Progress Progress on Development of an Integrated Ecological Response Model for the Lake Ontario/St. Lawrence River Presented by: Limno-Tech, Inc. September 11, 2002

Overview Project Background Role of modeling for addressing the ecosystem level problems Development of conceptual framework for the LOSL Integrated Model Development of a prototype LOSL Integrated Ecosystem Model Demonstration of the prototype model Next Steps

Background LTI is assisting the LOSL Study Board and the ETWG in evaluating the ecological impacts of alternative flow and water-level regulation plans for the Lake Ontario-St. Lawrence River system Three-phase project to synthesize all ecological research on system into an integrated ecosystem model Phase 1 of project begun end of May, 2002 Phase 1 intended to develop conceptual ecosystem model and demonstration prototype, and plan for full implementation

Phase 1 Tasks Form a Modeling Advisory Panel (MAP) that can provide advice and system-level perspective Develop a Conceptual Model Framework for the LOSL Integrated Ecological Response Model Develop and vet a simple prototype model Based on vetting of prototype, develop design criteria for full LOSL Integrated Ecological Response Model Prepare a plan for development, implementation and application of a system-wide LOSL Integrated Ecological Response Model

Why Develop an Integrated Ecosystem Response Model? Model serves as synthesis/repository of system knowledge Model helps identify gaps in knowledge and data Model allows assessment of multiple stressors acting in concert on multiple endpoints Model connects and integrates different geographical areas of system

Why Develop an Integrated Ecosystem Response Model? Model quantifies and demonstrates cause- effect relationships, including feedback processes Model has potential to extend empirical observations in space and time (e.g., compute long-term response from short- term processes) Model helps in evaluations and forecasts in Adaptive Management

Role of Integrated Ecological Response Model (LOSL IERM) Quantify the relationship between water-level and flow fluctuations under alternative regulation plans and effects on ecological performance indicators  Integration of various ETWG ecological component response models  Captures important ecological feed-forward and feedback interactions Account for management actions and system stressors related to other management issues and natural conditions  fisheries management, nutrients, toxic chemicals, aquatic nuisance species  natural hydrologic variability, global climate change Provide ecological performance indicator output to the overall Shared Vision Model  Appropriate for environmental evaluations  Allows comparison with other interests

Ecological Responses Value? Input to Shared Vision Model Regulation Natural hydrological & climatological variations H&H Model predicted water level/flow hydrograph Other Management Actions and System Stressors Changes in Habitat Quantity/Quality Shoreline Habitat Wetland Habitat Nearshore Habitat Riverine Habitat Open water/Impoundments Primary Producers Primary Consumers Secondary Consumers Tertiary Consumers Changes in Food Resources/Trophic Transfer Conceptual Model

Conceptual Model: Trophic Structure Birds Forage Fish Phytoplankton/B enthic algae Aquatic Macrophytes Mammals Reptiles and amphibians Zooplankton Benthic invertebrates Tertiary Consumers Top Predator Fish Secondary Consumers Primary Producers Primary Consumers

Conceptual Model Outputs Related to Ecological Performance Indicators 1. Muskrats Habitat-specific abundance 2. Birds Species richness Relative abundance of guilds 3. Amphibians/reptiles 4. Fish – spatially specific Fish guilds – population and biomass dynamics Northern Pike – population and growth rate 5. Habitat and food availability Wetland plant diversity Habitat-specific area of each vegetation type Wetland plant biomass 6. Special interest habitats 7. Special interest species 8. Water quality Nutrient levels in water column and sediments

Conceptual Model: Northern Pike Population Sub-model Abundance Age-0 Northern Pike Effect on Habitat Water Levels/Flow Abundance Adult Northern Pike Mortality Predation Natural Mortality Harvest Abundance Juvenile Northern Pike Phytoplankton/B enthic algae Aquatic Macrophytes Zooplankton Benthic invertebrates Effect on Food Availability: Primary Producers Effect on Food Availability: Primary and Secondary Consumers Nutrient Sources Temperature Stocking

Conceptual Model: Northern Pike Bioenergetics Sub-model Northern Pike Biomass Wetland Quantity/Quality Mortality Water Levels Harvest Nutrients Phytoplankton Zooplankton Planktivores Juvenile Northern Pike Biomass Stocking

Conceptual Model: Spatial Discretization Lake Ecosystem Open Embayment Beach Barrier Open bay wetland Near Shore Drowned River mouth Open Water Protected Bay Wetlands Upper River Ecosystem Lower River Ecosystem Move toward GIS-based habitat-specific resolution?

Conceptual Model: Temporal Scales Forcing Functions and Environmental conditions Input Data Biomass of Phytoplankton Zooplankton PhytoplanktonZooplankton Time Biomass (mg C/L) Solar RadiationTemperature Time = Month Time=Max Time (say year) Yes No Read Data for next day End Yes Print Output No Read Data for next month

Example: Forage Fish Interactions Nutrients Top Predator Fish Plankton Production Forage Fish TemperatureDO Birds Wetland Habitat Muskrat Zebra Mussels Benthic Production

LOSL Prototype Model Overview Prototype model demonstrates feasibility and utility of the full IERM. Prototype model is currently driven by empirical relationships based on available literature. Current performance indicators (PIs):  Wetland emergent plant coverage  Wetland emergent plant biomass  Wetland diversity index  Northern pike adult population  Muskrat population

LOSL Prototype Model Overview Actual PIs and associated algorithms will be based on ETWG study results. Five regulation scenarios currently provided by Bill Werick, including:  1958DD (baseline scenario)  Pre-Regulation Water level time series currently available for:  Lake Ontario  Lake St. Lawrence

Wetland Sub-model Wetland emergent area/biomass  Emergent total area/biomass inversely related to water level  Based on Lake St. Pierre study (Hudon, 1997) Wetland plant diversity index  Uses a representative wetland flood elevation to determine flooding frequency  Related to number of years between floods (disturbance events) (IJC, 1993)

Northern Pike Sub-model Simple population model adapted from pike model for Hamilton Harbour (Minns 1996) Tracks age class populations:  Young-of-year  Juveniles  Adults Habitat suitability index (HSI) based on:  Wetland diversity index  Emergent plant coverage  Spring water level variation

Northern Pike Sub-model Wetland Sub-model Hydro Sub-model % Emergent Coverage Vegetation Diversity Spring Water Level Decline Weighted Usable Area * Total Area YOY Survival Rate HSI

Muskrat Sub-model Adult muskrat population computed based on assumed density (no./ha) and habitat weighted useable area. Habitat suitability index (HSI) based on:  Intra-annual water level fluctuation  Emergent plant coverage  Wetland hydroperiod

Muskrat Sub-model Wetland Sub-model Hydro Sub-model Hydro period % Emergent Coverage Annual Fluctuations Weighted Usable Area * Total Area Muskrat Population HSI * Optimal Density

Prototype Model Demonstration

Next Steps Phase 1 completion (Oct, 2002):  Revise conceptual model based on input from ETWG, MAP, and other TWGs.  Prepare IERM development and application plan (include model concept, assumptions, design criteria, calibration/application strategy). Phase 2 ( ):  Work closely with ETWG sub-groups to structure and link sub-models.  Work with ETWG, MAP, and Plan Formulation Group to establish time and space scale for model.

Next Steps (cont) Phase 2 (cont):  Work with other TWGs to obtain necessary input and desired outputs from IREM.  Encode and beta-test working model. Phase 3 ( ):  Integrate all available system data and new data being developed by LOSL studies.  Calibrate model with available field observations and conduct sensitivity analysis.  Apply model to evaluate alternative regulation plan scenarios and assess responses to other system stressors.