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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

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Presented by limno tech inc september 11 2002

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
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
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
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
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 model1
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
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


Conceptual model
Conceptual Model

Natural hydrological & climatological variations

Regulation

Other Management Actions and System Stressors

H&H Model predicted water level/flow hydrograph

Changes in Food Resources/Trophic Transfer

Changes in Habitat Quantity/Quality

  • Shoreline Habitat

  • Wetland Habitat

  • Nearshore Habitat

  • Riverine Habitat

  • Open water/Impoundments

Primary Producers

Primary Consumers

Secondary Consumers

Tertiary Consumers

Value?

Input to Shared Vision Model

Ecological Responses


Conceptual model trophic structure
Conceptual Model: Trophic Structure

Phytoplankton/Benthic algae

Aquatic Macrophytes

Primary Producers

Primary Consumers

Zooplankton

Benthic invertebrates

Secondary Consumers

Forage Fish

Top Predator Fish

Reptiles and amphibians

Tertiary Consumers

Birds

Mammals


Conceptual model outputs related to ecological performance indicators
Conceptual Model Outputs Related to Ecological Performance Indicators

  • Muskrats

    • Habitat-specific abundance

  • Birds

    • Species richness

    • Relative abundance of guilds

  • Amphibians/reptiles

  • Fish – spatially specific

    • Fish guilds – population and biomass dynamics

    • Northern Pike – population and growth rate

  • Habitat and food availability

    • Wetland plant diversity

    • Habitat-specific area of each vegetation type

    • Wetland plant biomass

  • Special interest habitats

  • Special interest species

  • Water quality

    • Nutrient levels in water column and sediments


Conceptual model northern pike population sub model
Conceptual Model: Northern Pike Population Sub-model Indicators

Water Levels/Flow

Nutrient Sources

Effect on Food Availability: Primary Producers

Effect on Habitat

Phytoplankton/Benthic algae

Aquatic Macrophytes

Temperature

Effect on Food Availability: Primary and Secondary Consumers

Zooplankton

Benthic invertebrates

Abundance Juvenile

Northern Pike

Abundance Age-0 Northern Pike

Stocking

Abundance Adult

Northern Pike

Mortality

  • Predation

  • Natural Mortality

  • Harvest


Conceptual model northern pike bioenergetics sub model
Conceptual Model: Northern Pike Bioenergetics Sub-model Indicators

Water Levels

Nutrients

Wetland

Quantity/Quality

Phytoplankton

Stocking

Zooplankton

Northern Pike Biomass

Juvenile Northern Pike Biomass

Planktivores

Mortality

Harvest


Conceptual model spatial discretization
Conceptual Model: Spatial Discretization Indicators

Protected Bay

Wetlands

Drowned

River mouth

Open Water

Open

Embayment

Lake

Ecosystem

Upper River

Ecosystem

Lower River

Ecosystem

Near Shore

Beach

Barrier

Open bay

wetland

Move toward GIS-based habitat-specific resolution?


Conceptual model temporal scales
Conceptual Model: Temporal Scales Indicators

Solar Radiation

Temperature

Input Data

Forcing Functions and Environmental conditions

Phytoplankton

Zooplankton

Biomass of

Phytoplankton

Zooplankton

Biomass (mg C/L)

No

Read Data for next day

Time

Time = Month

Yes

No

Read Data for next month

Time=Max Time (say year)

Yes

Print Output

End


Example forage fish interactions
Example: Forage Fish Interactions Indicators

Temperature

DO

Muskrat

Zebra

Mussels

Wetland

Habitat

Plankton

Production

Forage

Fish

Top

Predator Fish

Nutrients

Benthic

Production

Birds


Losl prototype model overview
LOSL Prototype Model Overview Indicators

  • 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 overview1
LOSL Prototype Model Overview Indicators

  • 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 Sub-model Indicators

  • 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
Northern Pike Sub-model Indicators

  • 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 model1
Northern Pike Sub-model Indicators

HSI

% Emergent

Coverage

Wetland

Sub-model

Weighted Usable Area

YOY

Survival Rate

Vegetation

Diversity

*

Total

Area

Hydro

Sub-model

Spring Water

Level Decline


Muskrat sub model
Muskrat Sub-model Indicators

  • 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 model1
Muskrat Sub-model Indicators

HSI

Hydro period

Wetland

Sub-model

% Emergent

Coverage

Weighted Usable Area

Muskrat

Population

*

Total

Area

*

Optimal Density

Hydro

Sub-model

Annual

Fluctuations



Next steps
Next Steps Indicators

  • 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
Next Steps (cont) Indicators

  • 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.