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Swimmers itch drivers in northern MI lakes
Thomas R. Raffel, Ph.D.
Department of Biological Sciences
Oakland University
Rochester, MI
Schistosomiasis:• 2-host life cycle (SNAILS)
• Exposure in water
• Human schistosomes (3 spp)• 2nd most important tropical disease worldwide
• 200-300 million people infected/yr; 800,000 deaths
• Avian schistosomes (12-15 spp)• Trying to infect birds
• Itchy bumps 1-2 days post-exposure
• Gradually fade over ~1 week
Adult worms (in blood vessel)
Trichobilharzia cercariapenetrating skin
• Trichobilharzia spp.• First described by Cort in
Douglas Lake (1928 )
Michigan: home of swimmer’s itch!
Physa integra
Stagnicola catescopium* (= Stagnicola emarginata)
Research Goals
1. Temporal dynamics
• Generate daily field data for cercaria abundance
• Test predictions for potential warning systems
2. Spatial distribution
• Identify landscape-level predictors of snail and parasite abundance
• Inform management decisions
• High day to day variation reported, but no daily
field data available for cercaria abundance
• Trematode biology is temperature-dependent
- Snail growth & reproductive rates
- Cercaria production rate
• Most studies ignore temperature fluctuations
I. Temporal dynamics: Gaps in Knowledge
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6/1 6/8 6/15 6/22 6/29 7/6 7/13 7/20 7/27
Tem
per
ature
, C
elsi
us
Date
Thermal Stress Hypothesis (Paull et al 2015)
• Proposed that high temperatures are energetically stressful to snails, depleting energy stores (e.g., fat reserves) during long warm periods.
• Depleted host energy limits cercaria production by trematode parasites
I. Temporal dynamics:
I. Temporal dynamics: Thermal Stress Hypothesis
Warm
Temperatures
Metabolism
(reaction rates)
Energy budget of
snail (fat reserve)
Cercaria
Immediate Effect
Delayed Effect
Higher levels when currentwater temperature is high
Lower levels following
multiple days of warm
temperatures
I. Temporal dynamics: Thermal Stress Hypothesis
Predictions:
Summer 2015 – Madelyn Messner
• Needed a large number of daily cercaria samples from
natural sites during peak swimmer’s itch season
Temporal dynamics: July 6 – August 2, 2015
Daily samples- filter
50L water
Hourly temperature
& light
• 378 individual sample tubes
• DNA extraction from dried sample
− 1 mL lysis buffer + 10 uL proteinase K
• qPCR – DNA quantification
− TaqMan Assay (Jothikumar et al 2015)
− Target itch-causing schistosomes
− Singlicate reactions w/reruns for inhibited reactions
IPC measures reaction inhibition (reduces measurement bias)
Singlicate reactions (low precision for individual measurements)
Temporal dynamics: sample processing
Temporal dynamics: statistical analysis
Response variable:
Cercaria/ 50L
Substantial day to day
variation
Random effects:
- Location
- Snail population
- Snail infection levels
- Bird visitation
- Water currents
Log cercaria/ 50L
Min Daily Temp
EXAMPLE: (Hypothetical)
• Pirate attacks correlate
with ocean wind speed
• Can we conclude increased
wind speed caused the
increase in pirate attacks
through time?
Temporal dynamics: temporal confoundment
YEAR17901755 1780 17851750
Pir
ate
atta
cks
Ocean
win
d sp
eed
Problem:
• THOUSANDS of possibly relevant variables increased or decreased during this time period, making this a potentially CONFOUNDED predictor variable
Poor evidence for causality (temporally confounded analysis)
Standard method – account for
long-term trend first, before
testing for relationships
Method 1:
• “Detrend” cercaria data
using deviations from a
spline curve fit to data
Temporal dynamics: temporal confoundment
*Method 2:
• Use past cercaria levels (over 3, 5, or 7 days) as a covariate in the
analysis. Past levels predict current levels.
AFTER accounting for the long-term trend, we tested for effects of current & past daily temperatures on cercaria abundance
Better evidence for a meaningful relationship
Random variation…. (singlicate analyses)
Best model according to AIC: 3 predictors
1. Higher cercaria levels in past 5 days →
higher cercaria levels today
2. Current temps positive trend
3. Past temps significant negative effect
Predictor variable Coefficient χ2 p-value
Log cercaria prev 5 days 1.94 23.9 <0.001
Min daily water temp 0.24 2.66 0.10
Previous 5 day water temp -0.69 14.0 <0.001
Temporal dynamics: Results
Temporal dynamics: Conclusions
• Field evidence for
Thermal Stress Hypothesis
• Positive effect of current temps
- Widely cited in literature
- Weaker (non-significant) effect in our analysis
Negative effect of past temps
- Novel finding; highly significant and predictive
- Higher-precision assays might help improve predictions in the future
Research Goals
1. Temporal dynamics
• Generate daily field data for cercaria abundance
• Test predictions for potential warning systems
2. Spatial distribution
• Identify landscape-level predictors of snail and parasite abundance
• Inform management decisions
II. Large-Scale Spatial Survey (16 lakes; 38 sites)
Maddie&
Jenna
Jason&
Ryan
Aleena & Alex
• >50 volunteers trained• >1040 cercaria samples collected• >3000 miles driven• >2500 qPCR assays run
What determines patterns of schistosome cercariaeabundance across a broad landscape?
What determines swimmer’s itch at a particular SITE?
Snail population density
Percent snails infected
Cercariae produced per snail
Bird infection?
Temperature? Algal
growth?
Cercariaein water
SWIMMER’S ITCH!
Wind/Waves?
Possible environmental drivers…..
Land Use • Urbanization• Agriculture• Vegetation• Development
Physical charateristics• Wave action• Lake size/depth• Substrate type• Temperature
Cercariae in water
Herbicide runoff
Zebra mussels
Insecticide runoff
Nutrient pollution (N, P)
Snail density
Arthropod predators (crayfish)
Attached algae
Water clarity
−
−
−Hypothesized drivers:
Bird visitation
Water clarity hypotheses*:
1. Clear water lets light penetrate to bottom of lake2. Algal periphyton is often light-limited, especially in deeper water3. Snail populations are often limited by periphyton (food) abundance 4. Trematode abundance often limited by abundance of host snails
Infected snailsTemperature
−
Continuous/Daily monitoring:• Cercaria density - daily filtered-water samples (volunteers + qPCR)• Wind speed & direction (volunteers)• Water temperature & light penetration (HOBO loggers)• Bird visitation
Weekly surveys:• Snail quadrat sampling & collection (identification, size distribution)• Turbidity & zebra mussel densities (quadrats)• Crayfish trapping• Zooplankton sampling (density, composition)
Site-level measurements:• Attached algae (periphyton) growth & composition• Zebra mussel settling rates• Water chemistry (nitrates+nitrites+ammonia, organophosphate)• Pesticides (2,4-D; glyphosate)• Sediment cores (Phosphorus, Organic carbon)• Substrate & shoreline characteristics; fetch; slope
Lake-level characteristics:• Land use in watershed & near shore• Lake size & depth
2016 survey parameters (>60 possible predictors….):
Results Part 1: Snails responded to water clarity
Supported a core prediction of our water clarity hypotheses….
… and Pleurocera are NON-HOST snails.
Characteristics:• Thick-walled shells• Operculate• Common in larger rivers• MI is northern edge of
known distribution
Not known to host Trichobilharzia sp. parasites
Encyclopedia of Life:Pleurocera collection records
Results 2: Cercariae responded to Stagnicola
• No added predictive power by adding other snail species to the analysis
“Stagnicola” snails:
Encyclopedia of Life:Stagnicola collection records
Characteristics: Known hosts for Trichobilharzia spp.
parasites• Non-Operculate• ARCTIC taxon – rare south of MI• Eat algal periphyton & macrophytes• Lives in deep water (up to 30 feet for
L. catascopium)• Prefer solid substrates• Regulation by fish predators…?
“Stagnicola” snails:
Stagnicolacatascopium/emarginata/elodes
Some sites had cercariae despite no Stagnicola….
• Might indicate influx of cercariae from offsite via water currents
• Can we account for any of this variation in our analysis?
F1,35 = 7.0; P = 0.012
Sites with few or no Stagnicola snails
How could submerged vegetation reduce the influx of cercariae from other sites?
Results 3: Submerged vegetation reduced cercariae(after accounting for snail density)
Plants as physical barriers? Plants as accidental “hosts”?
Hedychia coronarium (mariposa)(Warren & Peters 1968)
Floating water plants(Christensen 1979)
How could submerged vegetation reduce the influx of cercariae from other sites?
Bladderwort (Utricularia spp.)
• Carnivorous water plant• Known to eat cercariae!• Widespread in MI• Sometimes mistaken for milfoil
Eurasian milfoilBladderwort
Gibson & Warren 1970
Cercariae
Cercariae
Submerged vegetation Stagnicola
Maximum Lake Depth
Deciduous trees
−
Summary – Swimmer’s itch apparent risk factors
Shallow Lake:
Deep Lake:
HIGH Risk
LOW Risk Medium Risk
Medium Risk
Summary – Swimmer’s itch apparent risk factors
THANK YOU!!!
Funds & Lodging (still compiling names for 2016…):
RAFFEL LAB:Madelyn Messner*Jason Sckrabulis*Ryan McWhinnie*Jenna McBride*Alex BagerisAleena HajekKarie Altman
Collaborators:Pieter Johnson, Sara Paull, Bryan LaFonte, Curt Blankespoor, Ronald Reimink, David Szlag
Oakland University Support:Doug Wendell (chair), Arik Dvir, Cathy Starnes, Sheryl Hugger, Jan Bills, Kathy Lesich, Shawn Rasanen
Oakland Undergraduate researchers:Fieldwork: R. McWhinnie, J. McBride, A. Hajek, A. Bageris; qPCR: J. McBride, S. Trotter, G. Everett, J. Willis; Invertebrate counts: Melissa Ostrowski, James Willis, Rima Stepanian, Aman Singh
Oakland University StartupAl Flory & Monika SchultzChimney Corners ResortPlatte Lake Improvement AssnGlen Lake AssociationLake Leelanau Lake AssnLeelanau Clean WaterWalloon Lake AssociationLime Lake AssociationHiggins Lake Property Owners Assn
SICON LLCTwin Lakes Property Owners AssnElk-Skegemog Lake AssnCrystal Lake & Watershed Org.Lake Margrethe Foundation FundHamlin Lake Preservation SocietyPortage Lake Watershed ForeverIntermediate Lake Association
ALL OUR CITIZEN SCIENTIST VOLUNTEERS! (NEXT SLIDE)
• (Crystal Lake) Al Flory & Monica Schultz; Ted & Barb Fischer; Pat & Sherry Grant• (Glen Lake) Mike & Sara Litch; Rob Karner; John DePuy; John Kassarjian• (Lake Leelanau) John Lutchko; Dave Hunter; John Popa; Wayne Swallow• (Platte Lake) Bob & Mason Blank; Wilfred Swieki• (Little Traverse Lake) Len Allgaier• (Lime Lake) Dean Manikas• (Walloon Lake) Russ Kittleson• (Higgins Lake) Ron Reimink; Curt Blankespoor
• (Crystal Lake) Al Flory & Monica Schultz; Ted Fischer; Jana Way; Joel Buzzell; Shary Grant
• (Deer Lake) Todd Sorenson; Alec Sherman
• (Douglas Lake) Curt Blankespoor; Kira Surber
• (Elk Lake) Bob & Bryce Kingon; Dean Ginther; Ruth Bay
• (Glen Lake) John Kassarjian; Mike Litch; Denny Becker; Bill Meserve; Jack Laitala; Chris Dorsey Shugart
• (Hamlin Lake) Ginny Hluchan; Linda & Ted Leibole; Judi Cartier & Ed Franckowiak; Paula & Mike Veronie; Denny Lavis; Joe
Muzzo; Mara DeChene; Gail Hanna; Kathy Grossenbacher; Jim Gallie
• (Higgins Lake) Jim Vondale; Charlene Cornell; Richard Weadock; John & Susan Osler; Anne Grein; Ken Dennings; Greg Douglas;
Rebekah Gibson; Sue Gederbloom
• (Intermediate Lake) Steve & Kathy Young; Jim & Karen Gilleylen; Scott Zimmerman; Marcia Collins; Claude & Joyce Gilkerson;
Sheridan & Bob Haack
• (Lake Leelanau) David Hunter; John Popa; John Lutchko; Nick Fleezanis; Page Sikes
• (Lime Lake) Dean Manikas
• (Little Traverse Lake) Len Allgaier and Kristin Race
• (Lake Margrethe) Sandra & Ken Michalik; Mike Ravesi; Lisa Jaenicke; Nancy Atchison
• (Platte Lake) Wilfred J. Swiecki; Bob Blank; Tom & Christian Inman; Jackie & John Randall
• (Portage Lake) Al Taylor; Mary Reed; Tammy Messner; Ted Lawrence
• (Lake Skegemog) Dave Hauser; Kathi Gober
• (Walloon Lake) Christine Wedge; Russ & Kathy Kittleson; John Markewitz; Megan Muller-Girard
2015 survey volunteers (8 lakes)
2016 survey volunteers (16 lakes)
What does thermal stress predict through time?
Cold to Warm: initial increase in parasite production followed by steady decline
Constant Warm: parasite production declines longer it is held at warm temps
Paull et al 2015
D45L
D90
D45R
Effective Fetch (Lf )
𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝐹𝑒𝑡𝑐ℎ =σ 𝐷𝑖 × 𝑐𝑜𝑠 𝛾𝑖
σ𝑐𝑜𝑠 𝛾𝑖
• Distance wind can blow over water more wave action (in theory)
• Correlates with lake size & depth
𝑀𝑜𝑑𝑖𝑓𝑖𝑒𝑑 𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝐹𝑒𝑡𝑐ℎ =𝐷45𝐿𝑐𝑜𝑠 45° + 𝐷90𝑐𝑜𝑠 90° + 𝐷45𝑅𝑐𝑜𝑠 45°
𝑐𝑜𝑠 45° + 𝑐𝑜𝑠 90° + 𝑐𝑜𝑠 45°
But why are Pleurocerid snails more abundant at high-Fetch sites?
Possible hypothesis:• Adapted for shallow water & high wave action
Conifers – effects on turbidity, snails, & mussels?
• Conifers release terpenes (“turpentine”)
Toxic to algae? (few studies)
• Less algae → lower turbidity
Less food for mussels
More food for snails