Brook trout population dynamics: Integrated modeling across scales and data types
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Transcript of Brook trout population dynamics: Integrated modeling across scales and data types
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Brook trout population dynamics: Integrated modeling across scales and data types
Keith H. Nislow, Jason Coombs Northern Research Station, USDA Forest Service, Amherst, MA, USA
Ben Letcher, Yoichiro Kanno, Ron Bassar, Ana Rosner, Paul Schueller, Kyle O’Neil, Krzysztof Sakrejda, Matt O'Donnell, Todd DubreuilConte Anadromous Fish Research Center, U.S. Geological Survey, Turners Falls, MA, USA
Andrew Whiteley Department of Natural Resources Conservation UMass, Amherst, MA, USA
Steve Hurley
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Overview
Goal: understand population dynamics and provide broad spatial scale forecasts in response to environmental change
Problem: specificity/generality tradeoff Can’t do detailed, mechanistic studies
everywhere Lots of good survey data
Approach/solution: combined approach Response ~ f( env change,… )
How does/will environmental change affect stream salmonids?
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Data types
PIT tag Single-site demographic models
Seasonal sensitivity of lambda (population growth)
Abundance Multiple-site demographic models
Sensitivity + basin characteristics
Presence/absence Occupancy models
Effects of long term means + basin characteristics
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Data types
West Brook Isolated PIT tag Single-site demographic
model Body growth, survival,
movement, reproduction Integral projection model
Abundance Abundance models
Presence/absence Occupancy models
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Lambda sensitivities
Spring ↔Winter ↔Autumn ↓Summer ↓
Summer↑
Autumn ↑ Spring ↔
Winter↓
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Lambda response surfaces
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Forecast
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Data types
Yearly data, many sites
Age-0+ > age-0+ All
PIT tag Single-site demographic model
Abundance Abundance models
Autumn, Winter, Spring Flow Spring Temperature Elevation
State space Population projection
Presence/absence Occupancy models
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Estimated abundances
PIT tag Single-site demographic model
Abundance Abundance models
Autumn, Winter, Spring Flow Spring Temperature Elevation
State space Population projection
Presence/absence Occupancy models
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Forecast
PIT tag Single-site demographic model
Abundance Abundance models
Autumn, Winter, Spring Flow Spring Temperature Elevation
State space Population projection
Presence/absence Occupancy models
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Forecasts
Presence/absence Occupancy models
Abundance Abundance models Simple population
projection - state space
PIT tag Mechanistic models
↑
↓
↔
↔
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Extreme events forecast
PIT tag Single-site demographic model
Abundance Abundance models
Autumn, Winter, Spring Flow Spring Temperature Elevation
State space Population projection
Presence/absence Occupancy models
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Data types
Single or multiple year data, many sites
PIT tag Single-site
demographic model
Abundance Abundance models
Presence/absence Occupancy models
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Model estimates
Precip
Air T
% forest
PIT tag Single-site demographic
model
Abundance Abundance models
Presence/absence Occupancy models
Annual precipitation Minimum temperature Soil drainage class Drainage area Forest cover Stream slope
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Probability of Occupancy for Current Conditions
Drainage areaForest coverStream slope
Annual precipitationMinimum temperatureSoil drainage class
Model drivers
Brook TroutProbability of Occupancy
< 10%11% - 20%21% - 30%31% - 40%41% - 50%51% - 60%61% - 70%71% - 80%81% - 90%> 90%
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Drainage areaForest coverStream slope
Probability of Occupancy for Current Conditions
Annual precipitationMinimum temperatureSoil drainage class
Model drivers
Brook TroutProbability of Occupancy
< 10%11% - 20%21% - 30%31% - 40%41% - 50%51% - 60%61% - 70%71% - 80%81% - 90%> 90%
Probability of Occupancy 2 C increase
Probability of Occupancy 4 C increase
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Probability of Occupancy for Current Conditions
Brook Trout ResilienceIncrease tolerated (°C)
0°0.1° - 0.5°0.6° - 1°1.1° - 1.5°1.6° - 2°2.1° - 2.5°2.6° - 3°3.1° - 8.5°
Currently below threshold
Resilience of occupancy to temperature increase
Drainage areaForest coverStream slope
Annual precipitationMinimum temperatureSoil drainage class
Model drivers
Brook TroutProbability of Occupancy
< 10%11% - 20%21% - 30%31% - 40%41% - 50%51% - 60%61% - 70%71% - 80%81% - 90%> 90%
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Bringing it together
Variable Season Model
Single-site demographic
Multiple-site demographic
Occupancy
Flow Fall ↑ ** ↑ ***
Precip ↑Winter ↓ ** ↓ **
Spring ↔ ↔
Summer ↑ *** NA
Temperature Fall ↓ ** NA
Temperature ↓Winter ↔ NA
Spring ↔ ↔
Summer ↓ *** NA
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Summary
Congruent environmental effects on population growth across scales Increases confidence in generality of
results Negative effects of temperature Positive effects of flow in fall and
summer, negative effects in winter
Many brook trout populations at risk in future Flow and temperature Extreme events
Can identify resilient populations
Steve Hurley
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Web app
Map viewer Standard layers Data Model results Select a basin for scenario tester
Scenario tester Climate -> Landuse -> Environment -> Population response Evaluate management actions under alternate futures
http://felek.cns.umass.edu:8080/geoserver/www/data.html
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Data types
Sensitivity of annual survival