Effects of Spatio-temporal Heterogeneity on Resource Partitioning of Lake Ontario Salmonids

Using Archival Satellite Tags

Christina SemeniukAssistant Professor

University of Windsorsemeniuk@uwindsor.ca

Great Lakes Fishery Commission – Project Pre-Proposal PresentationMarch 7, 2013 Ann Arbor, MI

Team Members

PI:

• Nigel Hussey – Post-doctoral Research Fellow, GLIER, UWindsor• Aaron Fisk – Professor, GLIER, UWindsor• Timothy Johnson – GL Research Scientist, Ontario Ministry of Natural Resources• Tom Stewart – Program Advisor-Great Lakes Ecosystems, OMNR• Jana Lantry – Aquatic Biologist, New York State Department of Environmental Conservation

Co-PI’s:

Christina Semeniuk – Assistant Professor, GLIER, UWindsor

NYS Department of Environmental Conservation

Fish, Wildlife & Marine Resources

• I use this information to explore distributional and demographic patterns under future scenarios.

What I Study

• I investigate the cumulative effects of multiple stressors on the behaviour and movement decisions of wildlife.

• I then evaluate how these impacts can ultimately affect the persistence of wildlife populations.

• I ensure the scenarios are rooted in spatial systems to strengthen the predictive framework.

Future Scenarios

Spatial Systems

Behavioural Processes

Predictive Ecology

How I Conduct Integrated Resource Management

Ecology

Quantitative Modelling• individual – agent-based • population – system dynamics• spatial – GIS

Interdisciplinary Resource Management

Collaboration• academic• industry• government

• human dimensions of wildlife• econometric models

• field• theory

• habitat selection• predator-prey

• geography• geomatics engineering

Study Systems: Multi systems, Multi taxa

Unifying Thread

Team Members - Expertise

• Nigel Hussey – Resource partitioning, Animal movement• Aaron Fisk – Trophic ecology, Animal movement• Timothy Johnson – Food-web ecology, Fish bioenergetics• Tom Stewart – Bioenergetics/Food-web models, Spatial analyses• Jana Lantry – Population dynamics, Fisheries assessments

Christina Semeniuk – Ecological modeling, Spatial analyses PI:

Co-PI’s:

Lake Ontario Research Priorities

• Maintain healthy, diverse fisheries• Salmon, trout, walleye, yellow perch, basses

• Maintain and restore native fish communities• Atlantic salmon, lake trout, lake sturgeon, American eel

• Maintain predator-prey balance* Stewart et al., GLFC Spec. Publ., under review

• Restoration of Native Fishes is a Basin-wide Research Priority

• Draft Fish Community Objectives for Lake Ontario*

8

Statement of the Problem

• Non-complementary objectives (??):

Restoration of native speciesProductive salmonid fisheries

• Concerns about predator demand: prey supply

• Ecological effects associated with non-native fish introductions

Statement of the Problem

• Progress has been slow and many potential impediments have been identified

• interactions with non-native species, Chinook salmon (Oncorhynchus tshawytscha, CS)

• knowledge gaps in fish movement and migration

• Efforts to restore native lake trout (Salvelinus namaycush, LT) and Atlantic salmon (Salmo salar, ATS) are underway in Lake Ontario.

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Misc.Lake troutBrown troutAtlanticRainbowCohoChinook

Year

Catc

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our

Lantry and Eckert, 2012

Salmonid Abundance in Lake Ontario

Statement of the Problem

“Field studies are key in providing a more holistic vision of non-native species-induced ecological impact emerging from competitive forces.”

A. Ecological relationships will have impacts on stocking and restoration efforts

Changes in niche occupancy characteristics via:

1. Direct competition with Chinook salmon

2. Indirect competition through changes in prey base

Blanchet et al. 2007

Johnson et al. Unpublished data

Diet overlap

Statement of the ProblemB. Behaviour, movements and distribution of adult fish in the open lake

have received relatively little attention.

• Long-term environmental changes and/or whole-lake disturbances affect fish habitat-selection responses – growth, reproduction and survival.

“The advent of new and more powerful tracking technologies can address research questions such as large-scale movements (both spatial and temporal) and fine-scale behavior of fishes in and around fishways.”

• Many of the challenges surrounding movement are biologically complex and vary in terms of spatial and temporal scale.

Landsman et al. 2011

Research Questions

1. How does seasonal BMD and resource use compare among salmonids in Lake Ontario;

2. What is the degree of seasonal spatial overlap and the potential for interspecific competition of these species;

3. Do predators exploit spatial and temporal heterogeneity in thermal structure and prey distributions to maximize growth?

Understanding open-lake behaviour, movements, and distributions of salmonids in Lake Ontario is an essential pre-cursor to restoring self-sustaining populations

1. 2. 3.

Research Methods

(1) Animal Tracking

MiniPAT: Pop-up Archival Transmitting Tag

• Fish caught by trained anglers in the spring

• 6 tags / species, split Ontario-New York waters

• Simple attachment harness on fish

• User-specified archiving interval and time-to-release

• Upon release, relays data and current position to satellite for retrieval

http://www.asf.ca

Chittenden et al. 2013

Research Methods

(1a) Animal Tracking – Vertical positioning

Detailed movement ecology:

• Activity patterns – vertical daily, seasonal

• Thermal occupancy

Research Methods

(2a) Refining Geolocation: Horizontal positioning

Ådlandsvik et al. 2007

• create trajectories that join tag start- and end-locations: avoid the excluded areas where tag and environmental information disagree

Horizontal position will be estimated using a trajectory algorithm:

Time step 255 Trajectory Tag

Depth = 75 30

Time step 380 Trajectory TagTemperature = 20.4oC 21.0oCDepth = 25 5

Time step 205 Trajectory TagTemperature = 6.5oC 25.2oCDepth = 5 3

Temperature = 16.5oC 16.0oC

Research Methods

(2b) Refining Geolocation: Spatial-thermal map

Temperature-depth data will be obtained from a 3D hydrodynamic map of Lake Ontario.

Huang, Yerubandi et al. 2010

Research Methods

(2b) Refining Geolocation

Detailed movement ecology:

• Daily-seasonal activity rates

• Degree of potential spatio-temporal overlap between species

Simpfendorfer et al. 2012

Research Methods

(3) Energetic Optimization

-0.0058 Growth (g g-1 d-1)0 22

0.02

Density (g m-3)

0

55

10-3 101.3

Depth

Prey density

Temperature

Horne et al. 1996

• Thermal occupancy data will be combined with agency-derived diet, prey distributions and growth rates;

• Bioenergetics modeling will be used to evaluate:• predator demand differences among species• energetic consequences of occupied temperature• where are predators relative to prey and each other when demand peaks?

Research Deliverables1. A more complete understanding of seasonal behaviour, movement, and

distribution of salmonids in Lake Ontario

2. Insight into the potential for interspecific competition among salmonid species

3. Discern growth efficiency, thermal preferences

4. Contribute to stock assessment management

5. Extend methods to other species, lakes, and ecosystems

e.g., feeding ecology, corroborate diet isotopic information

e.g., partition of space and resources

e.g., recalibrate stocking demand relative to prey supply

e.g., aid in targeting location of stocks

Questions?

Great Lakes Fishery Commission – Project Pre-Proposal PresentationMarch 7, 2013 Ann Arbor, MI

Research Budget & Timeline

• Year 1: Animal tracking, vertical positioning analyses, spatial-map generation, development of geolocation algorithm.

• Year 2: Continued tracking, resource-partitioning analyses, and bioenergetics modeling.

$67,320 / year for 2 years • Costs:

• Purchase: miniPATs from Wildlife Computers• Hire: boating captains

Research Objectives & Hypotheses

Describe the seasonal behaviour, movements and distribution of LT, ATS, and CS in Lake Ontario using MiniPSATs and determine the degree of spatial and depth overlap and potential for competition

LT, ATS, and CS rarely overlap in their distribution reducing the potential for interspecific competition

Explore variation in growth rate potential for each species relative to spatial and temporal variation in temperature and prey

Patterns of occupancy exploit spatial variation in thermal habitat and prey distributions to minimize interspecific competition while maintaining sufficient access to prey and physiological optima to maximize growth.