ProgressProgress 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/Benthic algae

Aquatic Macrophytes

Mammals

Reptiles and amphibians

ZooplanktonBenthic

invertebrates

Tertiary Consumers

Top Predator Fish

Secondary Consumers

Primary Producers

Primary Consumers

Conceptual Model Outputs Related to Ecological Performance Indicators1. Muskrats

Habitat-specific abundance

2. Birds Species richness Relative abundance of guilds

3. Amphibians/reptiles4. 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 habitats7. Special interest species8. 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/Benthic algae

Aquatic Macrophytes

ZooplanktonBenthic

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 baywetland

Near Shore

DrownedRiver mouth

Open WaterProtected Bay Wetlands

Upper RiverEcosystem

Lower RiverEcosystem

Move toward GIS-based habitat-specific resolution?

Conceptual Model: Temporal Scales

Forcing Functions and Environmental conditions

Input Data

Biomass of PhytoplanktonZooplankton

Phytoplankton Zooplankton

TimeB

iom

ass

(mg

C/L

)

Solar Radiation Temperature

Time = Month

Time=Max Time (say year)

Yes

No Read Data for next day

EndYesPrint

Output

No Read Data for next

month

Example: Forage Fish Interactions

NutrientsTop

Predator FishPlankton

ProductionForage

Fish

Temperature DO Birds

WetlandHabitat

Muskrat

ZebraMussels

BenthicProduction

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

HydroSub-model

% Emergent Coverage

VegetationDiversity

Spring Water Level Decline

Weighted Usable Area

*TotalArea

YOYSurvival

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

HydroSub-model

Hydro period

% Emergent Coverage

AnnualFluctuations

Weighted Usable Area

*TotalArea

MuskratPopulation

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 (2002-2003): 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 (2003-2004):

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.