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

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?

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

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

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

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

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

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

Lambda response surfaces

Forecast

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

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

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

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

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

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

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

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

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

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

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

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

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

Data types Sensitivity of annual survival