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Brook trout population dynamics: Integrated modeling across scales and data types

Ben Letcher, Yoichiro Kanno , Ron Bassar , Ana Rosner, Paul Schueller , Kyle O’Neil, Krzysztof Sakrejda , Matt O'Donnell, Todd Dubreuil Conte Anadromous Fish Research Center, U.S. Geological Survey, Turners Falls, MA, USA. Keith H. Nislow, Jason Coombs

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Brook trout population dynamics: Integrated modeling across scales and data types

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  1. Ben Letcher, YoichiroKanno, Ron Bassar, Ana Rosner, Paul Schueller, Kyle O’Neil, Krzysztof Sakrejda, Matt O'Donnell, Todd Dubreuil Conte Anadromous Fish Research Center, U.S. Geological Survey, Turners Falls, MA, USA Keith H. Nislow, Jason Coombs Northern Research Station, USDA Forest Service, Amherst, MA, USA Steve Hurley Andrew Whiteley Department of Natural Resources Conservation UMass, Amherst, MA, USA Brook trout population dynamics: Integrated modeling across scales and data types

  2. 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?

  3. 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

  4. Data types • PIT tag • Single-site demographic model • Body growth, survival, movement, reproduction • Integral projection model • Abundance • Abundance models • Presence/absence • Occupancy models West Brook Isolated

  5. Lambda sensitivities Spring ↔ Winter ↔ Autumn ↓ Summer ↓ Summer↑ Autumn ↑ Spring ↔ Winter↓

  6. Lambda response surfaces

  7. Forecast

  8. Data types • PIT tag • Single-site demographic model • Abundance • Abundance models • Autumn, Winter, Spring Flow • Spring Temperature • Elevation • State space • Population projection • Presence/absence • Occupancy models Age-0+ > age-0+ All Yearly data, many sites

  9. 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

  10. 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

  11. Forecasts • Presence/absence • Occupancy models • Abundance • Abundance models • Simple population projection - state space • PIT tag • Mechanistic models ↑ ↓ ↔ ↔

  12. 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

  13. Data types • PIT tag • Single-site demographic model • Abundance • Abundance models • Presence/absence • Occupancy models Single or multiple year data, many sites

  14. Model estimates • 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 Precip % forest Air T

  15. Probability of Occupancy for Current Conditions • Model drivers • Drainage area • Forest cover • Stream slope • Annual precipitation • Minimum temperature • Soil drainage class

  16. Probability of Occupancy for Current Conditions Probability of Occupancy 2 C increase Probability of Occupancy 4 C increase • Model drivers • Drainage area • Forest cover • Stream slope • Annual precipitation • Minimum temperature • Soil drainage class

  17. Probability of Occupancy for Current Conditions Resilience of occupancy to temperature increase • Model drivers • Drainage area • Forest cover • Stream slope • Annual precipitation • Minimum temperature • Soil drainage class

  18. Bringing it together

  19. 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

  20. 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

  21. Data types Sensitivity of annual survival

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