1. 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 Dubreuil Conte 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

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 models Sensitivity of lambda Strong seasonal results Pathways of sensitivity  Abundance  Multiple-site demographic models Sensitivity of lambda Seasonal results with enough data Basin characteristics effects  Presence/absence  Occupancy models Basin characteristics effects Long-term mean effects

5. What can we estimate? Data typeModelEndpointBasin characterist ic effects? Yearly environment al effects Seasonal environment al effects Pathways of seasonal environment al effects PIT tagSingle-site demographic Population growth NoYes AbundanceMultiple-site demographic Population growth Yes Yes, but need lots of data No Pres/absOccupancyP(occupancy)YesNo

6. Data types West BrookIsolated  PIT tag  Single-site demographic model  Body growth, survival, movement, reproduction  Integral projection model  Abundance  Abundance models  Presence/absence  Occupancy models

7. Data types  Presence/absence  Occupancy models  Abundance  Abundance models  PIT tag  Mechanistic models Autumn

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

9. Lambda response surfaces

10. Forecast

11. 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

12. 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

13. 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

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

15. 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

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

17. 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

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

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

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

21. Bringing it together VariableSeasonModel Single-site demographic Multiple-site demographic Occupancy FlowFall↑ **↑ *** Precip ↑ Winter↓ ** Spring↔↔ Summer↑ ***NA TemperatureFall↓ **NA Temperature ↓ Winter↔NA Spring↔↔ Summer↓ ***NA

22. 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

24. 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

25. Data types Sensitivity of annual survival