Why habitat/water quality models?

• To map/predict current and future species assemblages, status

• To project future status of species and habitats under alternative management strategies, environmental conditions

• To explore linkages between habitat condition, water quality, and species status

Mary Ruckelshaus, Tim Beechie, Lance Garrison, Josh Nowlis

Habitat approaches to ecosystem(ish) modeling

• Statistical associations between species and habitats

• Spatial modeling of habitat-forming process functioning and potential impacts of toxics

• Linked mechanistic models of climate -->land use/hydrology-->species dynamics

• Under development: full ecosystem models including effects habitat change on other ecosystem components; linking watershed models to marine

Statistical associations between species and habitats

The primary goal of habitat modeling is to provide spatially explicitestimation of species occurrences to:

1) Improve accuracy and precision of abundance estimates

2) Predict occurrence outside of surveyed times and areas

3) Improve evaluation of risks due to human activities

4) Define habitat boundaries for the purposes of designation under ESA

Some applications of these approaches:What are the localized effects of military operations ?What are the risks of vessel-whale interactions in different areas ?Where are the areas of overlap between fisheries and mammals ?Where should protected areas be located?

Habitat Modeling ApproachThe goal is to develop spatially explicit predictionsof animal density and abundance

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Empirical models of the species-environmentrelationship Project these into space

as a density surface

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Example outcome: Predicted Seasonal Variation in Right Whale DensitiesIn the Southeast US Calving Area

Right Whale Density Sea Surface Temperature

Also: BathymetryEffortSightings

Example outcome: Spatial distribution of bottlenose dolphins in the Eastern Gulf of Mexico

Sightings (dots) and modeled densities of bottlenose dolphins from a GAM modelbased on sea surface temperature, chlorophyll concentration, depth, and distance from shore

Example outcome: Spatial distribution of bottlenose dolphins in the Eastern Gulf of Mexico

The resulting density surface may be used to support environmental assessmentsand planning of military operations in the Eastern Gulf Testing and Training Range

Effects of stormwater runoff on salmon

ModelOverview

Pre-spawnMortality Data

GIS (Habitat)Datalayers

Overlay GISDatalayers withDrainage Basins

StatisticalAnalysis

•Significant Variables•Predictive Model of Pre-spawn Mortality

Predictive Model ofPre-spawn Mortality

Habitat approaches to ecosystem(ish) modeling

• Statistical associations between species and habitat quantity/quality (data intensive, some extrapolation possible, limited generality)

• Spatial modeling of habitat-forming process functioning (remotely sensed data, relationships theoretically derived)

• Linked mechanistic models of climate -->land use/hydrology-->species dynamics (time, computer-intensive, validation not realistic)

Identify alternative watershed, harvest,

hatchery management strategies

Compare Forecasted Effects of Strategies

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ChinookCoho

Model Habitat Conditions & Fish Response

GIS

Analytical approach

Landscape processes and land use affect in-stream habitat conditions

LandscapeProcesses

Land use

Habitat Conditions

BiologicalResponse

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Identifying peak-flow impaired sub-basins

Impaired: >10% impervious area

Functioning: <3% impervious area

Designing and evaluating recovery strategies with uncertain futures

Climate Model(GFDL, Hadley)

Hydrology Model(DHSVM)

Air Temp., Meteorology

Salmon Pop. Model(SHIRAZ)

Stream flow, Temp.

Salmon Abundance

Land Cover & Land Form

Data

PredictedAtmospheric

CO2

Habitat Capacity

Climate Model(GFDL, Hadley)

Hydrology Model(DHSVM)

Air Temp., Meteorology

Salmon Pop. Model(SHIRAZ)

Stream flow, Temp.

Salmon Abundance

Land Cover & Land Form

Data

PredictedAtmospheric

CO2

Habitat Capacity

GFDL model Hadley model

Battin et al. 2007

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Habitat-water quality models: next steps?

• Estimates of full suite of ecosystem services and tradeoffs

• Dynamic drivers or set habitat-based capacity, survival in ecosystem models

Food webs and habitats: changes?

1) Nearshore ecosystem services

Food-web support & Habitat provisioning

Species directly important to humans (commercial and/or recreational harvest)

Species important in food-webs

Supporting/Regulating

Cultural/Aesthetic

Carbon sequestration

Non-consumptive use (in situ)

Non-use (ex situ)

Service Category Provides. . .

Shoreline protection/stabilization

Assimilative capacity

Decision Support Tool in Concept

User identifies time and spatialoptions for a given activity

Download and process remotelysensed data

Create corresponding shapefilefor the area

Generate updated Density Surface

Intersect the shapefile withthis density surface and

summarize (including uncertainty)

Outputs include estimates of numbers impacted, evaluationof “best” amongst options of

areas and times for the activities

Heavily Used Roads (Arterials)

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All Arterials (PSRC)

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r2 = 0.943;p = 0.0012; y = -0.042 + 19.286xFortsonCreek

Fauntleroy

Piper’s

Des Moines

Longfellow

Thornton

Primary causes of habitat destruction & degradation in Puget Sound

Spatial Aggregation of Data

Bathymetry SST Effort Sightings

Habitat information derived from remotely sensed data: Sea surface temperature, ocean color, SS height anomaly, winds

All data aggregated into spatial cells (~ 5 x 5 km square cells)

Predictive surfaces generated based on additional remotely sensed data

Vegetation Geology Climate

Light/heat inputs

Nutrient/chemical

inputs

Organic matter inputs

Hydrologic regime

Sediment supply

Physical habitat characteristics

Water quality and primary productivity

Biological response