Transcript LOSL1_091102_Presentation_to_ETWG

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
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Project Background
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Role of modeling for addressing the
ecosystem level problems
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Development of conceptual framework for the
LOSL Integrated Model
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Development of a prototype LOSL Integrated
Ecosystem Model
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Demonstration of the prototype model
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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
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Phase 1 Tasks
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Form a Modeling Advisory Panel (MAP) that can
provide advice and system-level perspective
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Develop a Conceptual Model Framework for the
LOSL Integrated Ecological Response Model
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Develop and vet a simple prototype model
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Based on vetting of prototype, develop design
criteria for full LOSL Integrated Ecological Response
Model
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Prepare a plan for development, implementation
and application of a system-wide LOSL Integrated
Ecological Response Model
Why Develop an Integrated Ecosystem
Response Model?
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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?
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Model quantifies and demonstrates causeeffect relationships, including feedback
processes
Model has potential to extend empirical
observations in space and time (e.g.,
compute long-term response from shortterm processes)
Model helps in evaluations and forecasts in
Adaptive Management
Role of Integrated Ecological Response
Model (LOSL IERM)
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Quantify the relationship between water-level and
flow fluctuations under alternative regulation plans
and effects on ecological performance indicators
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Account for management actions and system
stressors related to other management issues and
natural conditions
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Integration of various ETWG ecological component
response models
Captures important ecological feed-forward and
feedback interactions
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
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Appropriate for environmental evaluations
Allows comparison with other interests
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
Ecological
Responses
Value?
Input to Shared Vision Model
Conceptual Model: Trophic Structure
Primary Producers
Phytoplankton/B
enthic algae
Primary Consumers
Zooplankton
Secondary Consumers
Aquatic
Macrophytes
Benthic
invertebrates
Forage Fish
Top Predator Fish
Reptiles and
amphibians
Tertiary Consumers
Birds
Mammals
Conceptual Model Outputs Related to
Ecological Performance Indicators
1.
Muskrats
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2.
Birds
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3.
4.
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7.
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Fish guilds – population and biomass dynamics
Northern Pike – population and growth rate
Habitat and food availability
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6.
Species richness
Relative abundance of guilds
Amphibians/reptiles
Fish – spatially specific
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5.
Habitat-specific abundance
Wetland plant diversity
Habitat-specific area of each vegetation type
Wetland plant biomass
Special interest habitats
Special interest species
Water quality
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Nutrient levels in water column and sediments
Conceptual Model: Northern Pike
Population Sub-model
Nutrient Sources
Water Levels/Flow
Effect on Food Availability: Primary Producers
Phytoplankton/B
enthic algae
Effect on Habitat
Aquatic
Macrophytes
Temperature
Effect on Food Availability: Primary and Secondary Consumers
Zooplankton
Abundance Juvenile
Northern Pike
Abundance Adult
Northern Pike
Mortality
• Predation
• Natural Mortality
• Harvest
Benthic
invertebrates
Abundance Age-0
Northern Pike
Stocking
Conceptual Model: Northern Pike
Bioenergetics Sub-model
Water Levels
Nutrients
Phytoplankton
Wetland
Quantity/Quality
Stocking
Zooplankton
Planktivores
Northern Pike
Biomass
Mortality
Harvest
Juvenile Northern
Pike Biomass
Conceptual Model: Spatial Discretization
Protected Bay
Wetlands
Open
Embayment
Open Water
Drowned
River mouth
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
Solar Radiation
Temperature
Input Data
Forcing Functions and
Environmental conditions
Biomass of
Phytoplankton
Zooplankton
No
Read Data for next day
Biomass (mg C/L)
Phytoplankton
Time
Time = Month
Yes
No
Read Data for next
month
Time=Max Time
(say year)
Yes
Print
Output
End
Zooplankton
Example: Forage Fish Interactions
Muskrat
Nutrients
Zebra
Mussels
Wetland
Habitat
Plankton
Production
Forage
Fish
Top
Predator Fish
Benthic
Production
Temperature
DO
Birds
LOSL Prototype Model Overview
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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):
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Wetland emergent plant coverage
Wetland emergent plant biomass
Wetland diversity index
Northern pike adult population
Muskrat population
LOSL Prototype Model Overview
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Actual PIs and associated algorithms will
be based on ETWG study results.
Five regulation scenarios currently
provided by Bill Werick, including:
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1958DD (baseline scenario)
Pre-Regulation
Water level time series currently
available for:
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Lake Ontario
Lake St. Lawrence
Wetland Sub-model
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Wetland emergent area/biomass
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Emergent total area/biomass inversely related
to water level
Based on Lake St. Pierre study (Hudon, 1997)
Wetland plant diversity index
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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
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Simple population model adapted from
pike model for Hamilton Harbour (Minns
1996)
Tracks age class populations:
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Young-of-year
Juveniles
Adults
Habitat suitability index (HSI) based on:
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Wetland diversity index
Emergent plant coverage
Spring water level variation
Northern Pike Sub-model
HSI
Wetland
Sub-model
Hydro
Sub-model
% Emergent
Coverage
Vegetation
Diversity
Spring Water
Level Decline
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Total
Area
Weighted
Usable
Area
YOY
Survival
Rate
Muskrat Sub-model
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Adult muskrat population computed
based on assumed density (no./ha) and
habitat weighted useable area.
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Habitat suitability index (HSI) based on:
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Intra-annual water level fluctuation
Emergent plant coverage
Wetland hydroperiod
Muskrat Sub-model
HSI
Hydro period
Wetland
Sub-model
Hydro
Sub-model
% Emergent
Coverage
Annual
Fluctuations
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Total
Area
Weighted
Usable
Area
*
Optimal
Density
Muskrat
Population
Prototype Model Demonstration
Next Steps
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Phase 1 completion (Oct, 2002):
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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):
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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)
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Phase 2 (cont):
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Work with other TWGs to obtain necessary input
and desired outputs from IREM.
Encode and beta-test working model.
Phase 3 (2003-2004):
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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.