly more round worms. Further study is warranted with different species of lichen and at different times of the year. A closer examination of rotifer and round worm communities should also be carried out.

The ephemeral aquatic micro-habitat found on corticolous lichens is a unique and poorly

understood ecosystem. The diversity and numbers of aquatic organisms found on the thalli of common greenshield lichen and rough speckled shield lichen was remarkable. Additional research including several more species of lichen, such as lignicolous, terricolous, and saxicolous lichens, may provide a better understanding of these overlooked aquatic ecosystems.

REFERENCES Brodo, I. M. 1966. Lichen growth and cities: A Study on Long Island, New York.

The Bryologist, Vol. 69, No. 4 pp. 427-449. Brodo, I. M., S.D. Sharnoff, and S. Sharnoff, 2001. Lichens of North America. London: Yale

University Press. Carmer, M. 1975. Corticolous lichens of riparian deciduous trees in the central front

range of Colorado. The Bryologist, Vol. 78, No. 1 (Spring, 1975), pp. 44-56.

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Culberson, W.L. 1955. The corticolous communities of lichens and bryophytes in the upland forests of northern Wisconsin. Ecological Monographs 25:215-231.

Gerson, U. and M.R.D. Seaward. 1977. Lichen-invertebrate associations. pp 69-119. In

M.R.D. Seward (ed.), Lichen Ecology. New York. Harris, G. P. 1971. The ecology of corticolous lichens 1. The zonation on oak and birch in South

Devon. Ecology 59: 431-439. Harris, R.C. 2004. A preliminary list of the lichens of New York. Opuscula Philocichenum 1:55-

74.

Little, C. 1986. Fluctuations in the meiofauna of the aufwuchs community in a brackish-water lagoon. Vol. 23, Issue 2, 263–276.

Meininger, C.A. and G.W. Uetz, (1985). Variation in epiphytic microcommunities (Tardigrade-

Lichen-Bryophyte Assemblages) of the Cincinnati Ohio Area. Urban Ecology Vol. 9, 45-61.

Mistry, J. 1998. Corticolous lichens as potential bioindicators of fire history: A study in the

Cerrado of the Distrito Federal, Central Brazil. J. of Biogeography , Vol. 25, No. 3, pp. 409-441.

Nelson, D.R. 2002. Current status of the Tardigrada: evolution and ecology. Integrative and

Comparative Biology, Vol. 42, No. 3, 652-659. Pennak, R.W. 1989. Freshwater invertebrates of the United States: Protozoa to Mollusca.

Wiley. New York. Reyda, F.B. 2011. Pers. Comm. SUNY Oneonta Biol. Fld. Sta. Cooperstown, NY. Romano, I. F. 2003. On water bears. The Florida Entomologist, Vol. 86, No. 2 , 134-137. Sayre, R.M. and L.K Brunson,. 1971. Microfauna of moss habitats. The American Biology

Teacher, Vol. 33, No.2 , 100-102+105. Schutte, J.A. 1977. Chromium in two corticolous lichens from Ohio and West Virginia

The Bryologist , Vol. 80, No. 2 (Summer, 1977), pp. 279-283.

Stubbs, C. S. 1989. Patterns of distribution and abundance of corticolous lichens and their invertebrate associates on Quercus rubra in Maine. The Bryologist, Vol. 92, No. 4, 453-460.

Walewski, J. 2007. Lichens of the north woods. Duluth: Kollath & Stensaas Publishing. Wolseley, P. A. and B. Aguirre-Hudson. 1997. Fire in tropical dry forests: corticolous lichens as

indicators of recent ecological changes in Thailand. Journal of Biogeography, 24: 345–362.

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http://www.sciencedirect.com/science/journal/02727714/23/2

Alewife (Alosa pseudoharengus) density as a predictor of open water utilization by walleye (Sander vitreus) in Otsego Lake, NY

B.E. Bowers1

INTRODUCTION

Walleye (Sander vitreus) are typically associated with shoals, drop offs, or in aquatic vegetation near shore (Foust and Haynes 2007), while in some lakes and reservoirs walleye make more use of pelagic waters (Ager 1976; Festa 1987; Palmer 2005, Byrne et al. 2009). Walleye have been stocked at a target rate of 80,000/year from 2000-2006 and 40,000/year since 2007. Here, walleye occupy rocky shoals, weedy littoral areas and epilimnetic pelagic waters, rarely occurring at depths below 15m (Stich et al. 2008, Byrne et al. 2009, Potter et al. 2010). Alewife (Alosa pseudoharengus) were first documented in Otsego Lake in 1986 (Foster 1990) and were dominant by the early 1990s (Harman et al. 2002). They are efficient epilimnetic planktivores that demonstrate diel patterns in vertical migration and schooling behavior (Appenzeller and Legget 1992; Luecke and Wurtsbaugh 1993). Habitat utilizations during summer stratification indicate spatial overlap between walleye and alewife.

While walleye habitat utilization has been studied in Otsego Lake, the factors contributing to their open water habitat selection are unknown. In Otsego Lake all walleye with prey in their stomachs fed on alewives; in a study by Cornwell (2005) 65% of walleye stomachs contained alewife, while the remaining 35% were empty. In Lake Erie walleye were documented as changing prey selection during times of the year when certain species are more abundant, selecting alewives during the fall (Parsons 1971). Following the introduction and establishment of alewife to Lake Huron in 1988, walleye preyed on alewife, corresponding with increases in weight and body conditions of various walleye year classes (Cade et al. 2008). Porath (2003) found the introduction of alewife increased the body condition of walleye within Lake Mcconaughy, indicating walleye were foraging for alewife. It is currently hypothesized that walleye occupy open-water areas of Otsego Lake in order to forage on alewife.

This study sought to assess the spatial overlap of alewives and walleye in the open waters of Otsego Lake using hydroacoustic fisheries surveys. From these surveys, alewife and walleye densities were estimated and targets corresponding to walleye were identified in order to evaluate alewife density at increasing distance from walleye targets.

METHODS

The acoustic data analyzed for this study were collected on 17 October 2007 (Brooking

and Cornwell 2008). Data were collected using BioSonics DTX echosounder with a 123 kHz, 7.8o beam-width transducer mounted at a depth of 0.5 meter (Brooking and Cornwell 2008). A percid gill net survey was conducted on the 18, 19 and 20 of September 2007 by the New York State Department of Environmental Conservation on Otsego Lake (McBride, unpublished). Data

1 OCCA Harman Internship, summer 2011. Present affiliation: Plymouth State University, Plymouth, NH.

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from this survey were used to estimate the percentage of predator targets in the pelagic water that were most likely to be walleye.

Hydroacoustic data were analyzed using Sonar5-Pro post processing system (Balk and

Lindem 2007). The surface exclusion zone was established from the surface to 2.5m to eliminate data from the transducer’s near-field and surface noise. The bottom boundary included a margin of approximately 0.5 m above the bottom to avoid inclusion of bottom echoes in abundance estimates. Echograms were visually inspected to remove bad data regions and echoes from targets other than fish. Potential walleye targets occurring at depths between 2.5 and 15m were analyzed; shallow areas less than 15m in total depth were excluded to avoid non-walleye predator targets. Fish density (#/ha) was calculated using the echo counting method in Sonar5 (Balk and Lindem 2007) based on a minimum target strength threshold of -61dB. Abundance estimates were determined for predator-sized (TS >-37 dB) and prey-sized (TS -61dB to -37dB) targets (Brooking and Rudstam 2009). The September 2007 NYSDEC percid gill net survey of Otsego Lake provided ground truthing of acoustic data and indicated that 95% of the predator targets can be assumed to be walleye. The TS range used to estimate alewife abundance was based on target strength data from caged alewives; 99% of the TS measurements were between -61 and -37 db (Brooking and Rudstam 2009). The acoustic survey was analyzed in various ways to investigate the relationships between prey density and walleye presence/absence, walleye abundance, and distance from a walleye; each of these is described below.

Walleye presence/absence and prey density: The survey was divided into segments 100 pings in length (~58 meters); each segment was analyzed twice, using the TS thresholds for predators to identify individual predator targets as well as the TS thresholds associated with alewife, to determine prey density. Adult alewife density (TS -51 to -43dB) was estimated in each 100-ping segment; average density was calculated for two categories: segments containing a predator target (assumed to be a walleye) and segments from which predators were absent. A total of 11 segments contained prey/alewife densities in the presence of walleye and 202 segments contained prey/alewife densities absent of walleye. Average prey density in the absence of walleye targets was based on 11 randomly-selected 60-m/100-ping segments from the 202 that did not contain walleye targets. Walleye abundance and prey density: The survey was divided into segments 60m in length (~100 pings); each segment was analyzed twice, using the TS thresholds for predators to identify individual predator targets as well as the TS thresholds associated with alewife, to determine prey density. Each segment was assigned to one of three categories depending on walleye abundance (multiple walleye present, single walleye present, no walleye present). The average alewife density for each category was calculated; a total of 2 segments contained multiple walleye, 7 segments contained a single walleye and 202 segments contained no walleye.

Distance from walleye and prey density: Predator targets (> -37 dB) were located. Alewife density was calculated in 20m increments from each predator target to 100m, for a total of 5 density estimates. The average density for each distance increment (+/-20m, +/-40m, +/-60m, +/-80m, +/-100m) was calculated for the 11 identified predator targets. The density estimates for each increasing distance increment include areas analyzed in the previous, and so presents an average over the entire area rather than for a discrete distance range.

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RESULTS

Higher alewife density was associated with the presence of walleye in Otsego Lake (Figure 1&2). Large portions of the limnetic zone of Otsego Lake contained no predator targets and lower prey densities. Segments of the hydroacoustic survey where walleye were present had an adult alewife density of 712 fish per hectare, while those where no walleye were present had an adult alewife density of 392 fish per hectare (Figure 1). Adult alewife density in the presence and absence of walleye were not significantly different (T-test >.05).

Figure 1. Adult alewife density in the presence or absence of a predator in 60-meter segments of the limnetic zone of Otsego Lake, 17 October 2007. Bars indicate calculated standard error (SE).

Alewife density was highest in segments containing multiple walleye and lowest in those where walleye were absent (Figure 2). Sixty-meter segments with multiple walleye had a prey density of 1163/ha, those with a single walleye had 930/ha and those where walleye were absent had only 561/ha (Figure 2). Prey density in the presence of multiple walleye (1083 fish/ha) and absence of walleye (561 fish/ha) were significantly different (T-test <.05). Note: the data for “Walleye Absent” and “No Walleye” in the analyses of walleye presence vs. absence and walleye abundance were derived from different groups of segments randomly-selected from the pool of 202.

Figure 2. Prey density versus walleye abundance in 60-meter segments of the limnetic zone of Otsego Lake, 17 October 2007. Data were inaccessible for calculation of standard error.

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Figure 3 illustrates average prey density at distance from a predator target; on average, alewife density was greatest within 20m of a predator target and decreased slightly with the inclusion areas at increasing distance (Figure 3). Prey density decreased by 143 fish/ha from the nearest to the farthest distance from a walleye target.

Figure 3. Prey density at distance intervals from walleye targets in the limnetic zone of Otsego Lake, 17 October 2007. Bars indicate calculated standard error (SE)

DISCUSSION

Walleye inhabit open water regions of Otsego Lake and tend to be located in areas having above average alewife (prey) density, identifying the spatial overlap of alewife and walleye and its potential tie to forage potential for walleye. Higher alewife density corresponds with segments containing multiple walleye. Average adult alewife density decreases with increasing distance from a walleye target (Figure 3). However, the difference in density from the shortest to longest distance increment is less than the error associated with the density estimate. Use of discrete distance intervals may provide a better assessment of alewife density in proximity to walleye. Past diet studies of Otsego Lake walleye (in 2002 and 2007) have found that alewife are by far their preferred prey; 97% of stomachs with food items contained at least one alewife (Cornwell and McBride 2008). This dietary information, along with the density relationships documented in this study, indicate that alewife are likely a factor in the location of walleye, specifically those found in open water regions of Otsego Lake.

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REFERENCES

Ager, L.M. 1976. A biotelemetry study of the movement of walleye in Center Hill Reservoir, Tennessee. Proceedings of the Annual Conference of the Southeastern Association of Fish and Wildlife Agencies. 30:311-323

Appenzeller, A. R., and Leggett, W. C. 1992. Bias in hydroacoustic estimates of fish abundance due to acoustic shadowing: evidence from day–night surveys of vertically migrating fish. Canadian Journal of Fisheries and Aquatic Sciences, 49: 2179–2189. Balk, H. and T. Lindem. 2007. Sonar4 and Sonar5 post processing systems, operator manual

version 5.9.7, 420p. Lindem Data Acquisition Humleveien 4b. 0870 Oslo Norway. Brooking, T.E. and M.D. Cornwell. 2008. Hydroacoustic surveys of Otsego Lake, 2007. In 40th

Ann. Rept. (2007). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Brooking, T.E. and L.G. Rudstam. 2009. Hydroacoustic target strength distributions of alewives in a net-cage compared with field surveys: deciphering target strength distributions and effect on density estimates. Transactions of the American Fisheries Society.133(3):471- 486

Byrne J.M., D.S. Stich, and J.R. Foster. 2009. Diel movements and habitat utilization of walleye

(Sander vitreus) in Otsego Lake. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Cade, B., Terrel, J., & Porath, M. 2008. Estimating fish body condition with quantile regression. North American Jorunal of Fisheries Management, 28(2), 349-359.

Cornwell, M.D. 2005. Re-introduction of Walleye in Otsego Lake: Re-establishing a fishery and

subsequent influences of a top down predator. Occasional Paper No. 40. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M.D. and N.D. McBride. 2008. Walleye (Sander vitreus) reintroduction update: walleye stocking, gill netting and diet analysis 2007. In 40th Ann. Rept. (2007). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Festa, P.J., J.L. Forney, and R.T. Colesente. 1987. Walleye management in New York State. NYSDEC Bureau of Fisheries. 104p.

Foster, J.R. 1990. Introduction of the alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1989). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Foust, J.C., and J.M. Haynes. 2007. Failure of walleye recruitment in a lake with little suitable spawning habitat is probably exacerbated by restricted home ranges. Journal of

Freshwater Ecology. 22 (2): 297-304.

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Harman, W.N., M.F. Albright, and D.M. Warner. 2002. Trophic changes in Otsego Lake, NY followingthe introduction of the alewife (Alosa pseudoharengus). Lake and Reservoir Management. 18(3):215-226.

Luecke, C. and W.A. Wurtsbaugh. 1993. Effects of moon and daylight on hydroacoustic

estimates of pelagic fish abundance. Transactions of the American Fisheries Society. 122: 112-120.

Palmer, G., Murphy, B., & Hallerman, E. 2005. Movements of walleyes in claytorlake and the upper new river, virgina, indicate distinct lake and river populations. North American Journal of Fisheries Management, 25(4), 1448-1455.

Parsons, J.W. Selective food preferences of walleye of 1959 year class in Lake Erie. Transactions of the American Fisheries Society. 100.3 (1971): 474-85. Potter, J., Byrne, J, Stich, D. & Foster, J. ( 2010). Walleye (Sander vitreus) seasonal activity and

habitat utilization in Otsego Lake, New York. In 41st Ann. Rept (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Porath, M.T., and E. Peteres. 1997. Walleye prey selection in Lake McConaughy, Nebraska: A comparison between stomach content analysis and feeding experiments. Journal of Freshwater Ecology.12(4): 511-20. Stich, D.S., B. Decker, J. Lydon, J. Byrne, J.R. Foster. 2008. Summer, diel habitat utilization

of walleye in Otsego Lake, NY. In 40th Ann. Rept. (2007). SUNY Oneonta Biol. Fld. Stat., SUNY Oneonta.

Warner, D.M., L.G. Rudstam and R.A. Klumb, In situ target strength of alewives in freshwater. Trans. Am. Fish. Soc., 131 (2002), pp. 212-223.

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Summer 2011 trap net monitoring of fish communities utilizing the weedy littoral zone at Rat Cove and rocky littoral zone Brookwood Point, Otsego Lake

B. P. German1

INTRODUCTION

This study was a continuation of yearly monitoring of the littoral fishes of Otsego Lake. The long term goal of the study is to assess the littoral fish community and determine population dynamics of species utilizing littoral habitats. Rat Cove has been studied since 1979 (MacWatters 1980) and Brookwood Point since 2002 (Wayman 2003). Littoral habitats of sizeable lakes such as Otsego Lake are essential, providing spawning and nursery habitats for many species of fish. The illegal introduction of alewife (Alosa pseudoharengus) in 1986 (Foster 1990) altered the trophic balance and physical/chemical characteristic of Otsego Lake, due to the species’ opportunistic behavior and over effectiveness in grazing the lakes’ zooplanktonic community (Harman 2002). Alewives are efficient, opportunistic, epilimnetic planktivores that feed on microcrustaceans, insects, ichthyoplankton, zooplankton and their own eggs (Cornwell 2005). Long term monitoring of littoral fishes helps to assess the effect alewives have on the lakes fish communities, as well as alewife abundance and spawning activity. Additionally this study provides useful long term data on non-alewife species.

In order to mitigate the detrimental effects the alewife have imposed on the lakes’ ecosystem, predatory walleye (Sander vitreus) have been re-established through stocking beginning in 2000. During summer stratification, alewife utilize only the top layer of water (the epilimnion), resulting in a spatial separation between them and the cold water predators of Otsego Lake. This in turn leaves the alewife free of most predators, able to reproduce and feed with nothing keeping their population in check. Walleye have been known to forage in the epilimnion, so during summer stratification alewife would be ideal prey. This study continues to document littoral fish communities that could provide insight into changes occurring in Otsego Lake.

1 Robert C. MacWatters Internship in the Aquatic Sciences, summer 2011. Present affiliation: Department of Fisheries and Wildlife Technology, SUNY Agriculture and Technical College, Cobleskill, NY.

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METHODS & MATERIALS

Winged Indiana trap nets with a single throat were set out Monday through Friday and checked daily, at both Rat Cove and Brookwood Point (Figure 1) from 24 May to 29 July. At Rat Cove the trap was deployed perpendicular to the north shore and at Brookwood Point the trap was deployed due east from the middle of the point. The catch was transferred from the nets into totes, all metrics were taken on site and the fish were promptly returned to the water. Each fish was identified, weighed in grams, and measured (mm).

Figure 1. Bathymetric contour map of Otsego Lake, NY. Trap nets were set perpendicular to the shore at Brookwood Point and Rat Cove.


The overall mean catch per week at both Rat Cove and Brookwood Point increased dramatically between 2005 and 2011 (Tables 1 and 2). There are several factors that could be the cause of this abrupt change. The first factor that likely influenced the 2011 number was the utilization of brand new nets for the 2011 season. Although the nets were the same general design used in previous years (Indiana style traps), the new nets have wings which appear to improve catch rate. Additionally, the older nets used earlier were in regular need of repair. Even with extensive repairs to the old nets, it is evident that new functional equipment improved catch rates.

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Table 1. Mean weekly catch at Rat Cove and catch contributed by each species, 2000-2011 (modified from Bowers 2010).

Species 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Alewife 120 68 8 45 2 <1 0 3 1 <1 <1 <1 Golden Shiner <1 <1 <1 <1 <1 <1 0 0 <1 <1 <1 <1 Pumpkinseed 10 21 15 33 13 5 2 2 4 5 5 16 Blue Gill 2 3 4 2 2 1 <1 3 6 7 5 7 Redbreast Sunfish <1 <1 <1 <1 <1 <1 0 0 <1 <1 0 <1 Rock Bass 2 2 4 <1 2 <1 <1 <1 <1 <1 1 2 Largemouth Bass <1 <1 <1 <1 <1 <1 0 <1 <1 <1 <1 <1 Chain Pickerel <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 Atlantic Salmon 0 <1 0 <1 0 0 0 0 0 0 0 0 Yellow Perch 3 <1 1 <1 1 <1 <1 <1 <1 0 <1 4 White Sucker 1 <1 1 <1 2 <1 <1 0 0 0 <1 <1 Common Carp <1 <1 <1 <1 <1 <1 <1 0 0 0 0 <1 Brown Bullhead 2 <1 6 3 2 <1 0 0 0 <1 <1 <1 Spottail Shiner 0 0 <1 0 0 0 0 <1 0 0 0 0 Smallmouth Bass 0 0 <1 0 0 0 0 0 0 0 0 0 Emerald Shiner 0 0 0 0 <1 0 0 0 0 0 0 <1 European Rudd <1 0 <1 <1 <1 0 <1 0 <1 <1 1 <1 Common Shiner 0 0 0 0 0 0 0 0 0 0 0 <1 Walleye 0 0 0 0 0 0 0 0 0 0 0 <1 Total 141 96 41 87 25 9 5 11 14 15 14 35

Table 2. Mean weekly catch at Brookwood Point and catch contributed by each species, 2000-2011 (modified from Bowers 2010).

Species 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011Alewife 224 137 77 95 13 6 1 5 <1 <1 1 0 Golden Shiner <1 <1 1 2 2 <1 <1 0 0 0 <1 <1 Pumpkinseed 3 7 12 13 12 1 <1 <1 2 2 1 10 Blue Gill 7 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 15 Redbreast Sunfish <1 0 <1 <1 <1 <1 <1 <1 0 <1 <1 4 Rock Bass 8 4 4 4 3 1 <1 <1 <1 2 2 14 Largemouth Bass <1 <1 <1 <1 0 <1 0 0 <1 <1 0 <1 Chain Pickerel <1 0 <1 <1 <1 <1 0 <1 <1 0 0 <1 Atlantic Salmon 0 <1 0 0 0 <1 0 0 0 0 <1 0 Yellow Perch 2 <1 <1 0 <1 <1 <1 0 <1 <1 0 1 Walleye 0 0 0 <1 0 0 0 0 0 <1 0 <1 White Sucker 5 0 2 <1 <1 <1 <1 0 0 0 <1 <1 Common Carp 2 <1 <1 <1 <1 0 <1 0 0 0 0 0 Bluntnose Minnow <1 0 0 0 0 <1 0 0 0 0 0 0 Brown Bullhead 7 0 <1 4 4 0 <1 0 0 0 0 <1 Spottail Shiner 0 <1 0 0 0 0 0 <1 0 0 <1 3 Smallmouth Bass 0 0 0 <1 <1 0 0 0 <1 0 <1 <1 European Rudd 0 <1 0 <1 <1 0 <1 0 <1 0 0 0 Common Shiner 0 0 0 0 0 <1 0 0 0 0 0 0 Emerald Shiner 0 0 0 0 0 0 0 0 0 0 0 <1 Lake Trout 0 0 0 0 0 0 0 0 0 0 0 <1 Total 259 152 101 121 37 10 4 8 4 5 6 50

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A total of 85 fish were caught per week at Rat Cove and Brookwood Point, with only a single alewife harvested in 36 days of sampling (Figure 2). The alewife was caught on 21 June and represents the lowest catch for this species in over 10 years. It should be noted that mean alewife size, at 177mm, was the largest since 2000 (Figure 3). However this mean size is drawn from the single individual, this means the increase is unreliable.

Figure 2. Mean weekly alewife catch in Rat Cove and Brookwood Point trap nets 2000-2011. (Modified from Bowers 2010).

Figure 3. Mean total length of alewife captured during summer trap netting 2000-2011. (Modified from Bowers 2010). The 2011 alewife catch represents a single individual.

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DISCUSSION

A total of 861 fish were caught between Rat Cove and Brookwood Point over the 2011 sampling season. A total of 354 fish were caught in a weedy littoral habitat represented by Rat Cove, demonstrating an increase in nearly all species captured. In addition, 2011 also produced the first year in which walleye were captured in Rat Cove (n=6). Brookwood Point represents a rocky shoal that caught a total of 507 fish with the dominate fish being bluegill and rockbass. This is a remarkable increase from the 2010 season when only 50 fish were captured in total. Lake trout were recorded for the first time in over 10 years of sampling, the individual being small (56mm) indicating successful spawning of lake trout.

CONCLUSION

Otsego Lake has seen an increase in clarity, potentially due to two separate factors, first being the introduction and establishment of zebra mussels (Dreissena polymorpha) first documented in 2007 (Harman 2008). Zebra mussels have been documented to cause ecological changes, including increased water clarity, following a successful introduction to a water body (D’Itri 1996). In 2009 (Gillespie 2010) and 2010 (Albright and Leonardo 2011), cladoceran zooplankton mean size and Daphnia sp. abundance had increased, correlating with increased water clarity. (Transparencies through 2011 were even greater (Waterfield and Albright 2012)). This change in the plankton community is likely due to reduced grazing by alewife. Reduced competition would allow for increased length of the (fewer) remaining alewife (Figure 3). Future summer trap netting surveys are recommended in evaluating the shifts in population dynamics of littoral zone fishes, and the continued interactions with non-native alewife.

REFERENCES

Albright, M.F. and M. Leonardo. 2011. A surveyu of Otsego Lake’s zooplankton, summer 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. and H.A. Waterfield. 2012. Otsego Lake water quality monitoring, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneta.

Bowers, B. 2011. Summer 2010 trap net monitoring of littoral fish communities at Rat Cove & Brookwood Point, Otsego Lake. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M.D. 2005. Re-introduction of walleye to Otsego Lake: Re-establishing a fishery and subsequent influences of a top predator. Occas. pap. #40, SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

D'Itri, Frank. Zebra Mussels and Aquatic Nuisances Species. Chelsea, NY: Ann Arbor Press, 1996. 161-163. Print.

150

Foster, J.R. 1990. Introduction of alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1989). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Gillespie, S. 2010. A survey of Otsego Lake’s zooplankton community, summer 2009. In 42nd Ann. Rept (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N, M.F. Albright and D.M. Warner. 2007. Trophic changes in Otsego lake, NY, following the introduction of alewife (Alosa psuedoharengus). Lake and Reserv. Manage. 18(3):215-226.

Harman, W.N. 2008. Introduction. In 40th Ann. Rept. (2007). SUNY Oneonta Biol. Fld., SUNY Oneonta.

MacWaters, R. C. 1980. The fishes of Otsego Lake. Occas. Paper #7. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Wayman, K. 2003. Rat Cove and Brookwood Point littoral fish survey, 2002. In 35th Ann. Rept. (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

151

Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 20111

Holly A. Waterfield2 and Mark Cornwell

3

INTRODUCTION

Hydroacoustic surveys were conducted in June and November 2011 to estimate pelagic

fish abundance in Otsego Lake (Otsego County, NY). Following their introduction in 1986,

alewife (Alosa pseudoharengus) quickly became the most abundant forage fish in Otsego Lake

(Foster 1990) and had major impacts on trophic relationships, chlorophyll a, water clarity, and

hypolimnetic oxygen depletion rates (Warner 1999, Harman et al. 2002). Walleye (Sander

vitreus) stocking resumed in 2000 (previously stocked through 1934) to establish a recreational

fishery while at the same time introducing a predator which would potentially control the alewife

population. The acoustic surveys reported on here are part of an ongoing effort to document

changes in the pelagic fish community and lake trophic condition. Comparisons are made to the

results of past hydroacoustic surveys (1996 to 2007) which were summarized by Brooking and

Cornwell (2008).

METHODS

Acoustic surveys were conducted on the nights of 06 June and 08 November 2011,

beginning at least 1 hour after dark. Both surveys were conducted from north to south following

a zig-zag pattern from shore to shore (Figure 1). Approximately east-west transects were

connected with a diagonal “zig” to yield two sets of parallel transects for additional analysis of

methods and statistical approaches. Down-looking data were collected using a BioSonics DtX

echosounder with a 123kHz 7.5o beam transducer; data collection settings for each survey are

listed in Table 1. Performance of each transducer was checked against a standard tungsten

carbide sphere; no calibration offset was used.

Hydroacoustic data were analyzed using the Sonar5-Pro post processing system (Sonar5)

following conversion of the raw acoustic files to Sonar5-compatible formats (Balk and Lindem

2007). Surface and bottom exclusion zones were established on each echogram to isolate open

water areas for analysis. The surface exclusion zone was established from the surface to 2m to

eliminate data from the transducer’s near-field and surface noise. The bottom boundary included

a margin of approximately 0.5 m above the actual detected bottom to avoid inclusion of bottom

echoes in abundance estimates. Echograms were visually inspected to remove echoes from

targets other than fish (i.e., submerged vegetation). Passive noise, calculated from passive

listening data collected prior to each survey, was subtracted from all files before analysis. Fish

density (#/ha) was calculated using Sv/TS scaling method in Sonar5 (Balk and Lindem 2007)

based on a minimum in situ target strength threshold of -61dB for the fall survey and -55 dB for

the spring survey. The TS threshold used in past analyses was -61dB; the higher threshold of -55

1 Made possible by 2007 NSF grant entitled Acquisition of hydroacoustic and associated instrumentation for

fisheries research (DBI: 0722764). 2 Research Support Specialist, SUNY Oneonta Biological Field Station, Cooperstown, NY.

3 Assistant Professor, SUNY Cobleskill Department of Fisheries and Wildlife, Cobleskill, NY.

152

dB was used to exclude an abundance of small targets in the alewife abundance estimate (Figure

2). Target strengths of -61 to -55 dB have been associated with alewife ranging in length from

1.5 to 2.0 cm (Warner 2002), a size class that would not be present at the time of the June 2011

survey. Each transect was divided into layers for analysis based on areas of relatively

homogeneous fish distribution. Abundance estimates were determined for predator-sized (TS >-

35 dB) and prey-sized (TS -61dB or-55dB to -34dB) targets in each layer. Total fish abundance

and predator abundance was based on the summation of the estimates for all layers; alewife

abundance was based on estimates from the surface through the bottom of the metalimnion (layer

1 in June, layers 1+2 in November). Layers used in the analysis of the June survey were 2-15m

and 15m+; the November survey was analyzed in three layers: 2-15m, 15-30m, and 30m

+.

Table 1. Data collection settings for 06 June and 08 November 2011 acoustic surveys conducted

on Otsego Lake, NY.

Survey Date

Number of

transects

Downlooking

Frequency (kHz)

Average Survey

Speed (m/s)

Pulse Duration

(ms)

Ping Rate

(pps)

06/06/2011 8 123 1.6 0.4 4

11/08/2011 10 123 1.6 0.4 3

Figure 1. Bathymetric map of Otsego Lake, NY with acoustic transects surveyed 06 June 2011

(left) and 08 November 2011 (right).

153

Variable small mesh experimental gill nets were set concurrent with each survey. Each

net was composed of seven 3-meter wide panels of different mesh sizes (6.2, 8, 10, 12.5, 15,

18.7, and 25mm bar mesh). Nets were 21 meters long by 6 meters deep and set from the surface

downward or from the bottom upward. Three nets were set on the nights of 06 June and 06

November 2011 for about 12 hours each, set just before dark, pulled early morning. Fish were

tallied by panel and vertical position (top, middle, bottom) in the net. Species, length, and

weight were recorded for all fish caught.


Lake-wide acoustic fish density in June was estimated to be 61 fish/ha (95% CI +/- 38

fish/ha) based on the 8 transects (Table 2). Fish density estimates varied among transects

ranging from 15 fish/ha transects to 143 fish/ha (Table 2); this range of density estimates is less

than typically observed in the past (Brooking and Cornwell 2008, Waterfield and Cornwell

2010). This is the lowest density estimate since spring surveys began in 2004 (Table 3;

Brooking and Cornwell 2008). Figure 2 is a plot of acoustic targets by target strength (dB)

versus their depth (m) in the water column. A grouping of targets having a range in TS typically

associated with alewife was observed below 30m (Figure 2); these targets do not contribute to

the alewife abundance estimate, as they are in deeper waters.

Gill nets caught 9 alewife, all located in the surface net (fishing 0 to 6m); 78% of these

were located in the top 2 meters, outside of the acoustically-surveyed portion of the water

column. If this vertical distribution is representative of lake-wide alewife distribution, it is

possible that the acoustic density estimate does not include at least 75% of alewife in the water

column.

Table 2. Fish abundance estimates of alewife and predator-sized targets for transects surveyed

06 June 2011, including lake-wide mean, standard error (SE) and 95% confidence intervals.

Fish Density (fish/ha)

Transect Alewife Predator

1 35 5

2 15 8

3 22 27

4 143 115

5 100 55

6 59 37

7 86 23

8 30 26

Mean 61 2.7

S.E. 15.86 1

95% CI 38 2.5

154

Table 3. Alewife abundance estimates (fish/ha) for spring surveys conducted between 2004 and

2011.

Year

2004

2005

2006

2007

2010

2011

Figure 2. Target strength (TSc in decibels) versus depth (range in meters) of all acoustic targets

greater than -61dB identified in the June (left) and November (right) 2011 surveys

Total acoustic fish abundance in November was estimated to be

58 fish/ha) across 8 transects (Table 4). This estimate is the lowest reported since acoustic

surveys began on Otsego Lake in 1996 (Table 5).

observed at depths shallower than 1

was observed around or below 35m depth and having

associated with alewife (Figure 2

abundance. A cluster of predator

depth, a depth range typically occupied by walleye (Potter et al. 2010). Corresponding gill nets

caught no alewife in any net, though lake trout were caught in surface (0

nets.

Alewife abundance estimates (fish/ha) for spring surveys conducted between 2004 and

Fish/ha # transects stdev 95% CI

907 9 175 114

236 9 214 137

2522 10 1463 907

1330 9 611 399

105 14 236 137

61 8 49 38


1dB identified in the June (left) and November (right) 2011 surveys

Total acoustic fish abundance in November was estimated to be 57 fish/ha (95% CI +/

(Table 4). This estimate is the lowest reported since acoustic

surveys began on Otsego Lake in 1996 (Table 5). The majority of acoustic targets were

r than 15m (Figure 2). As observed in June, a grouping of targets

was observed around or below 35m depth and having in situ TS values within the range typically

2); these targets did not contribute to the estimate of alewife

A cluster of predator-size targets is seen in both transect sets between 20 to 3


, though lake trout were caught in surface (0-6m) and deep (8

Alewife abundance estimates (fish/ha) for spring surveys conducted between 2004 and


1dB identified in the June (left) and November (right) 2011 surveys.

fish/ha (95% CI +/-

(Table 4). This estimate is the lowest reported since acoustic

rgets were

, a grouping of targets

TS values within the range typically

t contribute to the estimate of alewife

size targets is seen in both transect sets between 20 to 30m


6m) and deep (8-14m)

155

Table 4. Fish abundance estimates of alewife and predator-sized targets for transects surveyed

08 November 2011, including lake-wide mean, standard error (SE) and 95% confidence

intervals.

Fish Density (fish/ha)

Transect Alewife Predator

1 49 23.7

2 7 0.0

3 278 5.6

4 78 4.7

5 0 0.6

6 9 1.7

7 2 2.3

8 20 6.4

9 18 0.0

10 18 0.0

11 151 0.0

Mean 57 4.1

S.E. 25.8 2.1

95% CI 57.6 4.7

Table 5. Abundance estimates (fish/ha) from fall acoustic surveys conducted between 1996 and

2011. Modified from Brooking and Cornwell (2008).

Fall Alewife Abundance Fall Predator Abundance

Year #/ha # transects stdev 95% CI #/ha # transects stdev 95% CI

1996 5170 7 1434 1063 7.5 7 4.2 3.1

1997 2053 9 798 521 3.3 9 3.4 2.2

2000 1382 8 925 774

2001 8562 9 3811 2490 35.2 9 13.9 9.1

2002 10901 16 4886 2394 15.2 16 10.7 5.2

2003 3851 16 2901 1421 1.2 16 1.5 0.7

2004 2418 9 1571 1026 3.5 9 4.7 3.1

2005 9562 9 3555 2322 8.6 9 8.8 5.7

2006 1631 7 2713 2010 19.4 7 25.6 19

2007 3921 11 2524 1492 6.5 11 5.7 3.4

2009 369 18 334 166 6.6 18 6.4 3.17

2010 275 16 464 247 2.9 16 4.3 2.3

2011 57 11 85 58 4.1 11 6.9 4.7

156

2011 results show a continuation of recent decreases in both spring and fall alewife

abundance (Tables 3 and 5), even when considering the confidence intervals and their reflection

of the high degree of variability among transect density estimates. This decrease in estimated

alewife abundance is corroborated by relatively low gill net catch for both surveys, as well as

results documented in other ongoing studies, including increased mean alewife size concurrent

with decreased trap net catch rate (Potter 2010) (in the summer of 2011 only a single alewife was

caught (German 2012)) and the prevalence of alewife in stomachs of captured walleye (McBride

and Cornwell 2008). Other trophic indicators measured in and calculated for Otsego Lake also

point toward changes that are directly related to the decreased alewife population including mean

size of cladoceran zooplankton (Albright and Zaengle 2012) and aerial hypolimnetic oxygen

depletion rates (Waterfield and Albright 2012).

REFERENCES

Balk, H. and T. Lindem. 2007. Sonar4 and Sonar5 post processing systems, operator manual

version 5.9.7, 420p. Lindem Data Acquisition Humleveien 4b. 0870 Oslo Norway.

Bowers, B.E. and H.A. Waterfield. 2011. Investigating walleye (Sander vitreus) behavior and

optimal forage theory in Otsego Lake, New York. In 43rd

Ann. Rept. (2010). SUNY

Oneonta Biol. Fld. Sta., SUNY Oneonta.

Brooking, T.E. and M.D. Cornwell. 2008. Hydroacoustic surveys of Otsego Lake, 2007. In 40th

Ann Rept. (2007). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M.D. and N.D. McBride. 2009. Walleye (Sander vitreus) reintroduction update:

Walleye stocking, gill netting 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld.

Sta., SUNY Oneonta.

German, B.P. 2012. Summer 2011 trap net monitoring of fish communities utilizing the weedy

littoral zone at Rat Cove and rocky littoral zone Brookwood Point, Otsego Lake. In 44th


Foster, J.R. 1990. Introduction of the alewife (Alosa pseudoharengus) into Otsego Lake. In 22nd


Harman, W.N., M.F. Albright, and D.M. Warner. 2002. Trophic changes in Otsego Lake, NY

following the introduction of the alewife (Alosa psuedoharengus). Lake and Reservoir

Management. 18(3)215-226

Potter, J. 2010. Littoral fish community survey of Rat Cove & Brookwood Point, summer 2009.

In 42nd


Warner, D.M. 1999. Alewives in Otsego Lake, NY: a comparison of their direct and indirect

mechanisms of impact on transparency and chlorophyll a. Occas. Pap. No. 32. SUNY

Oneonta Biol. Fld. Sta., SUNY Oneonta.

157

An update on the dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria) in the Goodyear Swamp Sanctuary, summer 2011

M.F. Albright

INTRODUCTION

The distribution and effectiveness of Galerucella spp. populations as a biocontrol agent of purple loosestrife (Lythrum salicaria) were monitored within Goodyear Swamp Sanctuary as part of an ongoing monitoring regime that began in 1997. Annual spring monitoring of the impact of Galerucella spp. on purple loosestrife is updated in this report. No fall survey was conducted due to the flooding caused by the hurricanes Irene and Lee. Details of the history of this study can be found in Albright et al. (2004). L. salicaria is an emergent semi-aquatic plant that was introduced into the United States from Eurasia in the early 19th century (Thomson 1987). It is an aggressive and highly adaptive invasive species which inhabits wetlands, flood plains, estuaries and irrigation systems. Once established, purple loosestrife often creates monospecific stands, displacing native species including cattails (Typha spp.), sedges (Carex spp.), bulrushes (Scirpus spp.), willows (Salix spp.) and horsetails (Equisetum spp.). Recent efforts, which include both chemical application and the use of biocontrol methods, have focused on controlling L. salicaria where stands impede well-diversified wetland communities (Thomson 1987). In June 1997, 50 adults each of Galerucella calmariensis and G. pusilla were introduced into Goodyear Swamp Sanctuary (N42°48.6’ W74°53.9), located at the northeastern end of Otsego Lake (Austin 1998). The beetles were initially released in cages from sites 1 and 2 (Figure 1). In 1998, sites 3-5 were introduced into the study in order to monitor the distribution of Galerucella over time to other stands of purple loosestrife (Austin 1999). Sampling sites were established to monitor the qualitative and quantitative effects of the beetles on purple loosestrife and also to examine the extent of any recovery by the native flora (Austin 1998). It was expected that these beetles would lessen the competitive ability of purple loosestrife by feeding upon their meristematic regions, resulting in defoliation, impaired growth, decreased seed production, and increased mortality (Blossey et al. 1994).

158

Figure 1. Map of Goodyear Swamp Sanctuary showing sampling sites. Sites 1 and 2 are 1997 Galerucella spp. stocking sites; sites 3-5 were established to evaluate the spread of Galerucella spp. within the Sanctuary over time.

METHODS

Spring monitoring was performed according to protocols established by Blossey et al. (1997). Observations of the insects and plants were made within the five 1m2 quadrats, marked by four visible stakes (Figure 1). Spring monitoring was completed on 27 May 2011. This first assessment is typically completed within 2-3 weeks after overwintering adults appear (Blossey 1997). Galerucella spp. abundance was estimated in each life stage (egg, larva, adult) according to the established abundance categories (Table 1). The number of stems of L. salicaria within each quadrat were counted, and the five tallest were measured. The percent cover of L. salicaria and the percent damage attributable to Galerucella spp. were both estimated according to established frequency categories. Fall monitoring was not completed due to flooding due to hurricane activity. Table 1. Categories prescribed by Blossey’s (1997) protocol for reporting abundance and frequency categories.

Abundance Categories Frequency Categories Number category range category mid point

0 1 0% A 0% 1-9 2 1-5% B 2.50%

10-49 3 5-25% C 15% 50-99 4 25-50% D 37.50%

100-499 5 50-75% E 62.50% 500-1000 6 75-100% F 87.50%

>1000 7 100% G 100%

159


All monitoring data are represented by abundance and frequency categories defined in Table 1. Changes between these frequency categories from year-to-year or plot-to-plot can represent a substantial change in abundance (Albright 2004) due to the broad ranges covered by each category. It should be noted that the actual number of L. salicaria stems are presented in the following results, while all other metrics are categorical. Variation in the number of stems between years or plots may not correspond with a shift in percent cover category, due to the above-stated lack of sensitivity that is inherent in a categorical classification scheme. Spring Monitoring (27 May 2011) No eggs of the Galerucella beetle were present in any of the quadrats (Figure 2). No larvae were found in any quadrat, as is consistent with past observations (Figure 3); spring sampling generally takes place prior to or during the laying of eggs. Quadrats 1 and 2 had adults at the Category 2 and 3 level, respectively (Figure 4).

1

2

3

4

5

6

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Abu

ndan

ce ca

tego

ry

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 2. Comparison of Galerucella spp. egg abundance from yearly spring samplings. Abundance categories taken from Table 1.

1

2

3

4

5

6

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Abu

ndan

ce ca

tego

ry


Figure 3. Comparison of Galerucella spp. larval abundance from yearly spring samplings. Abundance categories taken from Table 1.

160

1

2

3

4

5

6

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011Abu

ndan

ce ca

tego

ry


Figure 4. Comparison of Galerucella spp. adult abundance from yearly spring samplings. Abundance categories taken from Table 1.

Lythrum salicaria had as low an abundance of stems at the time of the 2011 spring monitoring than has been recorded (Figure 5). Estimated percent cover was also as low as has ever been recorded (Figure 6). That loosestrife which was in the quadrats was moderately damaged by herbivory (Figure 7).

0102030405060708090

100

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Num

ber o

f Ste

ms


Figure 5. Comparison of the number of purple loosestrife stems from yearly spring sampling observations.

161

010203040506070

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Freq

uenc

y C

ateg

ory

Mid

-poi

nt


Figure 6. Comparison of percent cover estimates by purple loosestrife from yearly spring samplings. Frequency category mid points derived from Table 1.

010203040506070

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Freq

uenc

y C

ateg

ory

Mid

-poi

nt


Figure 7. Comparison of percent damage estimates to purple loosestrife leaves from yearly spring samplings. Frequency category mid points derived from Table 1.

CONCLUSIONS

Spring monitoring indicated that L. salicaria was less abundant (based on percent cover and number of stems) than in any year since monitoring began in 1997. Galerucella spp. abundance was also low, undoubtedly due to the lack of L. salicaria. Observations related to the presence of Galerucella spp. at sites outside of Goodyear Swamp Sanctuary (i.e., Lydon 2008) indicate that the dispersal of Galerucella spp. is expanding from the original site and has indicated its potential effectiveness as a biological agent against the invasive.

REFERENCES

Albright, M.F., W.N. Harman. S.S. Fickbohm, H.A. Meehan, S. Groff and T. Austin. 2004. Recovery of native flora and behavior responses by Gallerucella spp. following biocontrol of purple loosestrife. Am. Midl. Nat. 152:248-254.

162

Austin, T. 1998. Biological control of purple loosestrife in Goodyear Swamp Sanctuary using Galerucella spp., summer 1997. In 30th Ann. Rept. (1997). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta. Austin, T. 1999. Biological control of purple loosestrife in Goodyear Swamp Sanctuary using Galerucella spp., summer 1998. In 31st Ann. Rept. (1998). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta. Blossey, B. 1997. Purple loosestrife monitoring protocol, 2nd draft. Unpublished document. Dept. of Natural Resources, Cornell University. Blossey, B., D. Schroeder, S.D. Hight and R.A. Malecki. 1994. Host specificity and environmental impact of two leaf beetles (Galerucella calmariensis and G. pusilla) for the biological control of purple loosestrife (Lythrum salicaria). Weed

Science. 42:134-140 Fagan, W.F., M.A. Lewis, M.G. Neubert, P. van den Driessche. 2002. Invasion theory and biological control. Ecology Letters 5(1) 148. Groff, S. 2001. Biological control of purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary using leaf-eating beetles (Galerucella spp.), summer 2000. In 34th

Annual Report (2000). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta. Lydon, J.C. 2008. Monitoring the dynamics of Galerucella spp. and purple loosestrife (Lythrum

salicaria) in the Goodyear Swamp Sanctuary and along the shorelines of Otsego, Weaver and Youngs Lakes, summer 2007). In 40th Ann. Rept. (2007). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Meehan, H.A. 2006. Biological control of purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary using leaf-eating beetles (Galerucella spp.), summer 2005. In 38th Annual Report (2005). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta. Rubenstein, M. 2010. Monitoring the dynamics of Galerucella spp. And purple loosestrife

(Lythrum salicaria) in the Goodyear Swamp Sanctuary, summer 2009. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Snyder, C.M. 2007. Monitoring the dynamics of Galerucella spp. and purple loosestrife

(Lythrum salicaria) in the Goodyear Swamp Sanctuary and along the Otsego Lake shoreline, summer 2006. In 39th Annual Report (2006). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Thompson, Daniel Q., R.L. Stuckey, E. B. Thompson. 1987. Spread, Impact, and Control of Purple Loosestrife (Lythrum salicaria) in North American Wetlands. U.S. Fish and Wildlife Service. 55 pages. Jamestown, ND: Northern Prairie Wildlife Research Center Online. http://www.npwrc.usgs.gov/resource/plants/loosstrf/loosstrf.htm (04JUN99).

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http://www.npwrc.usgs.gov/resource/plants/loosstrf/loosstrf.htm

Afton Lake water quality, nutrients and algae1

W.N. Harman, M.F. Albright and H.A. Waterfield

SAMPLING ACTIVITIES

Site visits to Afton Lake were made on 13 July and 7 October 2011. Water samples were collected over the deepest part of the lake from the surface to the bottom. These were analyzed for nutrients, important ions, algae groups, and algal abundance (See Tables below). Measurements were recorded on-site for temperature, dissolved oxygen, specific conductance, pH, chlorophylla and Secchi disk transparency (water clarity).

FINDINGS

Algal growth in Afton Lake appears to be limited by the availability of nitrogen; because of that there is an abundance of cyanobacteria (blue-green algae) which are able to “fix” atmospheric nitrogen. During our visits we observed three genera that are known to cause harmful algal blooms (HABs). This is typical in lakes that have experienced moderate levels of phosphorus loading from the watershed (i.e. livestock, septic system influx, sediment loading, etc.). In the present situation, phosphorus has been added to the lake system to the extent that nitrogen and phosphorus concentrations are no longer in balance with the requirements of a desirable algae community. The resulting noxious blooms cause the problems that have stimulated concerns; they can greatly reduce clarity, impose odor problems, and can create human and animal health risks even with passive contact and they provide little quality forage for zooplankton and other organisms.

To ultimately solve the problem, a reduction in phosphorus loading would need to be achieved to the point where phosphorus is again the nutrient controlling algal growth.

GOING FORWARD

Long-term Management: To get at the root cause of the algae problem, nutrient loading (especially phosphorus) must be addressed by the Afton Lake community, including those who live away from the shore within the watershed (which needs to be hydrologically defined). Generally, all land uses within the watershed should be assessed; in the case of Afton Lake, the dominant land uses contributing phosphorus are assumed to be residential development 1 This report was prepared for the Afton Lake Association by the BFS as part of a contractual agreement.

164

(including poorly functioning septic systems and fertilizers) and agriculture. The situation has progressed to the point that phosphorus is being released from the sediments during the summer. Without control of this internal source of phosphorus, reductions from the watershed alone will not be very effective in solving the problem. In-lake phosphorus inactivation, such as by aluminum sulfate, may be the best option to break the cycle of blue-green blooms.

Short-term management: There are a diversity of methods to control and prevent seasonal algal blooms; hypolimnetic aeration, water circulation and destratification, dilution and flushing, drawdown, various means of dredging, light limiting dyes, mechanical removal, selective water withdrawal, algaecides, phosphorus inactivation, sediment oxidation, settling agents (alum), and various biological control methods; enhanced grazing by zooplankton and fish, selective fish removal, additions of algal pathogens, competition and allelopathy, plantings for nutrient control, barley straw and others. Some are obviously inappropriate for your situation but several others could be considered after we find out enough to better understand the lake system.

Short-term Actions: As per our contract we will continue to monitor the situation during 2012 to determine if the 2011 bloom is likely to be repeated in the future. The collected data will then result in our providing a series of alternative actions you may take to meet your concerns.

RESULTS

Nitrogen compounds: The ratio of total nitrogen to total phosphorus in Afton Lake implies nitrogen limitation. Nitrate (NO3) is the main bioavailable form of nitrogen in lakes. That compound was near or below detection on all samples tested, indicating that all nitrogen available to the green algae is used as rapidly as possible. That indicates that a lack of nitrogen is limiting their growth enabling cyanobacteria to grow unimpeded by direct competition. Total nitrogen in the surface waters is primarily in organic forms (including living algal cells) (July TN = 0.8 mg/L; Oct TN = .39 mg/L). Elevated TN concentrations just off bottom (1.31-1.52 mg/L) are due to high ammonia levels (0.88 mg/L) resulting from the complete lack of oxygen there.

Phosphorus: Concentrations in Afton Lake are moderately high. This indicates that it is probably not the limiting factor for algal growth. Very high concentrations near the bottom (389 µg/L on 7 October) show that there is loading of phosphorus to the lake not only from sources in the watershed, but internally as well. This comes about when bottom waters loose oxygen and the bottom sediment releases phosphorus to the water above it.

Algae and Water Transparency: Secchi disk transparency was 0.5m (about 2 feet) at both site visits; chlorophylla concentration, a measure of algal pigments used to estimate algal abundance, varied from 0.8 – 26.2 µg/L in July, 0 – 235 µg/L in October. The upper values are well into a range that indicates eutrophic conditions. In July the algal community was dominated by Anabaena and Oscillatoria, both cyanobacteria. In October Aphanizomenon, another

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cyanobacterium, dominated. This provides the primary evidence in support of the conclusion that the lake is showing signs of eutrophication. Observations reported by members of the Afton Lake Association implied that more intensive blooms than we observed either date occurred earlier in the summer

Temperature and Dissolved Oxygen profiles indicate that Afton Lake experiences strong thermal stratification during the summer months, meaning that there is a warm surface layer floating on top of the cold deep water. This has major implications for the amount of dissolved oxygen in the water column – and in turn, for habitat available to fish and other aquatic organisms, and very importantly to internal nutrient cycling. On both sampling dates the entire water column below 7m (24 feet) was anoxic (essentially devoid of free oxygen), meaning that these depths do not provide habitat for fish or invertebrates (fish food organisms). These conditions also lead to internal phosphorus loading (the release of phosphorus from the bottom sediments) as previously discussed.

Suggestions: In addition to collecting data in 2012 as outlined in our contract agreement, we would like to provide a set of collection bottles and preservative for an agent of the lake association to collect surface lake samples at the onset of what appears to be any algal bloom. We feel that this might provide us some insight as to the conditions that precede, and perhaps trigger, the blooms. This might assist in future in-lake management activities to reduce blue-green blooms, should that ever be attempted.

ANALYSIS METHODS & RESULTS

Table 1. Methods used in the analysis of water samples collected from Afton Lake.

Parameter

Minimum Detection Level Method Reference

Total Phosphorus 4 µg/L Persulfate digestion followed by single reagent ascorbic acid

Liao and Marten 2001

Total Nitrogen 0.04 mg/L Cadmium reduction method following peroxodisulfate digestion

Ebina et al. 1983

Nitrate+nitrite-N 0.02 mg/L cadmium reduction method Pritzlaff 2003 Ammonia-N 0.02 mg/L Phenolate method Liao 2001 Alkalinity Titration to pH = 4.6 APHA 1989 Calcium EDTA titrimetric method APHA 1989 Chloride Mercuric nitrate titration APHA 1989

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Table 2. Physical measurements made on 12 July and 7 October 2011 at Afton Lake.

temperature ( oC)

dissolved oxygen (mg/L)

dissolved oxygen (% saturation) pH

specific conductivity (ms/cm)

oxidation-reduction potential (mV)

chlorophylla (µg/L) Depth

(m) 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011

0 27.10 16.23 10.83 9.60 136.1 97.8 9.70 8.93 0.155 0.133 59.4 88.7 5.8 16.41 26.00 16.24 12.31 9.57 151.2 97.4 9.90 8.42 0.136 0.134 58.1 96.5 10.4 12.92 21.50 16.23 7.39 9.54 84.0 97.2 8.30 8.29 0.124 0.133 119.8 102.8 8.1 13.23 16.10 16.23 7.25 9.48 73.8 96.6 8.10 8.21 0.116 0.134 140.5 107.5 2.4 12.14 11.20 16.22 6.26 9.49 57.5 96.7 7.70 8.16 0.111 0.133 152.4 111.1 1.3 11.45 7.90 15.67 3.68 5.41 31.5 54.8 7.50 7.03 0.114 0.129 160.5 -43.2 1.4 14.76 6.20 11.34 1.15 0.13 9.5 1.2 7.30 6.98 0.117 0.128 166.2 -113.6 0.8 20.57 5.30 7.63 0.15 0.06 1.3 0.5 7.10 7.00 0.122 0.140 -50.0 -140.2 7.2 132.78 5.00 6.31 0.06 0.05 0.5 0.4 7.00 6.96 0.124 0.144 -97.0 -170.0 4.2 234.99 4.90 5.63 0.10 0.11 0.4 0.9 6.90 6.95 0.125 0.144 -11.3 -171.9 3.1 100.6

10 4.80 5.20 0.02 0.06 0.2 0.5 6.80 6.96 0.126 0.146 -118.0 -166.2 5.8 58.711 4.70 5.01 0.00 0.07 0.0 0.6 6.80 6.96 0.127 0.147 -124.1 -162.4 7.1 37.512 4.60 4.88 0.00 0.09 0.0 0.7 6.80 6.98 0.128 0.147 -127.6 -159.5 8.4 26.413 4.50 4.70 0.00 0.17 0.0 1.3 6.70 7.01 0.130 0.150 -137.4 -158.8 10.1 19.614 4.40 4.65 0.00 0.14 0.0 1.1 6.70 7.04 0.131 0.151 -134.0 -154.3 12.1 24.615 4.40 4.62 0.00 0.18 0.0 1.5 6.70 7.08 0.133 0.154 -142.0 -148.3 14.0 20.116 4.40 4.59 0.00 0.27 0.0 2.2 6.70 7.14 0.134 0.155 -146.0 -141.3 15.4 19.317 4.40 4.62 0.00 0.54 0.0 4.4 6.70 7.07 0.135 0.163 -150.4 -117.8 26.2 0.3

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Table 3. Nutrient concentrations determined for water samples collected from Afton Lake on 12 July and 7 October 2011. BD indicates that the concentration was below detectable levels.

ammonia (mg/L)

nitrate+nitrite (mg/L)

total nitrogen (mg/L)

total phosphorus (µg/L)

Depth (m)

7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011 7/12/2011 10/7/2011

0 bd - 0.03 bd 0.81 0.38 51 21 16 0.88 - bd bd 1.31 1.52 76 389

REFERENCES


17th ed. American Public Health Association. Washington, DC. Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total

phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1721-1726. Liao, N. and S. Marten. 2001. Determination of total phosphorous by flow injection analysis

colorimetry (acid persulfate digestion method). QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.


107-06-1-J. Lachat Instruments, Loveland, CO. Pritzlaff, D. 2003. Determination of nitrate-nitrite in surface and wastewaters by flow injection

analysis. QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

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Laurel Lake water quality, nutrients, and algae, summer 20111

H.A. Waterfield, W.N. Harman and M.F. Albright

SAMPLING ACTIVITIES

Site visits to Laurel Lake were made on 16 June and 25 July 2011; water samples were collected over the deepest part of the lake from the surface to the bottom, as well as from the inlet stream and outlet of the lake. These samples were analyzed for nutrients, important ions, algae groups, and algal abundance (See Table 1 below). Measurements were recorded on-site for temperature, dissolved oxygen, specific conductance, pH and Secchi disk transparency (water clarity). On 16 June, measurements were also made to assess the presence of optical brighteners, which are found in laundry detergents, but the results were inconclusive; the tannic materials originating from the upstream bog caused interference with the readings.

FINDINGS & RECOMMENDATIONS

Algal growth in Laurel Lake is currently limited by the availability of nitrogen; this is the root cause of the blue-green algae over-abundance. This is typical in lakes that have historically experienced a moderate level of phosphorus loading from the watershed (i.e. active grazing by livestock, septic system influx, sediment loading, etc.). In the present situation, phosphorus has been added to the lake system to the extent that nitrogen and phosphorus concentrations are no longer in balance with the requirements of the algae. This situation favors the growth of blue-green algae (cyanobacteria). The resulting noxious blooms are not part of a healthy ecosystem (they do not provide nutrition to plankton or other organisms). They can greatly reduce clarity, impose odor problems, and can pose human and animal health risks even with passive contact.

To ultimately solve the problem, a great reduction in phosphorus loading would need to be achieved to the point where phosphorus is again the nutrient controlling algal growth. In the short term, if the Association wishes to stop the development of blue-green blooms, a proactive strategy must be developed.

Going Forward

Long-term Management Recommendations: To get at the root cause of the algae problem, nutrient loading (especially phosphorus) must be addressed by the Laurel Lake community, including those who live away from the shore within the watershed. Generally, all land uses within the watershed should be assessed; in the case of Laurel Lake, the dominant land use contributing phosphorus is residential development. The situation has progressed to the point that phosphorus is also released from the sediments during the summer – without control of this internal source of phosphorus, reductions from the

1 This report was prepared for the Laurel Lake Association by the BFS as part of a contractual agreement.

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watershed will be much less effective in solving the problem. In-lake phosphorus inactivation may be your best option to break the cycle of blue-green blooms (see the description below).

Short-term Actions: If the desire of the LLA in the short term is to prevent blooms from occurring for safety and recreational concerns, a plan should be formulated in the winter or early spring (with consult of a professional). How will the situation be monitored? Once certain conditions are met, what is the course of action?

1. Develop of a strategy to monitor the lake (i.e. weekly monitoring of temperature and presence/absence of blue-green algae)

2. Establish criteria for initiating treatment , potentially one of the following (this list is not exhaustive):

a. An algaecide and/or peroxide: The algaecide kills the algae and the peroxide degrades the toxins so they aren’t dispersed in the water.

b. Phosphorus inactivation: Buffered aluminum sulfate is used to remove algae and phosphorus from the water column and settle it on the lake bottom. This will also largely prevent the release of phosphorus from the sediments.

c. Circulation: Blue-green algae thrive in calm conditions. Circulation can be used to deter their growth by providing constant (or daily) agitation in the surface waters.

3. Treat according to regulations, best practices, etc. before a bloom develops. You, or a consultant, will need to work with your regional DEC office to develop an approved strategy to manage – some of the treatments listed above may not be permitted in your DEC Region.

4. If a significant bloom occurs, lake users must be informed and proper precautions should be taken to avoid exposure. The DEC and/or Department of Health in your county should also be informed – they will likely follow up with testing or further guidance.

RESULTS

Nitrate: very low (below our detection level); this indicates that the algae are using all available nitrate. The amount of nitrate in the water column is limiting the algal growth. Blue-green algae are able to dominate because they can use nitrogen from the atmosphere; other algal groups are not able to do this, and so are outcompeted by the blue-greens.

Phosphorus: Concentrations in Laurel Lake are moderately high. It is not likely the limiting factor for algal growth and that there is loading of phosphorus to the lake from sources in the watershed and internally from the substrate under anoxic conditions in near bottom waters. It is difficult to directly compare 2011 results with those from past testing, as we are unsure of the type/location of sample taken for past analyses. It is likely that this would be comparable to the 2011 surface sample. However, it seems that phosphorus concentrations have decreased since the 1983 sampling. On the 25 July sampling, near-bottom phosphorus levels were showing an increase. This situation in consistent with “internal loading”, where phosphorus associated with bottom sediments is released into the water column in the absence of oxygen (see below) and becomes available for use by algae.

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Algae and Water Transparency: Secchi disk transparency was 2.8m (9.2 ft) at both site visits; chlorophylla concentration, a measure of algal pigments used to estimate algal abundance, was also similar on both site visits: 26 µg/L in June, 25 µg/L in July. These values are in a range that indicates eutrophic conditions. In June the algal community was dominated by chrysophytes, a group of algae that do well in cooler water temperatures and higher nutrient conditions. This provides more evidence in support of the conclusion that the lake is continuing to show signs of eutrophication, as indicated by previous monitoring and recommendations. In July, cyanobacteria (blue-green algae) were equally as abundant as the chrysophyte group, though they were not “blooming” at this point. Observations reported by members of the LLA indicate that a bloom did occur following a period of hot dry weather; this type of weather, along with low nitrogen availability favors blue-green algae over others. Any effort to control blue-greens needs to be initiated at the early onset of a bloom. Additional sampling may provide insight into when that might occur (seasonal succession of algae types, nutrient sampling (nitrogen: phosphorus ratio, temperature, etc.).

Temperature and Dissolved Oxygen profiles indicate that Laurel Lake experiences strong thermal stratification during the summer months, meaning that there is a warm surface layer floating on top of the cold deep water (this is normal). This has major implications for the amount of dissolved oxygen in the water column – and in turn, for habitat available to fish and other aquatic organisms, and very importantly, internal nutrient cycling. The combination of organic loading from the bog and moderate algal production contribute to oxygen loss in deeper water. On both sampling dates the entire water column below 4 meters depth (13 ft) was essentially devoid of free oxygen (anoxic), meaning that these depths do not provide habitat for fish or invertebrates (fish food organisms). These conditions also lead to internal phosphorus loading (the release of phosphorus from the bottom sediments) as previously discussed.

Chlorides: Chlorides can be used to indicate potential contamination from onsite wastewater treatment systems, road salting, and other activities on the landscape. Chloride levels in Laurel Lake are extremely low; changes in these concentrations over time would likely indicate that chlorides are being added to the lake system from a land-based source.

Total Nitrogen: Results indicate that organic nitrogen is a major component of the total nitrogen present in the lake; sources of this include algae in the water and organic materials flowing in from the upstream bog. Nitrogen in this form is not readily available for use by algae or rooted aquatic plants, and so is not contributing meaningfully to the over production of algae; however, it is partially associated with tannins and other substances that contribute to the brownish color of the water. These compounds have the effect of reducing light penetration, a condition that also favors blue-green algae that compete well under low-light conditions.

Ammonia: Not present in high concentrations through most of the water column. Increased concentrations in the deeper water result from the low oxygen conditions. Ammonia can be toxic to aquatic life, but in this situation it is likely not something to be concerned with.

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ANALYSIS METHODS & RESULTS TABLES

Table 1. Methods used in the analysis of water samples collected from Laurel Lake.

Parameter Minimum Detection Level Method Reference

Total Phosphorus 4 µg/L Persulfate digestion followed by single reagent ascorbic acid

Liao and Marten 2001

Total Nitrogen 0.2 mg/L Cadmium reduction method following peroxodisulfate digestion

Ebina et al. 1983

Nitrate+nitrite-N 0.2 mg/L cadmium reduction method Pritzlaff 2003 Ammonia-N 0.2 mg/L Phenolate method Liao 2001 Alkalinity Titration to pH = 4.6 APHA 1989 Calcium EDTA titrimetric method APHA 1989 Chloride Mercuric nitrate titration APHA 1989

Table 2. Nutrient concentrations determined for water samples collected from Laurel Lake on 16 June and 25 July 2011. BD indicates that the concentration was below detectable levels.

ammonia (mg/L) nitrate+nitrite (mg/L) total nitrogen (mg/L) total phosphorus (ug/L) Depth (m) 6/16/2011 7/25/2011 6/16/2011 7/25/2011 6/16/2011 7/25/2011 6/16/2011 7/25/2011

0 BD BD BD 0.22 0.35 12 21 3 BD BD BD 0.19 0.47 20 31 6 BD BD BD 0.25 0.35 29 31 9 BD BD BD 0.29 0.58 25 35

12 0.34 BD BD 0.71 1.12 34 60 Outlet BD 0.04 0.20 0.84 11 49 Inlet BD BD 0.29 0.35 40 127

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Table 3. Alkalinity and ion concentrations determined for water samples collected from Laurel Lake on 16 June and 25 July 2011.

alkalinity (mg CaCO3/L) calcium (mg/L) chlorides (mg/L) Depth (m) 6/16/2011 7/25/2011 6/16/2011 7/25/2011 6/16/2011 7/25/2011

0 7.2 7.2 3.6 - 3.5 4.2 3 7.2 6.2 4.0 - 4.5 4.2 6 7.2 6.2 4.4 - 4.0 4.5 9 9.2 11.3 4.0 - 4.0 4.5

12 10.3 12.3 4.0 - 4.0 4.5 Outlet - - 0.0 - - - Inlet 3.1 2.1 2.8 - 2.5 2.5

Table 4. Physical measurements made on 16 June and 25 July 2011 at Laurel Lake.

temperature (C) dissolved oxygen (mg/L) pH sp. conductivity (µs/cm) Depth (m) 6/16/2011 7/25/2011 6/16/2011 7/25/2011 6/16/2011 7/25/2011 6/16/2011 7/25/2011

0 20.75 27.11 9.09 7.36 7.26 7.00 26 32 1 19.85 27.16 9.23 7.39 7.18 6.92 26 32 2 17.89 24.21 9.84 9.00 6.90 6.73 26 32 3 10.64 16.81 10.40 5.11 6.63 6.25 28 33 4 6.98 10.78 4.67 3.51 6.38 6.18 28 33 5 5.90 7.08 1.90 0.00 6.32 6.13 28 34 6 5.39 6.03 0.00 0.00 6.33 6.11 28 34 7 5.10 5.45 0.00 0.29 6.43 6.33 32 40 8 4.96 5.21 0.00 0.00 6.48 6.42 35 43 9 4.92 5.13 0.00 0.00 6.55 6.43 40 50

10 4.89 5.06 0.00 0.00 6.64 6.45 44 53 11 4.88 4.98 0.14 0.00 6.82 6.45 72 60 12 4.87 4.98 0.12 0.07 6.71 6.44 88 80

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REFERENCES

APHA, AWWA, WPCF. 1989. Standard methods for the examination of water and wastewater, 17th ed. American Public Health Association. Washington, DC.

Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total

phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1721-1726. Liao, N. and S. Marten. 2001. Determination of total phosphorous by flow injection analysis

colorimetry (acid persulfate digestion method). QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.


107-06-1-J. Lachat Instruments, Loveland, CO. Pritzlaff, D. 2003. Determination of nitrate-nitrite in surface and wastewaters by flow injection

analysis. QuikChem®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

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2011 Catskill Region Aquatic Nuisance Species Survey for the Catskill Center for Conservation and Development

W.N. Harman1

Work Plan:

This plan outlines a contract for services between The Catskill Center for Conservation and Development and the SUNY Oneonta Biological Field Station, Willard N. Harman, Director. The scope of work was stipulated as 1 through 5 below: 1. Compile relevant survey and inventory information from all known sources.

2. Determine access locations for 2 “easily accessed” lakes or reservoirs in each of 5 watersheds to be approved by CRISP.

3. Develop a qualitative sampling technique with approval from members of CRISP and sample aquatic communities in each lake:

a. benthic macrophytes b. benthic macroinvertebrates c. zooplankton d. fish

4. Concentrating on Didymosphenia, macrophytes, macroinvertebrates, sample at 3 locations in each of five (5) major regional streams at what appears to be optimal habitat considering stream character.

5. Develop a final summary report, which should include collected research that was compiled and the results of qualitative sampling for distribution among CRISP partners.

On site observation and sampling procedures:

Upon arrival at a proposed collecting site the following procedures were followed: 1. Observations were made of access, surrounding land use and semi-aquatic invasive

exotics. Species in question were collected for future determination. 2. CRISP Aquatic Survey sheets were begun to be filled out with the date, location by

descriptive name and coordinates. Semi-aquatic nuisance species and abundances were indicated on check off list (See Working List below).

3. Character of biotope was observed (water quality, trophic status, appearance). 4. Depending on the site, macrobenthic invertebrates and any plants or algae species were

collected by hand picking from the substrate. Triangle nets or hand sieves were used to

1 Distinguished Service Professor and Director, SUNY Oneonta Biological Field Station.

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collect organisms from vegetation or inorganic substrates. Seines were used in lotic (running) waters via traditional “kick” methods for macroinvertebrate collections. Any ANS were noted and indicated on check off list.

5. A 63µm mesh plankton net was tossed out into the water or lowered from a boat or structure over the water, and retrieved, to observe zooplankton. Any ANS were noted and indicated on check off list.

6. Any ANS fish observed were noted and indicated on check off list. 7. Questionable ANS species were placed in containers and returned to the laboratory for

further study and species determination. 8. Any sampling equipment, wading gear, boats and trailers were treated as indicated below

before leaving the collection site.

Sampling protocols to prevent inadvertent distribution of ANS followed the current New York State Department of Environmental Conservation, Bureau of Fisheries sampling, survey, boat and equipment protocols. In particular, to prevent inadvertent distribution of any exotics encountered, all equipment before use was clean and dry, or disinfected. After utilization all equipment was disinfected at each collecting site immediately after use.

For all survey work in streams and rivers where the status of aquatic nuisance species (ANS) was unknown, sampling (at any one work day) started at the uppermost reach and then worked downstream. Disinfectant was kept in the transporting vehicle for ready use at each site. Prior to leaving each site any visible plants, animals and substrate were removed from any boat, trailer, sampling equipment, boots or containers, live wells, etc., to prevent transfer of biota or water from one water body to another. In all cases a 10% bleach solution was used as a disinfectant. Boats and trailers were cleaned using a high temperature pressure washer at the BFS after each use (limiting boat based sampling to one collection site daily). Working List of CRISP Aggressive High Threat Aquatic Nuisance Species:

The list provided in Table 1 has been compiled from ANS species lists from nearby regions (the Great Lakes and New England), from local and nearby records and updated based on the results of this survey. Organisms listed in Categories E and C have limited distributions within the Catskill region. Consideration for “Elimination” or “Containment” as listed is based only on my opinion. Actual strategies planned and/or undertaken to address each situation would depend on concern relative to the aggressive characteristics of the organisms so categorized, resources available, likelihood of success and organization priorities (See Narrative).

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Table 1. List of aquatic nuisance species (ANS) considered in the Catskill regional survey. A = Approaching the Catskill region; documented at locations nearby, E = To be cited for eradication; limited distribution in the Catskills, C = Containment (elimination not feasible); limited distribution but well established in the region, W = Widespread within the Catskills. Pathogens Genus Novirhabdovirus* Viral Hemorrhagic Septicemia A Myxobolus cerebralis Salmonid whirling disease A Aeromonas salmonicola Furunculosis A * Viral taxonomy does not follow binomial nomenclature. The species is VHS. Algae Didymosphenia germinate Didymo E Nitellopsis obtusa Starry stonewort C Vascular plants Cabomba caroliniana Fanwort A Egeria densa Brazilian elodea A Hygrophila polysperma East India hygrophila A Hydrilla verticillata Hydrilla A Salvinia molesta Giant salvinia A Myriophyllum spicatum Eurasian watermilfoil C Myriophyllum aquaticum Parrot’s feather A Myriophyllum heterophyllum Variable-leaved watermilfoil A Butomus umbellatus Flowering rush A Iris pseudacorus Yellow flag Iris C Fallopia japonica Japanese knotweed W Lythrum salicaria Purple loosestrife W Phragmites australis Common reed W Trapa natans Water chestnut E Hydrocharis morsus-ranae European frog bit A Najas minor Slender-leaved naiad A Najas guadalupensis Southern naiad C Nymphoides peltata Yellow floating heart A Potamogeton crispus Curly leaf pondweed C Rorippa amphibia Great water cress A Zooplankton Bythotrephes cederstroemi Spiny water flea A Cercopagis pengoi Fish hook water flea A Invertebrate benthos Corbicula fluminea Asiatic clam A Dreissena polymorpha Zebra mussel A Dreissena bugensis Quagga mussel A Bithynia tentaculata Faucet snail A

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Table 1 (cont.). List of aquatic nuisance species (ANS) considered in the Catskill regional survey. Cipangopaludina chinensis Chinese mystery snail A Potamopyrgus antipodarium New Zealand mud snail A Orconectes rusticus Rusty crayfish W Eriocheir sinensis Chinese mitten crab A Fish Gymnocephalus cernuus Eurasian ruffe A Neogobius melanostomus Round goby A Proterothinus marmoratus Tubenose goby A Tinca tinca Tench A Alosa aestivalis Blueback herring C Alosa pseudoharengus Alewife C Cyprinus carpio Common carp W Ctenopharyngodon idella Grass carp E Dorosoma cepedianum Gizzard shad A Morone americana White perch C Scardinius erythrophthalmus European rudd C Channa argus Snake head A Misgurnus anguillicaudatus Loach, Oriental weatherfish C Birds Cygnus olor Mute swan C Narrative: CRISP Aquatic Survey: 2011

Results pre-survey data search:

In preparation for conducting the survey, I contacted all relevant NYS DEC regional

offices and received important anecdotal information on fisheries. I checked out the 1984 Adirondack Lakes Survey (expanded in 1987 to include Lower Hudson Region) from the DEC library and made hard copies of survey results on over 40 Catskill Lakes over 40 ha in size. Contact was made with the NYC DEP and data were received from their macrobenthic monitoring efforts. I talked to faculty from the SUNY Cobleskill Fisheries and Aquaculture Department. NYS DEC records included some reasonable fisheries inventories, nothing relevant on invertebrates or plants. The NYC DEP provided excellent data concerning macrobenthic invertebrates and anecdotal information on fish. Other than the anecdotal information from DEC fisheries and SUNY Cobleskill Fisheries and Aquaculture personnel there were no satisfactory data from any source relevant to ANS. I found nothing on pathogens attributed specifically to the Catskill region.

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Field work:

Wet weather in the spring gave me a late start. Storms of tropical origin terminated sampling in late summer. Despite the weather related problems, collections were made at 30 sites in 8 watersheds (described in Table 2, coordinates given in Table 3). Eighteen lakes (18) and twelve (12) stream reaches were sampled. Originally, the strategy was to sample larger lentic water bodies assuming the potential of a higher diversity of organisms present. In the Catskills the largest water bodies are reservoirs, most with restricted access, arguably precluding the most common vector of ANS dispersal; recreational activities. Therefore, in addition to those water bodies, smaller standing waters in the same catchments were also sampled.

Summary of results: I encountered fewer exotics than I expected to find in the Catskills and lower numbers of

those that were encountered. Both algae listed, didymo and starry stonewort, were present. Twenty (20) vascular plants of concern were on the list. I found eight (8). Of the ten (10) invertebrates listed only two were found; zebra mussels and rusty crayfish. Five (5) out of the 13 fish listed were found. Most of the ANS were present in the Susquehanna River watershed. The Central Catskills are comparatively free of exotics. Some were undoubtedly missed, but both the lake and river sites were selected for their ease of access and therefore exposure to vectors of ANS introductions.

Dominant vascular plant ANS are the emergents purple loosestrife (Lythrum salicaria), common reed (Fragmites australis) and the (practically) terrestrial Japanese knotweed (Fallopia japonica). Although widespread, they are encountered in greater frequency in the northwestern counties (Otsego, Delaware, northern Schoharie). In all cases loosestrife was subjected to herbivory by Galerucella spp., a chrysomelid beetle, and appears to be reasonably controlled. Submergent aquatic plants of concern were rarely encountered. White Lake (site 9) and Lake Louise Marie (site 12), both in Sullivan County, support populations of milfoil (Myriophyllum spp.), but apparently not Eurasian milfoil. I would like to check again in the future to assure positive identification. The only invertebrate macrobenthos observed were rusty crayfish (Orconectes rusticus) found in a few locations where streams were carrying high loads of silt, and zebra mussels (Dreissena polymorpha) restricted to the Susquehanna River drainage basin. All fish data were obtained verbally from sources in NYS DEC and SUNY Cobleskill or have been found in locations regularly sampled by Biological Field Station (BFS) personnel.

Recommendations for mitigative activities:

The purpose of developing a survey of aquatic nuisance species (ANS) in the Catskill region is to:

1. Provide an understanding of the current nature and condition of regional aquatic resources relevant to the distribution and abundance of ANS.

2. To begin the development of a baseline from which to assess the importance of newly documented organisms relative to the ANS threat within the region.

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3. To enable the CRISP partners to address the implementation of early detection rapid response protocols when appropriate.

Therefore, the following few comments on situations as observed during the summer of 2011.

1. The aquatic algae; didymo , starry stonewort and the plants; yellow flag iris, curly –leaved pondweed and Eurasian milfoil as well as the fish; white perch, and alewife all have restricted distributions within the region. Given the current techniques for management, in areas where they have been successfully established there would be very little chance of success in eliminating them without severe environmental damage and/or tremendous expense. Therefore I suggest containment to the habitats in which they are now encountered by the use of prophylactic measures.

2. The aquatic plant; southern naiad and the loach (a fish) have restricted distributions but may not be particularly aggressive. I believe southern naiad has been beneficial in Otsego Lake stabilizing unconsolidated sediments.

3. European carp has been widespread locally for at least 100 years, and although detrimental to native species and negatively affecting sensitive habitats, its elimination would be impractical and not unlike attempting to remove other “naturalized” species such as several commonly stocked fish such as largemouth black bass, several small sunfishes and yellow perch that are now found throughout the region (that is not to preclude their removal from isolated smaller water bodies where intensive fisheries management takes place).

4. Although I did not encounter grass carp, they are in Summit Lake, Schoharie County. The DEC Region 4 office has issued 233 additional stocking permits (in 2011 for small ponds) for the control aquatic plants. If they are encountered in any waters outside of permitted ponds they should be eliminated. Data for alewife and white perch are also from DEC and SUNY Cobleskill. Fisheries data continue to trickle in. I will update as appropriate.

5. Water chestnut, and in my opinion, mute swans should be eliminated whenever they are encountered.

Table 2. Sampling sites evaluated during the 2011 Catskill regional ANS survey.

Location Site # 1. Susquehanna River: A. Otsego Lake, Otsego Co. (1) B. Canadarago Lake, Otsego Co. (21) C. Moe Pond, BFS Upper Research Site, Otsego Co. (29) D. Susquehanna ox bow wetland, Oneonta, Otsego Co. (30) 2. Delaware River: 2a. West Branch. A. Cannonsville Reservoir. Stilesville, Delaware Co. (Rt. 10) (5) B. Oquaga Lake. McClure, Broome Co. (4) C. Oquaga Creek, Delaware Co. (2) D. West Branch Delaware River at Deposit, Delaware Co. (3) E. West Branch Delaware River at Rts. 10/26, Delaware Co. (6)

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Table 2 (cont.). Sampling sites evaluated during the 2011 Catskill regional ANS survey.

F. Little Delaware River at Bovina, Delaware Co. (21A) 2b. East Branch. A. Pepacton Reservoir. Downsville (Rt. 30), Delaware Co. (7) B. Beaver Kill at Rt. 54, Sullivan Co. (22) C. Little Pond, Little Pond State Campground, Delaware Co. (23) D. Waneta Lake, Sullivan Co. (24) E. Beaver Kill at Rockland, Sullivan Co. (8) 3. Schoharie Creek. A. Schoharie Reservoir. near Prattsville, Green Co. (18) B. Blenheim Gilboa Reservoir. North Blenheim (Rt. 30), Schoharie Co. (19) C. Summit Lake (Rt. 10), Schoharie Co. (20) D. Schoharie Creek at Jewett Ctr., Green Co. (17) 4. Hudson drainage. A. Esopus Creek at Allaben, Ulster Co. (28) B. Ashokan Reservoir. Ashokan (Rt. 28), Ulster Co. (16) 5. Wall Kill A. Rondout Reservoir. Lowes Corners (Rt. 153), Sullivan Co. (14) B. Rondout Creek, Sundown Wild Forest, Ulster Co. (15) C. Cape Pond, Ulster Co. (27) 6. Mongaup/Neversink Rivers A. Neversink Reservoir. Neversink (Rt. 55), Sullivan Co. (13) B. Lake Louise Marie. Bridgeville (Rt. 17), Sullivan Co. (12) C. White Lake, Sullivan Co. (9) D. Black Lake. (Rt. 55), Sullivan Co. (26) E. Swan Lake, Sullivan Co. (10) G. Lake Superior, Sullivan Co. (11) 7. North Brook. A. Hunter Lake. Fosterdale (Rt. 52), Sullivan Co. (25) Table 3. Coordinates for sampling sites described above (Table 2). 1. N42o43.119’ W074o 55.575 2. N42o05.860’ W074o23.600’ 3. N42o03.641’ W075o25.123’ 4. N42o01.051’ W075o27.603’ 5. N42o04.162’ W075o19.968’

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Table 3 (cont.). Coordinates for sampling sites described above (Table 2). 6. N42o10.434’ W075o01.966’ 7. N42o04.328’ W074o54.529’ 8. N41o57.852’ W074o54.476’ 9. N41o40.458’ W074o50.311’ 10. N41o45.315’ W074o46.940’ 11. N41o39.663’ W074o52.258’ 12. N41o36.602’ W074o34.386’ 13. N41o94.780’ W074o40.063’ 14. N41o51.439’ W074o30.437’ 15. N41o54.608’ W074o27.203’ 16. N41o59.916’ W074o06.725’ 17. N42o14.555’ W074o19.791’ 18. N42o19.248’ W074o26.217’ 19. N42o26.417’ W074o27.237’ 20. N42o35.130’ W074o35.022’ 21. N42o49.005’ W074o59.550’ 21A. N42o14.930’ W074o49.871’ 22. N42o03.015’ W074o41.353’ 23. N42o02.352’ W074o44.938’ 24. N42o57.709’ W074o49.933’ 25. N41o43.231’ W074o54.291’ 26. N41o37.949’ W074o52.319’ 27. N41o44.914’ W074o26.234’ 28. N42o06.390’ W074o21.122’ 29. N42o43.100’ W074o55.601’ 30. N42o26.486’ W074o06.907’ Table 4. ANS taxa indicating locations collected by site number. Pathogens Site number Genus Novirhabdovirus* Viral Hemorrhagic Septicemia Myxobolus cerebralis Salmonid whirling disease Aeromonas salmonicola Furunculosis * Viral taxonomy does not follow binomial nomenclature. The species is VHS. Algae Didymosphenia germinate Didymo 28 Nitellopsis obtusa Starry stonewort 1,21 Vascular plants Cabomba caroliniana Fanwort Egeria densa Brazilian elodea Hygrophila polysperma East India hygrophila

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Table 4 (cont.). ANS taxa indicating locations collected by site number. Hydrilla verticillata Hydrilla Salvinia molesta Giant salvinia Myriophyllum spicatum Eurasian watermilfoil 1,9,21 Myriophyllum aquaticum Parrot’s feather Myriophyllum heterophyllum Variable-leaved watermilfoil Butomus umbellatus Flowering rush Iris pseudacorus Yellow flag iris 1,21 Fallopia japonica Japanese knotweed 1,3,6,8,9,17,18,20,21A,28,30 Lythrum salicaria Purple loosestrife 1,5,6,9,12,16,19,21,28,30 Phragmites australis Common reed 14,21,29 Trapa natans Water chestnut 10,27,30 Hydrocharis morsus-ranae European frog bit Najas minor Slender-leaved naiad Najas guadalupensis Southern naiad 1 Nymphoides peltata Yellow floating heart Potamogeton crispus Curly leaf pondweed 1,3,10,21,30 Rorippa amphibia Great water cress Zooplankton Bythotrephes cederstroemi Spiny water flea Cercopagis pengoi fish hook water flea Invertebrate benthos Corbicula fluminea Asiatic clam Dreissena polymorpha Zebra mussel 1,21 Dreissena bugensis Quagga mussel Bithynia tentaculata Faucet snail Cipangopaludina chinensis Chinese mystery snail Potamopyrgus antipodarium New Zealand mud snail Orconectes rusticus Rusty crayfish 1,6,21 Eriocheir sinensis Chinese mitten crab Fish Gymnocephalus cernuus Eurasian ruffe Neogobius melanostomus Round goby Proterothinus marmoratus Tubenose goby Tinca tinca Tench Alosa aestivalis Blueback herring Alosa pseudoharengus Alewife 1,5,7,18,21,19* Cyprinus carpio Common carp 1,21 Ctenopharyngodon idella Grass carp 20* Dorosoma cepedianum Gizzard shad Morone americana White perch 1,5,7,12,18* Scardinius erythrophthalmus European rudd 1

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Table 4 (cont.). ANS taxa indicating locations collected by site number. Channa argus Snake head Misgurnus anguillicaudatus Loach, Oriental weatherfish* Birds Cygnus olor Mute swan *Alewife, grass carp and white perch records are from DEC region 4 and SUNY Cobleskill. Aside from Summit Lake, permits have been issued for stocking of grass carp in 233 sites, all 5 acres or less in surface area in DEC Region 4. Loach are in the Manor Kill, Schoharie County. Fish data continue to come in from various reliable sources. I will continue to update the survey with an indication that records are anecdotal if appropriate.

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2011 Pearly Mussel Surveys of Portions of the Catatonk Creek, Butternut Creek

and Unadilla River

Award Number 58053

Image from Strayer & Jirka, 1997

Submitted to:

James Curatolo Upper Susquehanna Watershed Coordinator

Upper Susquehanna Coalition 4729 State Route 414 Burdett, NY 14818

&

Thomas Bell Project Manager & State Wildlife Grants’ Biologist

1285 Fisher Ave Cortland, NY 13045

Submitted by: Dr. Willard N. Harman, Distinguished Service Professor

& Paul H. Lord

Authors:

Paul H. Lord [email protected]

&

Timothy N. Pokorny [email protected]

January, 2012

SUNY Oneonta Biological Field Station 5838 State Highway 80

Cooperstown, New York 13326

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mailto:[email protected]


EXECUTIVE SUMMARY

We completed surveys for pearly mussels on portions of the Catatonk Creek, the Butternut Creek, and the Unadilla River in 2011. Financial considerations limited the scope of our surveys, but we made good use of techniques mastered in the surveys completed in the previous three years. We sought to determine the status of the Brook floater (Alasmidonta varicosa) in the Catatonk and to see if we could find a nearby location for relocating the Brook floaters during dam removal. We sought to determine the status of the four New York Susquehanna River Watershed pearly mussel species of greatest conservation need (SGCN), Elktoe (Alasmidonta marginata), Brook floater (A. varicosa), Green floater (Lasmigona subviridis), and Yellow lampmussel (Lampsilis cariosa), in the Butternut Creek and the Unadilla River. Additionally, we looked under large flat rocks in the Butternut Creek and the Unadilla River for Hellbenders (Cryptobranchus alleganiensis).

Key findings:

o Brook floaters persist in the Catatonk Creek, but there is no evidence of recent reproduction. Our cursory survey of nearby stream locations failed to identify a suitable location for relocating the mussels during dam removal.

o Dense and extensive pearly mussel beds exist in the Butternut Creek, but there is only one pearly mussel SGCN found there: the Yellow lampmussel.

o All four SGCN appear (Brook floater identification was tentative) in the Unadilla River, but tens of thousands of mussels have been killed in the last year.

A NYSDEC investigation into the cause was stymied by issues of jurisdiction: the Unadilla River forms the boundary between two NYSDEC regions.

o No Hellbenders were located.

Recommendations:

o Proceed with the plan for removing the Spencer Lake dam protecting the pearly mussels immediately downstream of the dam by temporarily moving them to a refuge location.

o Protect the extensive Eastern elliptio (Elliptio complanata) beds in the Butternut Creek which can be used to repopulate New York Susquehanna River Watershed with Eastern elliptios once their larval hosts, American eels (Anguilla rostrata), are reintroduced to the watershed.

o Protect the Unadilla River from pearly mussel killing pollution.

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BACKGROUND

There being no funding for writing this important report, it is terse and without full editing. We provide background regarding pearly mussels in the NY State section of the Susquehanna Watershed in Lord et al. (2011). The focus of our 2011 surveys was to provide a “quick look” at three lotic areas of interest: the Catatonk Creek, Butternut Creek and Unadilla River.

The Catatonk Creek, in Tioga County, held a population of threatened Brook floaters (Alasmidonta varicosa) a decade past (Strayer & Fetterman 1999; NY Natural Heritage 2011) just downstream of a Catatonk Creek dam being considered for removal (Nxxxxxxx Wxxxxxxx; UTM XXT xxxxxxE, xxxxxxx; Curatolo pers comm). Our focus was to determine if the population persisted and if nearby sites could serve as a temporary home for the Brook floaters.

The Unadilla River was preliminarily surveyed by a student of Lord’s (Maricle 2011) in 2010. Maricle’s survey provided evidence of the persistence of three of the pearly mussel species of greatest conservation need (SGCN) in New York Susquehanna River Watershed rivers: the Elktoe (Alasmidonta marginata), Green floater (Lasmigona subviridis), and Yellow lampmussel (Lampsilis cariosa). Adding to interest in the Unadilla River was that it previously held Eastern hellbenders (Cryptobranchus alleganiensis), a species of special concern (NYSDEC 2012; USCA 2010). Our focus was to validate and expand upon the 2010 Unadilla River survey seeking to identify pearly mussel biodiversity hotspots.

The Butternut Creek is a major Unadilla River tributary reputed to be relatively pristine and considered a potential habitat for both pearly mussels of greatest conservation need and the Eastern hellbender (USCA 2010).

Methods and Rationale

To make the most of our financially constrained field time, we tailored methods refined in recent Susquehanna watershed surveys (Lord et al. 2011) to each waterway and to our focus for that waterway.

In the Catatonk Creek, we devoted most of our time to careful accounting for the Brook floater population immediately downstream of the dam considered for removal. We first completed a careful examination of the creek bottom using a combination of viewing buckets, mask and snorkel, and SCUBA as appropriate for the varying depths found in the Creek 400 m downstream of the dam. We then excavated 105 randomly chosen 0.10 m2 quadrats to the depth that pearly mussels could burrow and survive, and we sieved the sediments through at 0.12 inch [3.05 mm] mesh screen to find small mussels. We noted all live mussels found and characterized the Creek bottom and shorelines of surveyed areas consistent with Lord et al. (2011). Following this intense survey at the dam site, we made cursory viewings of streams above and below our survey site to identify potential pearly mussel transfer refuge locations for possible dam modification work.

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In the Butternut Creek, making use of facilitating clarity unusual for the New York Susquehanna River Watershed rivers, we casually surveyed extensive areas from our kayaks. We validated our kayak observations in four locations using viewing buckets, mask and snorkel, and SCUBA as appropriate for the varying depths found in the creek. We noted all live mussels found, although in some sections we noted the mussels as too numerous to count and estimated their densities per square meter. In areas where we left our kayaks to search for mussels, we characterized the creek bottom and shorelines of surveyed areas consistent with Lord et al. (2011). We used flashlights to search under large flat rocks for Hellbenders (Cryptobranchus alleganiensis).

In the Unadilla River, our searches were limited to viewing buckets, mask and snorkel, and SCUBA as appropriate for the varying depth and visibility found in the river. We sampled in 14 locations and used our kayaks to identify additional locations with significant numbers of dead pearly mussels. We determined the approximate timeframes for these deaths based on shell erosion and aufwuchs attached to the shells. In areas where we left our kayaks to search for mussels, we characterized the river bottom and shorelines of surveyed areas consistent with Lord et al. (2011). We used flashlights to search under large flat rocks for Hellbenders.

Per methods found in Lord et al. (2011), we created ArcGIS files, documenting our findings, for submittal to the USC, NYSDEC, and New York Natural Heritage Foundation.

RESULTS

In the Catatonk Creek we found a modest population of Brook floater although we found no evidence of recent reproduction (Table 1). Our cursory survey of accessible stream locations above and below the intense survey location did not produce an ideal location for temporary storage of the pearly mussels in the intense survey location.

Table 1. Live pearly mussels found in Catatonk Creek (Tioga County, NY) below XXXXXX dam in 2011 surveys.

Common Name Scientific Name Number FoundBrook floater Alasmidonta varicosa 10Eastern elliptio Elliptio complanata 269Eastern floater Pyganodon cataracta 9Squawfoot Strophitus undulatus 135Triangle floater Alasmidonta undulata 38

In the Butternut Creek, we found sparse pearly mussel populations in the headwaters and, downstream, long reaches with dense pearly mussel populations (Figure 1). We encountered a few areas where silt obscured visibility and the pearly mussel populations became sparse. We found only one pearly mussel SGCN: the Yellow lampmussel. Other pearly mussel species found alive include Eastern lampmussels (Lampsilis radiata), Eastern elliptios (Elliptio complanata) and Squawfoots (Strophitus undulatus). We found several recent dead Triangle floaters (A. undulata) although we never found a live animal. Approximately 69 % of the live mussels surveyed were Eastern elliptio. The Eastern elliptio were overall smaller and less

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eroded than Eastern elliptio animals collected elsewhere in New York Susquehanna River Watershed rivers. We found no Hellbenders.

Figure Redacted.

Figure 1. Butternut Creek and Unadilla River areas searched for pearly mussels (black) in 2011 noting locations with live pearly mussels and pearly mussel Species of Greatest Conservation Need (SGCN) as determined by the New York State Department of Environmental Conservation (NYSDEC, 2010). Elktoe (Alasmidonta marginata) = orange circle, Brook floater (A. varicosa; tentative identification) = red circle, Green floater (Lasmigona subviridis) = blue circle, Yellow lampmussel (Lampsilis cariosa) = yellow circle and other pearly mussels = green.

In the Unadilla River, recent pearly mussel deaths were evident in a small reach in the headwaters and in an extensive reach from the Skaneateles Turnpike south to West Edmeston. We determined most of these deaths occurred in the previous twelve months. In South Edmeston, we found an additional dead population of pearly mussels which we determined had been dead longer than a year, probably killed in the year prior to the survey year. We requested enforcement attention to probable illegal dumping of organic wastes. We found three pearly mussel SGCN: the Yellow lampmussel, the Elktoe and the Green floater (Figure 1). We found no animals that were clearly Brook floater, although we did find several possible Brook floaters similar to those noted previously (Strayer & Fetterman, 1999; Lord et al. 2011). We found no Hellbenders.

DISCUSSION

Removal of the Catatonk Creek dam poses a direct threat to the pearly mussel population in the intensely surveyed area below the dam. We are confident that we can identify a protecting location for temporary storage of the mussels if a decision is made to remove the dam. While moving involves risk for the population, there is potential benefit to the Brook floater population in the Catatonk Creek. There were few Brook floaters in the lower part of the surveyed area. The area immediately below Xxxxxx Road held the Brook floater population. This area had wooded wetlands on both sides of the Catatonk Creek similar to other high quality pearly mussel beds in New York Susquehanna River Watershed rivers (Figure 2; Lord et al. 2011). If the dam is removed and the stream restored, the stream would have protecting wetlands on both sides providing a hydraulic refuge as discussed in Lord et al. (2011).

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Figure Redacted.

Figure 2. Imagery of the area of the Catatonk Creek, below the intersection of Xxxxx Road and Xxxxxxx Road, holding a population of Brook floater (Alasmidonta varicosa) delineating the wooded wetlands providing a hydraulic refuge for pearly mussels.

The Butternut Creek is a treasure. Most of the Creek areas we surveyed were protected with substantial buffers. The water is clear for most of the creek’s length. Some pearly mussel species thrive, but we did not find three of the four pearly mussel SGCN in the Butternut Creek. There could be any number of explanations. We suspect summer month water temperatures are not high enough to facilitate reproduction (Galbraith and Vaughn 2011), but this is something that needs to be studied for each species. The cold water also apparently slows growth of Eastern elliptio. Given the superannuated Eastern elliptio population and its lack of reproduction in New York Susquehanna River Watershed rivers, this Butternut Creek population may serve as a source of reproductive material should American eels (Anguilla rostrata) be reintroduced to the New York Susquehanna River Watershed rivers. (See Lord et al. 2011.)

Our Unadilla River survey provides the story of an opportunity missed. There have been at least two major losses of pearly mussels (estimated in the tens of thousands), including all SGCN species, in the last two years. Enforcement response has been slow and uncoordinated, apparently because the river forms the boundary between two NYSDEC regions which stymied enforcement of a problem that involves both sides of the river. It is unclear, at the time of this writing (five months after our initial report), whether illegal dumping has been completely stopped. There are still sizeable pearly mussel beds in the Unadilla River holding SGCN. The Unadilla River needs protection: buffers, strict enforcement of waste spreading regulations, and increased monitoring.

ACKNOWLEDGEMENTS

This work was facilitated by James Curatolo, Heidi M., and Mike Stensland.

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REFERENCES

Curatolo, J. 2011. Personal communication. Upper Susquehanna Watershed Coordinator.

Upper Susquehanna Coalition, 4729 State Route 414, Burdett, NY 14818. Office/Fax: (607) 546-2528; cell: (607) 765-4780; E-mail: [email protected] .

Galbraith, H. S. and C. C. Vaughn. Effects of reservoir management on abundance, condition,

parasitism and reproductive traits of downstream mussels. River Res Applic. Vol. 27. pp. 193-201.

Lord, P. H., T. N. Pokorny, and W. N. Harman. 2011. Susquehanna Freshwater Mussel

Surveys: 2008-2010. Biol. Fld. Sta. rpt for NYSDEC (Award Number 47260).

Maricle, S. 2011. Unadilla River pearly mussel survey. In 43rd Annual Report (2010). SUNY Oneonta Biol. Fld. Sta. SUNY Oneonta.

New York Natural Heritage Program. 2011. Online Conservation Guide for Alasmidonta varicosa. Available from: http://www.acris.nynhp.org/guide.php?id=8378. Viewed 4 January 2012.

NYSDEC. 2012. Eastern hellbender fact sheet. http://www.dec.ny.gov/animals/7160.html as viewed on 4 January 2012.

Strayer, D. L. and A. R. Fetterman. 1999. Changes in the distributions of the freshwater mussels (Unionidae) in the Upper Susquehanna River Basin, 1955-1965 to 1996-1997. Am. Mid. Nat. 142:328-339.

USCA. 2010. Meeting of Upper Susquehanna Conservation Alliance in Cortland, NY on 13Oct10

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http://www.dec.ny.gov/animals/7160.html

Drainage basin size as a predictor of fish species richness in the Otsego Lake Watershed

John R. Foster1 and Ryan Lewis2

Abstract: This study was conducted to determine if fish faunal richness can be predicted from the size of the drainage basin of individual tributary streams in the Otsego Lake watershed. Previous electro-fishing surveys conducted since 1989, plus two surveys conducted in this study were downloaded into a Geographic Information Systems Data Base and analyzed. The number of species present in each tributary stream was strongly correlated to the drainage area of that stream. However, anthropomorphic factors, such as road crossings and channelization also impacted species richness.

INTRODUCTION

Within the same watershed, stream order, stream size, stream length, discharge and drainage basin are highly correlated (Harrel et al. 1967, Platts 1979). In previous studies, these various watershed measures have been correlated with the number of fish species present, i.e. species richness (Eadie et al. 1986, Hugueny 1989, Barila et al. 1981).

The Otsego Lake watershed encompasses and area of 18,811 ha. (Harman et al. 1997).

The tributary streams in the Otsego Lake watershed have been individually surveyed by numerous authors (Hayes 1989, 1990, Bassista & Foster 1995, Reynolds et al. 2010, Miner 1997, Foster 1996, Jamieson et al. 2004). Unfortunately, the data from these surveys are not available in a comprehensive database that would allow for comparisons across studies and watersheds.

The goal of this study was two-fold; the first was to develop a Geographic Information Systems (GIS) database that would allow the examination of fish fauna data collected since 1989 by the SUNY Oneonta Biological Field Station and SUNY Cobleskill. In order to meet this goal, the location of each species collected in the Otsego Lake watershed was plotted on a map using SUNY Cobleskill’s Geographic Information Systems (GIS) database. Streams that had not been surveyed (Glimmerglen and Mount Wellington) were surveyed as part of this report. The second objective of this study was to utilize the newly created database to determine the correlation between fish species richness and the size of the drainage basins of the Otsego Lake tributary streams.

MATERIALS & METHODS

The Otsego Lake watershed is located in the Towns of Otsego, Springfield and Middlefield in Otsego County, New York, with the northern most part of the watershed in 1 BFS Visiting Researcher/Fisheries & Wildlife Dept., SUNY Cobleskill, NY 2 Fisheries & Aquaculture Student, Fisheries & Wildlife Dept., SUNY Cobleskill, NY

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Herkimer County. Elevation of the mouths of tributary streams in Otsego Lake is 1190 feet above sea level, and the upper regions of the watershed reach as high as 1900 feet in elevation. The data utilized for this study were limited to the permanent streams named in Figure 1 and Table1. Ephemeral streams were not included in this study.

Figure 1. Otsego Lake’s watershed tributary streams. Named streams were studied in this report.

Data utilized in this study were collected from 1989 – 2012 (Table 1). Data reported were from single surveys and did not represent the accumulation of species found in a given watershed through multiple surveys. In most cases survey information has been published in the Annual Reports of the SUNY Oneonta Biological Field Station, although the studies by Cornwell and Lewis represent new surveys conducted for this paper. Surveys were conducted primarily with backpack electro-shockers, although occasionally seines were also used. A minimum of 1,000 seconds of electrofishing was used for each survey.

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Table 1. Otsego Lake tributary stream drainage basin, species richness, sample year and information source.

Stream Watershed

Acres Number of

Species Sample

Year Source

Shadow Brook 11,660.2 28 1994 Bassista & Foster 1995

Shadow Brook 11,660.2 24 2010 Reynolds et al.2011

Cripple Creek 10,179.8 17 1996 Miner 1997

Hayden Creek 7,822.2 17 1996 Foster 1996

White Cr./Trout Brook 3,241.6 16 1996 Foster 1996

Leatherstocking Creek 2,073.3 13 1990 Hayes 1990

Mt. Wellington Stream 1,899.1 2 2012 Cornwell, pers. com.

Brookwood Creek 1,568.0 7 1989 Hayes 1989

Mohican Creek 1,112.4 8 1989 Hayes 1989

Glimmerglen Creek 1,039.5 2 2010 Lewis in prep.

Willow Brook 926.9 2 1989 Hayes 1989

Three Mile Point Stream 308.9 3 1989 Hayes 1989

RESULTS

There was a strong correlation between the size of the drainage basin of individual streams and species richness (Figure 2, Pearson Product Moment Correlation r = .900, P < .001). Relatively few fish were considered to be widely distributed throughout the Otsego Lake watershed. Blacknose dace (Rhinichthys atratulus), longose dace (R. cataractae) and creek chubs (Semotilus atromaculatus) were found in over two thirds of the streams sampled. However, most species had very restricted distributions and occurred in less than one third of the stream sampled. These included rainbow trout (Oncorhynchus mykiss), brook trout (Salvelinus fontinalis), alewife (Alosa pseudoharengus), redsided dace (Clinostomus elongatus), cutlips minnow (Exoglossum maxillingua), golden shiner (Notemigonus crysoleucas), emerald shiner (Notropis atherinoides), common shiner (Luxilus cornutus), spottail shiner (N. hudsonius), northern redbelly dace (Chrosomus eos), bluntnose minnow (Pimephales notatus), fallfish (Semotilus corporalis), pearl dace (Margariscus margarita), central mud minnow (Umbra limi), chain pickerel (Esox niger), channel catfish (Ictalurus punctatus), margined madtom (Noturus insignis), redbreasted sunfish (Lepomis auritus), black crappie (Pomoxis nigromaculatus), smallmouth bass (Micropterus dolomieu) and yellow perch (Perca flavescens). A number of these fish were primarily lentic species (emerald shiner, spottail shiner, chain pickerel, channel catfish, redbreasted sunfish, black crappie, and yellow perch) and were only found in the stream mouths or in association with watershed lakes.

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DISCUSSION

Fish species richness in Otsego Lake's watershed was strongly correlated with drainage area of the individual streams. The correlation between species richness and drainage basin size appears to be based on the fact that as watershed size increases, habitat diversity and complexity also increase (Eadie et. al. 1986, Hugueny 1989, Gratwicke and Speight 2005). However, other factors were certainly at work here. Stream drainage basin is also strongly correlated with stream order, stream size, stream length and discharge (Harrel et al. 1967, Platts, 1979).

Figure 2. The relationship between drainage acreage and fish species richness in the Otsego Lakes watershed.

Confounding this study was the fact that access to the full drainage basin was lacking for most of the streams studied. Access to the upper portions of the drainage basins along the west side of Otsego Lake was severely restricted by elevated culverts at road crossings (Hayden Creek, White Cr./Trout Brook, LeatherstockingCreek, Brookwood Creek, Mohican Creek, Glimmerglen Creek, and Three Mile Point Stream), dams (Cripple Creek and Hayden Brook) and waterfalls (Leatherstocking Brook). Species richness was much higher near the lake and below the insurmountable barriers. For example, in Leatherstocking Creek only four species were found above the Route-80 culvert, while 19 species were found in the much smaller reach below this obstruction (Hayes 1990, Hakala 1994). In Trout Brook, five species were found above the road crossing, while 14 species were found below.

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Other environmental issues impacted the relationship between species richness and drainage basin. Mount Wellington stream was severely channelized and access to Otsego Lake was restricted by the passage of the stream through a long pipe. A watershed of its size (1,899 acres) would be expected to hold at least 8 species of fish. Instead, only two species were found, creek chubs and largemouth bass (which are more often associated with standing water than flowing water).

GIS can be a powerful tool in studying fisheries distributions and aquatic ecosystems (Valavanis et al. 2004). In setting up the data base it was clear that some streams had not been thoroughly surveyed, and recent data were lacking from a number of other streams. In fact, most streams have not been surveyed in the last 20 years. Recent surveys have discovered new species and expanding distributions of others (Jamieson et al. 2005, Somerville et al. 2005). More surveys of the fish fauna in the Otsego Lake watershed should be conducted in the near future.

ACKNOWLEDGEMENTS

Kevin Poole, Henry Whitebeck and Joseph Lydon assisted with ArcGIS map production and assisted in the survey of Glimmerglen Stream; Mark Cornwell and his fisheries management class conducted the survey of Mount Wellington Stream reported in this study. SUNY Oneonta’s Biological Field Station and SUNY Cobleskill Fisheries & Wildlife Department provided equipment and assistance for this study.

LITERATURE CITED

Barila, T.V., R.D. Williams and J.R. Stauffer, Jr. 1981. The influence of stream order and selected stream bed parameters on fish diversity in Raystown Branch, Susquehanna River drainage, Pennsylvania. J. of Applied Ecology 18: 125-131.

Bassista,T.P. and J.R. Foster. 1995. Relative abundance and species composition of fish in

Shadow Brook, Otsego County, New York. In 27th Ann. Rept. (1994). SUNY Oneonta Biol. Field Station. SUNY Oneonta. pp. 37-44.

Eadie J., T.A. Hurly, R.D. Montgomerie, K,L. Teather. 1986. Lakes and Rivers as Islands:

Species-area relationships in the fish faunas of Ontario. Environmental Biology of Fishes 15(2): 81-89

Foster, J.R. 1996. The fish fauna of the Otsego Lake watershed. In 28th Ann. Rept.(1995).

SUNY Oneonta Biol. Field Station. SUNY Oneonta. p.187-201. Gratwicke, B. and M.R. Speight 2005. The relationship between fish species richness,

abundance, and habitat complexity in a range of shallow tropical marine habitats. J. of Fish Biol. 66: 650-657

196

Hakala, J.P. 1994. Stream ecology of Leatherstocking Creek immediately following planting of riparian vegetation (year-0). In 26th Ann. Rept.(1993). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. p. 171-185.

Harrel, R.C., B..J. Davis and T.C. Dorris. 1967. Stream order and species diversity of fishes in

an intermittent Oklahoma stream. Am. Mid. Nat. 78: 428-436. Hayes, S.A. 1989. Preliminary fish survey of the Otsego Lake watershed. In 22nd Ann. Rept.

(1989).SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. p. 88-89.

Hayes, S. A. 1990. Preliminary survey of the fisheries ecology of Leatherstocking Creek. In 23rd Ann. Rept. (1990). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta. p. 37-51.

Harman, W.N., L.P. Sohacki, M.F. Albright, and D.L. Rosen. 1997. The State of Otsego

Lake, 1936-1996. Occasional Paper #30. SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Hugueny B, 1989. West African rivers as biogeographic islands: species richness of fish

communities. Oecologia 79(2): 236-243 Jamieson S.R., T.J. Somerville and J.R. Foster. 2005. The fish fauna of Weaver and Young Lake

tributaries, with the first record of the brook stickleback (Culaea inconstans) in the Otsego Lake watershed. In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta. SUNY Oneonta.

Miner, M.M. 1997. A fisheries survey of Cripple Creek. In 29th Ann. Rept. (1996). SUNY

Oneonta Biol. Fld. Sta. SUNY Oneonta. p 120-125. Platts, W.S. 1979. Relationships among stream order, fish populations, and aquatic

geomorphology in an Idaho river drainage. Fisheries 4(2): 5-9. Reynolds, R.J., J.C. Lydon and J.R. Foster. 2011. Fish faunal changes in Otsego Lake’s

Shadow Brook watershed following application of best management practices. In 43rd Ann. Rept. (2010) SUNY Oneonta Bio. Field. Station. SUNY Oneonta. p 191-200.

Somerville T.J., S.R. Jamieson and J.R. Foster. 2005. The invasion of the central mudminnow. (Umbra limi) into the Otsego Lake Watershed. In 37th Annual Report (2004). SUNY

Oneonta Biol. Fld. Sta. Valavanis V.D., S. Georgakarakos, A. Kapantagakis, A. Palialexis and I. Katara. 2004. A GIS

environmental modeling approach to essential fish habitat designation. Ecological Modeling 178(3-4): 417-427

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1 Fisheries & Aquaculture Student, Fisheries & Wildlife Dept., SUNY Cobleskill. 2 BFS Visiting Researcher, Fisheries & Wildlife Dept., SUNY Cobleskill. 3 R. C. MacWatters Intern in Aquatic Sciences, 2007. Fisheries & Wildlife Dept., SUNY Cobleskill.

Spine punching: An effective way of marking spiny-rayed fish

Anthony Bruno1, John R. Foster2 and Joe C. Lydon3

Abstract: The effectiveness of spine punching as a technique for marking spiny rayed fish was examined using Otsego Lake walleye tagged with a variety of methods beginning in 2008. Spine punching proved to be cheap and easy to apply. Spine punches were retained extremely well and were easy to detect 4 years later. No negative impacts on survival and condition were found. Utilizing different spines to punch provided a system for unique identification. Spine punching appears to be one of the most effective techniques for marking spiny rayed fish.

INTRODUCTION To be effective, fish tagging methods must be cheap, long lasting, easy to identify, easy

to apply and have little negative effects on fish. One of the most common ways to mark fish is fin clipping. It has proven to be effective and cheap (Zerrenner et al. 1997, Thompson et. al. 2005), but has negative impacts on fish growth and survival (Bumgarner et al. 2009, Coble 1971, Shetter 1967). Numbered jaw tags have the advantage of allowing the fish to have a unique identification number, but they hinder the growth (Deroche 1963, Shetter 1967, Zerrenner et al. 1997), survival (Zerrenner et al 1997) and are frequently lost (Newman & Hoff 1998, Crawley 2009). Visual implant elastomer (VIE) tags have a low mortality rate (Close 2000, Zerrenner et al. 1997, Thompson et al. 2005) and a long retention time (Close 2000, FitzGerald et al. 2004). However, recently tagged fish can lose VIE tags at a high rate (Bailey et al. 1998) and while VIE tags can be quickly applied to fish (Close 2000), they are relatively expensive (Thompson et al 2005). Unfortunately all existing tagging and marking methods have problems that limit their usefulness.

The utilization of a hole punch to mark soft rayed fins has been used for short-term

identification in studies determining population size (Guy et al. 1996). Hole punching is fast and cheap, but the limited number of fins provide limited opportunities to vary the punches. Further, while hole punches are easy to detect over the short term, fins must be closely examined for long term detection of this mark (Crawley 2009). A modification of the fin punching technique whereby the dorsal fin spines are punched has the potential of overcoming some of the limitations of soft fin punches. Spine punching is expected to retain the advantages of low cost and ease of application, but may have the distinct advantage of ease of long term detection. Additionally, fish can be given a unique identifying mark by punching different spines or spine combinations.

The goal of this study was to determine if spine punching is an effective way of marking

spiny-rayed fish. The objective was to determine the ease of detection years after its application, and determine if spine punching reduces survival and condition.

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MATERIALS & METHODS Walleye were collected and examined from Shadow Brook, Hayden Creek and Cripple

Creek, Otsego County, New York (Figure 1). Fish were captured 12, 14, 15 April 2011, from 2100 to 2300 hours. Follow-up sampling was carried out in April 2012.

Figure 1. Otsego Lake and its main tributaries, with arrows showing the walleye collection sites utilized in this study.

Walleye were collected by night electrofishing, with a Haltech (HT-2000) electro-fisher.

Stunned fish were placed in totes, individually measured, sexed, and checked for ripeness. Then they were examined for third and fifth dorsal spine punches, anal fin punches, fin clips, jaw tags, and VIE tags posterior to left eye and on the isthmus. Tagging locations examined corresponded to those utilized in previous studies (Table 1).

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Table 1. Number of walleye marked each year with each marking technique.

Marking Number of Fish Marked

Marking Year

Source

3rd Dorsal Spine Punch 628 2008 Lydon et al. 2009

Jaw Tag 490 2008 Lydon et al. 2009

VIE Tag Posterior Left Eye 628 2008 Lydon et al. 2009

Anal Fin Hole Punch 320 2009 Peck et al. 2010

VIE Tag Isthmus 320 2009 Peck et al. 2010

5th Dorsal Spine Punch 588 2010 Crawley et al. 2010

A short term (81 day) study was conducted to determine the impact of spine punching on

condition and survivability. In the aquaponics greenhouse at the State University of New York at Cobleskill, six, 500 gallon closed recirculation tanks were stocked with 235 tilapia ranging from 120-350 grams. A random sample of fifty fish from each tank was measured, weighed and then given a spine punch in their dorsal fin corresponding to their tank number. Fish from tank one were given a spine punch in the third dorsal spine, fish from tank two received a spine punch in the fourth dorsal spine and so on. Fish were again weighed and measured after 81 days and the condition and mortalities of marked and unmarked fish were recorded.

RESULTS Of the 462 walleye examined in 2011, 154 had one or more tags (Table 2). All walleye

receiving a 3rd spine hole punch retained the mark. Since the fish receiving a 5th spine punch had not received a second mark there was no way of determining if this punch was missed or lost. Spine punch retention was higher than VIE, jaw tagging and soft fin punching (Table 2).

Spine punched tilapia did not have a higher mortality (.005% N=600) over 81 days than

did tilapia that did not receive a spine punch (.009% N= 1110). The condition of tilapia receiving a spine punch (K = 1.99) did not differ from tilapia that did not receive a spine punch (K = 1.96).

Walleye marked with an anal fin punch were difficult to detect visually. Often the anal

fin had to be felt to find the scar from the healed hole. VIE tags also require a fairly extensive search with a black light, since the VIE tag had a tendency to fragment, fade or become lost. Jaw tags were easily detected.

Spine punches were remarkably easy to detect even after two (Figure 2) and four (Figure

3) years. Spines either reconnected at an oblique angle, or there was a gap in the spine where the

200

punch had occurred. The dorsal fin had to be erected during the examination, but the time of detection occurred faster than with the VIE tags and the anal fin punch (Figure 3). Table 2. The 2011 recapture data showing mark retention in walleye marked during a particular year.

Marking # RecapturedWith Marks

Per Cent Retained

Marking Year

3rd Dorsal Spine Punch 27 100% 2008

Jaw Tag 14 93% 2008

VIE Tag Posterior Left Eye 24 88% 2008

Anal Fin Hole Punch 46 98% 2009

VIE Tag Isthmus 32 56% 2009

5th Dorsal Spine Punch 102 - 2010

Figure 2. Two years after the 5th dorsal spine was punched it was easy to detect.

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Figure 3. Four years after the 3rd dorsal spine was punched it was easily detectable.

DISCUSSION An effective method of marking and tagging fish is critical for fisheries research and

management (Hilborn et al. 1990). Fish marking is used to determine population abundance, year class strength, harvest rates, growth, survival, homing and migrations (Hilborn et al. 1990, Guy et al. 1996). Tag retention, impact on growth and survival and the ease and cost of application and detection are critical considerations in evaluating marking and tagging methods.

One hundred percent of the walleye retained the 3rd spine dorsal punch after three years.

Even after four years the spine punch in the 3rd dorsal spine was easily visible. In contrast, the three-year retention of the VIE tag posterior to the left eye was retained only 88% of the time. Further, there was some difficulty distinguishing between the green and yellow VIE tags under the ultraviolet light. The VIE tag on the isthmus was even harder to detect and it’s retention after two years was only 56%. Inexperience in tagging fish with VIE tags may have explain these lower rates of tag detention (FitzGerald et al. 2004, Olsen et al. 2001, Close 2000). Similarly, after two years the anal ray punch needed to be viewed more closely than the spine punches in order to detect it, even though it was retained 98% of the time. Like VIE tags, jaw tags took a

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long time to apply, but had a 93% retention rate over 3 years. These three year retention rates were higher than reported for the same fish after one year (Crawley et al. 2009).

In this first study to test spine punching as marking technique for spiny rayed fish, spine

punching proved to be cheap and easy to apply. Further, after four years spine punches were retained extremely well, and had no negative impact on condition or survival. The choice of spines to punch also provided a system for unique identification. For these reasons, spine punching appears to be one of the most effective techniques for marking spiny rayed fish.

ACKNOWLEDGEMENTS SUNY Cobleskill fisheries students volunteered many hours to help complete this study.

Equipment for this study was supplied by the Fisheries & Wildlife Department of SUNY Cobleskill.

LITERATURE CITED

Bailey, R. E., J. R. Irvine, F. C. Dalziel, and T. C. Nelson.1998. Evaluations of visible implant

fluorescent tags for marking Coho salmon smolts. North Am. J. of Fish. Manage. 18:191–196.

Bumgarner, J.D., M.L. Schuck, and H.L. Blankenship. 2009. Returns of hatchery steelhead with

different fin clips and coded wire tag lengths. Washington Department of Fish and Wildlife. North Am. J. of Fish. Manage. 29:903-913.

Churchill, W.S. 1963. The effect of fin removal on survival, growth, and vulnerability to capture

of stocked walleye fingerlings. Transactions of the Am. Fish. Soc. 92:298–300. Close, T.L. 2000. Detection and retention of postocular visible implant elastomer in fingerling

rainbow trout. North Am. J. of Fish. Manage. 20:542–545. Coble, D.W. 1971. Effects of fin clipping and other factors on survival and growth of

smallmouth bass. Transactions of the Am. Fish. Soc. 3:460-473. Crawley, W.T., J.C. Lydon, J.R. Foster, D. Johns, K.J. Poole and M.D. Cornwell. 2010. The

Efficacy of Jaw tag, visual implant elastomer, fin clip, and fin punch in Otsego Lake, NY walleye (Sander vitreus) studies. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

DeRoche. S.E. 1963. Slowed growth of lake trout following tagging. Transactions of the Am.

Fish. Soc. Vol. 92:185-186. Fitzgerald, J.L., T.F. Sheehan, and J.F. Kocik. 2004. Visibility of visual implant elastomer tags

in Atlantic salmon reared for two years in marine net-pens. North Am. J. of Fish. Manage. 24:1,222-227.

203

Hilborn. R., C.J. Walters, and D.B. Jester, Jr. 1990. Value of fish marking in fisheries management. In N. C. Parker and five coeditors. Fishmarking techniques. Am. Fish. Soc. Symposium 7. Bethesda. Maryland.

Guy, C.S., H.L. Blankenship and L.A. Nielsen. 1996. Tagging and marking. In B. R. Murphy

and D.W. Willis, editors. Fisheries Techniques, 2nd edition. Am. Fish. Soc., Bethesda, Maryland.

Lydon, J.C., M.D. Cornwell, J.R. Foster, T.E. Brooking and S. Cavaliere. 2009. Mark-recapture

and catch per unit effort measures of walleye (Sander vitreus) abundance in Otsego Lake, NY. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Stat., SUNY Oneonta.

Newman, S.P. and M.H. Hoff. 1998. Estimates of loss rates of jaw tags on walleyes. Am. Fish.

Soc. 18:202-205. Olsen, E.M. and L.A. Vollestad. 2001. An evaluation of visible implant elastomer for marking

age-0 brown trout. North Am. J. of Fish. Manage. 21: 967-970. Peck, D. J., J.R. Foster, J.C. Lydon, K.J Poole and M.D. Cornwell. 2010. The effectiveness of

spring stream electro-fishing, trap netting and lake electro-fishing for determining walleye (Sander vitreus) abundance in Otsego Lake, NY. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Shetter, D.S. 1967. Effects of jaw tags and fin excision upon the growth, survival, and exploition

of hatchery rainbow trout fingerlings in Michigan. Transaction of the Am. Fish. Soc. 94: 394-399.

Thompson, J. M., P.S. Hirethota, and B.T. Eggold. 2005. A comparison of elastomer marks and

fin clips as marking techniques for walleye. North Am. J. of Fish. Manage. 25:308–315.

Zerrenner, A., D.C. Josephson, and C.C. Krueger. 1997. Growth, mortality, and mark retention of hatchery brook trout marked with visible implant tags, jaw tags, and adipose fin clips. The Progressive Fish-Culturist 59: 241-245.

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DEC Invasive Species Eradication and Control Grant FINAL REPORT1

W.N. Harman, H.A. Waterfield and M.F. Albright

Site description: 40-acre wetland in the City of Oneonta draining to the Susquehanna River. In 2008, water chestnut occupied an area of approximately 4 acres of open-water. Growth was very dense. Purple loosestrife was the dominant emergent plant in the wetland. Water Chestnut Eradication Strategy: Herbicide applications (2, 4-D) in densely populated areas, hand-pulling of satellite populations prior to fruit-production each year. Additional water quality and nutrient data were collected in order to assess the response in general water quality conditions to the herbicide application. 2008-2011 Activities: Herbicide applications to control this population were conducted prior to this grant in 2006 and 2007 and continued with funding from this grant in 2008, 2009, and 2011 (Figure 1). Hand-pulling of satellite patches and individual plants was done each year via canoe (Figure 2). Assessment of success: the combination of herbicide treatment and hand-pulling of plants was hugely effective in reducing the population from 2007 to 2010. Native floating-leaved plants were rebounding (Figure 3). Logistical complications resulted in a “missed” herbicide application during the 2010 growing season (described below) and subsequent rebound of the population (also see Figure 1). Following the 2011 application a second growth of plants was observed in mid-August. These plants were also producing fruits; a major hand-pulling event was held in mid-September, though growth was so prolific that all harvest off all plants was not achievable. Spring 2010 assessments will give insight into the viability of these fruits produced late in the growing season.

Problems encountered: coordination of efforts among multiple parties proved challenging. The herbicide application permitting process was chronically delayed by the landowner; thus annual permits were not approved until late in the season, following the production of fruiting bodies. Nuts were somewhat advanced in development and it was unclear whether or not the herbicide treatment would be effective or successful; the 2010 herbicide application was postponed until 2011, with the intent being to treat earlier in the season to ensure treatment before fruit production. This missed herbicide application resulted in high fruit production in 2010 and vigorous growth of individuals and expansion of moderately-sized patches were observed in 2011. Though the 2011 application area was larger than in previous years (Figure 1), the density of plants in this area was substantially reduced from earlier years (Figure 4). Hand-pulling efforts have been very successful in reducing the spread of water chestnut to areas away from the main, dense patches, though would be more appropriate for a water body that is either high-profile or has a larger public base to draw from in soliciting volunteers. Purple Loosestrife Control Strategy: Galerucella spp. beetles were released in the wetland to serve as a biocontrol agent. Galerucella are leaf-eating beetles that consume only purple loosestrife at all life stages. 2008-2011 Activities: Galerucella spp. were introduced to the marsh in 2006. In 2008, purple loosestrife in the northeastern portion of the marsh was heavily damaged by the beetles and produced few inflorescences; plants in the southwestern portion of the marsh remained healthy. In 2009 dead standing loosestrife could be seen from the railroad access; plants were heavily damaged throughout the wetland and inflorescences were rare. In August, new shoots of purple loosestrife could be seen growing up through standing dead loosestrife stems from 2008. In 2010, loosestrife was damaged throughout the wetland, evidence that beetle distribution was increasing within the area. In 2011, the beetles were observed in early-summer, though damage to loosestrife was reduced and the plants were able to produce flowers. This was also the case elsewhere in the county where loosestrife is controlled by Galerucella. 1 Final report to NYS DEC for a 2007-2011grant for water chestnut eradication and purple loosestrife control activities.

205

h

Figure 1: Area of wapattern in 2011 Appl

Figure 2. Exampleloaded with plants

206

2007 Patc

a

ter chestnut patch in 2007 and 2008; ication Area represents a drastic redu

of isolated plants and patches targeteduring a hand-pulling event (right).

2011 Application Are

2008 Patch

2009 Application Area

herbicide application areas in 2009 and 2011. Broken ction in density of plants.

d for hand-pulling efforts (Left) and canoes

Figure 3. Native floating-leaved plants in 2010 (left) and 2011 (right) making a come-back in the open water areas of the marsh. In 2011, the expanded water chestnut patch included areas that were dominated by rebounding native plants in 2010.

Figure 4: Main water chestnut patch in 2006 (left) and 2011 (right).

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Intestinal damage in locally occurring game fish infected with the

acanthocephalan, Leptorhynchoides thecatus

F. B. Reyda1, C. Lange

2, J. Sheehan

2, U. Habal

2, D. Willsey

2, L. Laraque

2, & M. O’Rourke

2

INTRODUCTION

Recent survey work on the intestinal parasites of Otsego Lake fishes (Reyda, 2010;

Szmygiel and Reyda, 2011) has demonstrated that the acanthocephalan Leptorhynchoides

thecatus is common in several fish species of potential economic importance in Otsego Lake and

nearby waters. Leptorhynchoides thecatus appears to have a very low level of host specificity

and has been found in the locally occurring centrarchid species, Largemouth bass, Smallmouth

bass, Pumpkinseed, Redbreast sunfish and Rock bass. In addition, L. thecatus has been

encountered in Yellow perch, Eurasian carp, Chain pickerel, White sucker, and Walleye in

Otsego Lake. The low level of host specificity in L. thecatus has been previously reported in the

literature (DeGiusti, 1949).

Acanthocephalans attach to the host intestinal wall using its hooked proboscis, causing

extensive tissue damage and potential fatality in various vertebrates (Nickol and Crompton,

1983). The pathological effects of L. thecatus can be seen microscopically at the point of direct

attachment between the proboscis and host intestine. Extent of pathology depends on the depth

of penetration and the amount of worms present in an infected intestine, but has only been

documented in a single previous study (Venard and Warfel, 1953). Given its common local

occurrence, the current histological study was undertaken to address the potential pathology of L.

thecatus to its hosts by focusing on infections in Smallmouth bass (Micropterus dolomieu), and

Yellow perch (Perca flavescens).

METHODS

The fish specimens used for this study were collected as follows: Ten Yellow perch were

collected in February 2011 in Canadarago Lake Otsego County, New York, by ice fishing. A

single Smallmouth bass was collected in September 2011 from Brookwood in Otsego Lake,

Otsego County, New York, by hook and line. Fish were immediately returned to the Biological

Field Station Hop House Lab in Springfield, New York and stabilized in aquaria. Fish were

sacrificed via prolonged anesthetization with FinQuel®

, or via pithing. The fish were then

necropsied immediately following measurement of total length in centimeters.

During each necropsy the intestine and the pyloric cecae (if present) were isolated from

the rest of the abdominal cavity with an anterior incision at the stomach and a posterior incision

at the anus. The intestine was then opened with a single longitudinal incision and the pyloric

cecae were opened with several incisions. The intestines and pyloric cecae were subsequently

fixed in 10% formalin, or, in the case of the Smallmouth bass specimen, in 10% neutral buffered

1 Assistant Professor of Invertebrate Zoology and Researcher, Biology Department and Biological Field Station,

SUNY Oneonta 2 SUNY Oneonta Undergraduate Student, Biology Department, SUNY Oneonta

208

formalin. Pieces of intestinal or cecal tissue with attached L. thecatus were cut into ~3–4 mm

square plugs.

Histological sections were prepared by conventional methods. First, tissue plugs with L.

thecatus were dehydrated in a graded ethanol series, followed by xylene, xylene mixed with

paraplast, and ultimately paraplast at 56C for a minimum of eight hours for maximum infiltration

of paraplast into the tissue. Tissue plugs were embedded in pure paraplast and sectioned at 10

micron intervals using an Olympus CUT 4060 microtome. Sections were dried onto warmed

slides using warmed Sodium silicate. Once dry, slides were stained with Delafield’s

Hematoxylin and counterstained with Eosin, and subsequently mounted under long coverslips

with Canada balsam. Once dry, slides were examined with an Olympus CX 41 compound

microscope and images were captured with the attached Luminera Infinity 2 Digital Microscope

Camera.

Figure 1. Light micrographs of histological sections of Yellow perch intestine. 1A, Uninfected

intestine. 1B, 1C, Proboscis of Leptorhynchoides thecatus embedded into intestinal layers.

209

RESULTS

Although many of the Yellow perch and Smallmouth bass we encountered during survey

work (e.g., Szmygiel and Reyda, 2011) were infected with L. thecatus, a single Yellow perch, 32

cm in length from Canadarago Lake, and a single Smallmouth bass, 44 cm in length from Otsego

Lake, were selected for intensive histological analysis in which multiple tissue plugs were

sectioned. These two specimens (Yellow perch, FR11_1; Smallmouth bass, FR11_60) were

chosen because they were heavily infected, containing at least 30 individual attached L. thecatus.

A portion of uninfected intestinal tissue of Yellow perch is shown in Figure 1A for

comparison. Figure 1A illustrates the tissue layers of the intestine, including the mucosal layer,

consisting of microvilli containing epithelial and goblet cells and underlying lamina propria; the

submucosal layer; the muscular coat; and the serosa of connective tissue. This can be compared

with Figures 1B and 1C in which the proboscis of L. thecatus is visible. Damage to the mucosal

wall is visible in Figures 1B and 1C. Epithelial cells are torn and disrupted, and the proboscis is

embedded within the underlying lamina propria. The “gap” in Figures 1B and 1C is thought to be

an artifact (see discussion), but surrounding the gap a proliferation of erythrocytes and

leukocytes are visible. It seems that in these infections the proboscis only penetrates the

muscosal layer; it does not reach the submucosa.

Figure 2. Light micrographs of histological sections of Smallmouth bass digestive system. 2A,

Uninfected pyloric cecum, sagittal section. 2B, Proboscis of Leptorhynchoides thecatus

embedded into intestinal layers, with trunk of worm also visible.

210

Figure 2 (continued). 2C, Higher magnification view of L. thecatus proboscis shown in 2B. 2D,

Another plane of section of same L. thecatus specimen pictured in 2B, 2C.

211

A portion of uninfected pyloric cecum of Smallmouth bass is shown as a sagittal section

in Figure 2A, illustrating the extent of folding and ridges that characterize the surface of the

pyloric cecum, a pattern also observed in the intestine. The remaining figures are cross sections

of the intestinal wall with a proboscis of L. thecatus attached. In Figures 2B, 2C and 2D the

proboscis is embedded deep into the muscosal wall, disrupting the microvilli and penetrating the

lamina propria. In Figures 2B and 2D the actual trunk of the worm is also visible, nestled

between microvilli. Again, a “gap” is visible in each of these figures, but this is thought to be an

artifact. The high magnification view of the proboscis in Figure 2C illustrates a proliferation of

erythrocytes and leukocytes surrounding the area of proboscis attachment. Figure 2C also clearly

illustrates the individual hooks on the proboscis. These hooks are the namesake of the Phylum

Acanthocephala, the “thorny-headed worms”. Figures 2B and 2D illustrate the overall extent of

proboscis penetration. In both examples, the proboscis has fully penetrated the mucosal layer,

and barely reaches, but does not penetrate, the submucosal layer.

DISCUSSION

One of several technical hurdles encountered in this study was the presence of “gaps” in

the histological sections of both Yellow perch and Smallmouth bass intestine. These gaps were

observed between the proboscis and the host tissue to which it was attached. This apparent

retraction of the proboscis from the host tissue has been observed previously (Venard and

Warfel, 1953; Bullock, 1963) and is considered an artifact of fixation that occurs when the

parasite is killed at the time of preservation. That is, there would be no gap in an actual infection

of L. thecatus in a living Yellow perch or Smallmouth bass because the parasite by definition

attached to the intestinal wall with its hooks. Evidence of this is apparent in that the tissue

surrounding the gaps in Figures 1B, 1C, 2B, 2C, and 2D is damaged, presumably from contact

with the proboscis.

The intestinal damage observed in this study is extensive at the level of the mucosal

layer. Although no cases of full intestinal perforation were observed, the tearing of epithelial

cells and the disruption of microvilli and the underlying lamina propria raises the possibility that

secondary infections with bacteria could result.

Although parasitic attachment may not be the sole contributor to host animal death

(Nickol and Crompton, 1983), the effects based on the histopathology validate that

acanthocephalans can impair host health (Bullock, 1963, this study), though this may be difficult

to measure in wild populations.

CONCLUSION

The documented damage caused by L. thecatus to the intestines of Yellow perch and

Smallmouth bass raises the possibility that acanthocephalans play a role in the variability of

populations of economically important game fish species in Otsego Lake and nearby waters.

212

ACKNOWLEDGEMENTS

Timothy Pokorny (SUNY BFS), Michael Schallert (Ridgefield Springs, New York),

Daniel Henning (Chicago, Illinois), and Dr. Allan Green (SUNY Oneonta) kindly provided

several fish specimens for this study. Thanks to Stephen Daniels, Janine Caira (University of

Connecticut), and to Allen Anderson (SUNY Oneonta) for offering technical advice. We are

grateful to Allison Schulman for providing some of the sections for this study, and to Janine

Caira and her students for hosting us during some of the histological work of this project. This

project was supported with funds from a Student Research Grant from the SUNY Oneonta

Research Foundation awarded to U. Habal., D. Willsey., L. Laraque., and M. O’Rourke, and

with a Teaching, Learning and Technology Center Fellowship awarded to F. B. Reyda.

REFERENCES

Bullock, W. L., 1963. Intestinal Histology of some salmonid fishes with particular reference to

the histopathology of acanthocephalan infections. Journal of Morphology. 112: 23-44.

DeGiusti, D. L. 1949. The life cycle of Leptorhynchoides thecatus, an acanthocephalan of fish.

Journal of Parasitology. 35: 437-460.

Lincicome, D. R., and H. J. VanCleave 1949. Distribution of Leptorhynchoides thecatus, a

common acanthocephalan parasite in fishes. American Midland Naturalist. 41(2): 421-

431.

Nickol, B. B., and D. W. T. Crompton. 1985. Biology of the Acanthocephala. Cambridge

University Press, Cambridge, England.

Reyda, F. B. 2010. Parasitic worms of fishes of Otsego Lake and nearby water bodies, 2009. In

42nd

Annual Report of the SUNY Oneonta Biological Field Station. Pp. 276–281.

Szmygiel, C., and F. B. Reyda. 2011. A survey of the parasites of Smallmouth bass (Micropterus

dolomieu) In 43rd

Annual Report of the SUNY Oneonta Biological Field Station. Pp.

235–240.

Venard, C. E., and J. H. Warfel. 1953. Some effects of two species of Acanthocephala on the

alimentary canal of the largemouth bass. Journal of Parasitology. 39: 187-190.

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BFS Technical Report #31 AQUATIC MACROPHYTE

MANAGEMENT PLAN FACILITATION LAKE MORAINE, MADISON COUNTY, NY

2011 1. MACROPHYTE BIOMASS MONITORING 2. WATER QUALITY ANALYSIS

WILLARD N. HARMAN MATTHEW F. ALBRIGHT

OWEN ZAENGLE

SUNY Oneonta Biological Field Station

5838 St. Hwy. 80 Cooperstown, NY 13326

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BACKGROUND (From Harman et al. 2010)

Located in Madison County NY, Moraine Lake (42o 50’ 47” N, 75o 31’ 39” W) was

formed by a deposited glacial moraine damming a valley. The lake, which has been artificially raised, is divided into two basins separated by a causeway and interconnected by a submerged culvert. The north basin is approximately 79 acres, has a mean depth of 1.1m, and a maximum depth 3.7m. The south basin occupies 182 acres, has a mean depth of 5.4m, and a maximum depth of 13.7m. Most of the recreational activities such as fishing, boating and swimming take place in the south basin (Harman et al. 1997).

Moraine Lake has been regarded as meso-eutrophic due to the high productivity of algal and macrophytic plants, low transparency, and depleting levels of dissolved oxygen in the hypolimnion during summer stratification. Developments of lakeside residences and nearby agricultural activities are believed to have contributed to the current productivity status of the upper and lower basins (Anon. 1991). Nutrient loading as a result of faulty septic systems from the residences are believed to be a significant source of the problem in nutrient introduction (Harman et al. 1998). Many of the systems are out of date, undersized, and extremely close to the lake (Brown et al. 1983). Furthermore, soils surrounding the lake have poor percolation rates, steep slopes, shallow depths to bedrock, and fractured bedrock make the lake vulnerable to nutrient loading (Harman et al. 2008).

INTRODUCTION

The aquatic macrophyte communities of Moraine Lake have been monitored by the

SUNY Oneonta Biological Field Station (BFS) since 1997. The purpose of monitoring these plant communities has historically been directed towards controlling Eurasian water-milfoil (Myriophyllum spicatum), though in recent years the expansion of the exotic starry stonewort (Nitellopsis obtusa) has been a matter of increased focus. Eurasian water-milfoil is an invasive species that grows rapidly and its extensive canopies cause problems for recreation and other species growth (Borman et al. 1999). Numerous methods of control have been applied to reduce the abundance of Eurasian water-milfoil (Harman et al. 2006). Since 1998, efforts have focused primarily on applications of Sonar®, which has been demonstrated to control Eurasian water-milfoil with some specificity. The goal of managing the Eurasian water-milfoil in the past has been to achieve a balance of species (Lembi 2000, Harman et al. 2008). Most recent activities have included a Sonar® application in the north basin in 2010 and in the south basin in 2011.

These efforts to control Eurasian water-milfoil have been effective in reducing the

biomass of this species in relation to the overall biomass of aquatic plants in the Lake. However, currently Moraine Lake is experiencing a state of productivity whereby macrophytes other than Eurasian water-milfoil and macroalgae, such as coontail (Ceratophyllum demersum), sago pondweed (Stuckenia pectinata) and starry stonewort (Nitellopsis obtusa) are producing biomass that may be a threat to the recreational goals of the users of the Lake. It would be timely to address nutrient loading in addition to controlling plant mass via Sonar® application and other methods.

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MATERIALS AND METHODS

Sampling took place 6 June, 7 July, 27 July and 7 October. Five collection sites were sampled, two in the north basin and three from the south basin (Figure 1). The sampling method used was the Point Intercept Rake Toss Relative Abundance Method (PIRTRAM) (Lord and Johnson 2006). It was evaluated in 2008 by comparing the PIRTRAM and dry weight methods such that the rake toss method “could prove useful, if not too much value is placed on actual abundance estimates. …an adequate number of replicate samples could provide insight into species dominance and extent related to exotic nuisance species as well as efforts to control them” (Harman et al. 2008).

For this method two heads of garden rakes were welded together and connected to a 10m

nylon cord. At each of the 5 sites, the rake was thrown out randomly 3 times. The rake was allowed to settle to the bottom of the lake and slowly pulled into the boat. Once in the boat, species were separated and each was assigned an abundance category. The 5 abundance categories are “no plants” (denoted by “Z”), “fingerful” (“T”= trace), “handful” (“S” = sparse), rakeful (“M” =medium), and “can’t bring into the boat” (“D” = dense). Table 1 provides biomass range estimates associated with each category. Each rake toss triplicate sample’s category was converted to its corresponding mid-point (Harman et al. 2008). The mid-points were averaged for each species. These species averages were then summed together to look at overall biomass at each site.

In each basin at the deepest location, water quality parameters were measured with a

YSI® multiprobe. From surface to substrate, temperature, dissolved oxygen, conductivity, pH, and ORP were measured. A water sample was taken from each basin and returned to the lab to be analyzed using the Lachat QuickChem FIA+Water Analyzer®. The ascorbic acid method following persulfate digestion (Liao and Marten 2001) was used to determine total phosphorus. For total nitrogen, the cadmium reduction method (Pritzlaff 2003) was used following peroxodisulfate digestion as described by Ebina et al. (1983). The phenolate method (Liao 2001) was used to measure ammonia and the cadmium reduction method (Pritzlaff 2003) for nitrate+nitrate-nitrogen. (Harman et al. 2008)

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Figure1. Bathymetric map of Moraine Lake, Madison County, NY. Contours in feet. WQ1 and WQ2 represent were water quality data were collected, sites 1-5 represent where plant biomass and rake toss methods were performed (Harman et al. 2008). Table 1. Categories, field measurements, midpoint of each category (g/m2) and dry weight ranges applied for the rake toss method and used to generate Tables 2-6 (Harman et al. 2008). Abundance Categories Field Measure Total Dry Weight (g/m^2) mid low high"Z" = no plants Nothing 0 0 0 0"T" = trace plants Fingerful .0001 - 2.000 1 0.0001 2"S" = sparse plants Handful 2.001 - 140.000 71 2.001 140"M" = medium plants Rakeful 140.001 - 230.000 185 140.001 230"D" = dense plants Can't bring in boat 230.001 - 450.000+ 340 230.001 450

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RESULTS

Plant Biomass

Tables 2-6 proved biomass estimates, by species, over the summer of 2011 for sites 1-5 at Moraine Lake. Eurasian water-milfoil density was generally low in the south basin sites throughout the summer (Tables 2-4). However, it, along with coontail, was abundant in the north basin throughout the summer (Tables 5 and 6). Of particular note is the continued dominance by starry stonewort (Nitellopsis obtusa) at sites 1 and 3; the biomass estimates given in Tables 2 and 4 undoubtedly underestimate actual values because masses of this plant would collapse and fall off the rake as it was being pulled into the boat. Beds of this plant were often so thick that the perception was that a false bottom existed over 1 m from the actual bottom.

Figures 2-6 graphically summarize the plant biomass contributed by starry stonewort

(Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species between 2008 and 2011. While not the original focus of study, starry stonewort is highlighted along with milfoil because it is also an exotic nuisance species and management efforts ought to focus upon control both species.

Table 2. Mean biomass (g/m2) category mid-points for each species found at Site 1 during 2011 sampling events.

Site 1 6/10/2011 7/7/2011 8/17/2011 10/7/2011 Myriophyllum spicatum Megalodonta beckii Zosterella dubia 0.33 0.67 Najas spp. Ceratophyllum demersum 0.33 Chara vulgaris 123.33 Vallisneria americana 0.33 0.33 Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 47.67 Potamogeton crispus 47.67 Potamogeton zosteriformis 0.33 24.33 0.33 Potamogeton pusillus Nitellopsis obtusa 24.00 123.33 0.33 46.67 Total 120.00 124.00 149.00 47.00

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Site 2 6/10/2011 7/7/2011 8/17/2011 10/7/2011

Myriophyllum spicatum 0.33 Megalodonta beckii Zosterella dubia 0.33 0.33 0.67 Najas spp. Ceratophyllum demersum 85.67 123.33 185.00 0.33 Chara vulgaris Vallisneria americana Elodea canadensis 0.33 Ranunculus aquatilis 24.33 Ranunculus trichophyllus Stuckenia pectinata 47.67 Potamogeton crispus 109.00 Potamogeton zosteriformis 0.33 0.33 Potamogeton pusillus Nitellopsis obtusa Total 268.00 123.67 185.67 0.66


Site 3 6/10/2011 7/7/2011 8/17/2011 10/7/2011 Myriophyllum spicatum 23.67 Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum Chara vulgaris Vallisneria americana Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 0.67 Potamogeton crispus 47.33 Potamogeton zosteriformis Potamogeton pusillus Nitellopsis obtusa 109.00 185.00 236.67 250.33 Total 180.67 185.00 236.67 250.33

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Site 4 6/10/2011 7/7/2011 8/17/2011 10/7/2011 Myriophyllum spicatum 24.33 0.67 47.67 47.67 Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 1.00 0.33 109.00 71.00 Chara vulgaris Vallisneria americana Elodea canadensis Ranunculus aquatilis 0.33 Ranunculus trichophyllus Stuckenia pectinata 0.33 1.00 Potamogeton crispus 85.33 24.33 Potamogeton zosteriformis 61.67 24.33 1.00 Potamogeton pusillus Nitellopsis obtusa Total 111.00 63.67 181.33 144.00


Site 5 6/10/2011 7/7/2011 8/17/2011 10/7/2011 Myriophyllum spicatum 47.67 0.67 24.00 71.00 Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 0.67 23.67 62.00 47.33 Chara vulgaris Vallisneria americana Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 24.33 47.67 0.33 Potamogeton crispus 71.00 36.00 0.67 Potamogeton zosteriformis 23.67 Potamogeton pusillus Nitellopsis obtusa Total 143.67 108.00 110.00 119.00

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Figure 2.Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011) and 2011, site 1 (see Figure 1 for site locations).

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Figure 3. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011) and 2011, site 2 (see Figure 1 for site locations).

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Figure 6. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011) and 2011, site 5 (see Figure 1 for site locations). Water Quality Analysis Water quality parameters over summer 2011 were comparable to those of recent years. In the south basin, waters below 10m were anoxic by the first sampling date (10 June). By 7 July waters below 8m were anoxic. Transparency was as high as 5.5m on 7 July and was 2.0m on 7 October. pH was typically between 7.0 and 8.5. Surface nitrite+nitrate concentrations were low, from below detection (<0.02 mg/l) to 0.38 mg/l. Surface total nitrogen ranged from 0.24 to 0.49 mg/l, and total phosphorus from 10 to 27 ug/l. In the shallower north basin, bottom waters were occasionally anoxic, though intermittent mixing was evident. pH ranged from 7.3 to 9.3. Surface nitrite+nitrate concentrations ranged from below detection to 0.46 mg/l, total nitrogen ranged from 0.41 to 0.89 mg/l and total phosphorus ranged from 16 to 47 ug/l.

DISCUSSION

2011 was the third year during which starry stonewort has been dominant where present (sites 1 and 3, the south end of the south basin and the eastern embayment at the north end of the south basin (see Figures 2 and 4)). It should be noted that its abundance is likely much higher than those figures imply due to difficulties related to measurement via the rake toss method. On a number of samples collected, masses of this species collapsed off the rake as the sample was lifted into the boat. It is not quickly spreading to other sites in that basin, and it has not yet been documented in the north basin. It has become a serious recreational pest in many lakes (i.e.,

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Pullman and Crawford 2010), and in Moraine Lake it likely will become increasingly common and problematic and may soon be considered the focus of management concerns.

REFERENCES

Anon. 1988. Madison County septic system survey. Madison County Planning Department, Wampsville, NY 13163.0

Borman, S., R. Korth, and J. Tempte. 1999. Through the looking glass. A field guide to aquatic

plants. Wisconsin Lakes Partnership. Crow, G. E. and C. B. Hellquist. 2000a. Aquatic and wetland plants of Northeastern North

America. V.1. Pteridophytes, gymnosperms, and angiosperms: dicotyledons. The University of Wisconsin Press.

Crow, G. E. and C. B. Hellquist. 2000b. Aquatic and wetland plants of Northeastern North

America. V.2. Angiosperms: monocotyledons. The University of Wisconsin Press. Fuller, R. 1997. Unpublished data. Colgate University, Hamilton, NY 13346. Harman, W.N. and M.F. Albright and T.F. Smith. 2011. Aquatic macrophyte management plan

facilitation, Lake Moraine, Madison, N.Y. 2010. Tech. Rept. #29. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N., M.F. Albright, H.A. Waterfield and M. Rubenstein. 2010. Aquatic macrophyte

management plan facilitation, Lake Moraine, Madison, N.Y. 2009. Tech. Rept. #27. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N. and M.F. Albright and L. Zach. 2009. Aquatic macrophyte management plan

facilitation, Lake Moraine, Madison, N.Y., 2008. Tech. Rept. #26. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W. N. and M. F. Albright, and C. M. Snyder. 2008. Aquatic macrophyte management

plan facilitation, Lake Moraine, Madison County, NY., 2007 Tech. Rept. #25. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W. N. and M. F. Albright, and A. Scorzafava. 2006. Aquatic macrophyte management

plan facilitation, Lake Moraine, Madison County, NY. Tech. Rept. #23. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright, P.H. Lord and M. E. Miller. 2002. Aquatic macrophyte

management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #13. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

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Harman, W. N. and M. F. Albright, P.H. Lord and M. Miller. 2000. Aquatic macrophyte management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #9. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright, P.H. Lord and D. King. 1998. Aquatic macrophyte

management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #5. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright. 1997. Aquatic macrophyte survey of Lake Moraine, Madison

County, summer 1997, as related to management efforts by Sonar ® application. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Lembi, C.A. 2000. Aquatic Plant Management. Purdue University, Cooperative Extension

Service. West Lafayette, IN 47907. Lord, P.H. and R.L. Johnson. 2006. Aquatic plant monitoring guidelines.

http://www.dec.ny.gov/docs/water_pdf/aquatic06.pdf NYS Department of Environmental Conservation, Water Division. A Primer on Aquatic Plant

Management in NYS. http://www.dec.ny.gov/docs/water_pdf/ch6p2.pdf. 8.12.2009. Pulman, G.D. and G. Crawford. 2010. A decade of starry stonewort in Michigan. Lakeline,

summer 2010. North American Lake Management Society.

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http://www.dec.ny.gov/docs/water_pdf/ch6p2.pdf. 8.12.2009