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SALMONID (BROOK TROUT) POPULATION PERSISTENCE Development of a DSS Ben Letcher USGS, Conte Anadromous Fish Research Center, Turners Falls, MA Keith Nislow USFS, Northern Research Station, Amherst, MA
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Salmonid (Brook trout) population persistence

Feb 09, 2016

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Ben Letcher USGS, Conte Anadromous Fish Research Center, Turners Falls, MA Keith Nislow USFS, Northern Research Station, Amherst, MA. Salmonid (Brook trout) population persistence. Development of a DSS. Why care about brook trout?. Widespread - PowerPoint PPT Presentation
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Salmonid (Brook trout) population persistence Development of a DSSBen LetcherUSGS, Conte Anadromous Fish Research Center, Turners Falls, MA Keith NislowUSFS, Northern Research Station, Amherst, MA

Why care about brook trout?WidespreadFound in most northeastern streams with decent habitatSmall isolated streams, rivers, lakes, bogs, sea-run Indicator of water qualityTemperature, aciditySensitive to land use changeMobileHabitat connectivity important whats the key scale?Important component of aquatic communityAbundant Predation, food source, nutrient dynamics

Invaders in the westImportant to understand population dynamicsImportant fisheryNative and stockedIndicator of functioning habitatSensitive species, harbingerGood data availableDistribution, local abundanceIndividual-based studies

Who cares about brook trout?Eastern Brook Trout Joint VentureCoalition of state and federal managersThe Nature ConservancyConnecticut River programUSFWSLCC projectUSFSLong-term fundingTrout unlimitedSea-run brook trout coalition

Threats to population persistenceHabitat fragmentationIsolated populations Water withdrawalsSeasonal effects of stream flowLand use/land changeRiparian buffer, impervious surfaces

Climate changeAir temperature and precipitation affecting:Stream flow and temperature Interactions with climate change

Overall goalUnderstand how populations workWhat affects local population persistence?Endpoint probability of persistence after x yearsBody size distributionsDevelop DSS tool for managersProbability of population persistence under varying management scenarios

Eastern brook trout joint venture, 2007LCC project tasksTask 1: Hierarchical modeling framework to account for multiple scales and sources of uncertainty in climate change predictions

Task 2: Statistical models to predict stream flow and temperature based on air temperature and precipitation.

Task 3: Incorporate climate change forecasts into population persistence models

Task 4: Develop a decision support system for evaluating effects of alternate management strategies in the face of climate change.

Task 5. Develop curriculum and run training workshops for users of the decision support system.

ApproachSynthetic data collection and analysis to: Account for multiple sources of uncertainty Allow error propagationProvide answers in form of statistical distributionHow certain are we of result?

UncertaintiesMeasurement,Observation

Process[survival]

Inputs[environment,GCC]

Run-to-run

Outcome[Persistence]ApproachFine-scale data collection at multiple sites~ 1 km, 20-m unitsSeasonalTagged individuals, >35,000 since 1997

Model dynamics and uncertainty using Bayesian estimationGrowthSurvivalReproductionMovement

Combine statistical models into simulationsLink components- interactions

Develop management tool - DSSWeb-basedEvaluate alternate management strategies

What questions can we address?Habitat fragmentationWhich barriers do we prioritize for removal/repair?Water withdrawalHow much water can be extracted?Importance of water sourceHow does extent of groundwater input affect persistence?Climate change forecastsWhat are the effects of variation in stream flow, temperature?InteractionsHow much will effects of isolation and water supply be magnified under GCC?

ApproachReproductionBody growthSurvivalMovement

Age structureBody size distributionsPopulation processesAbundanceNe, NbEnvironmentOutcomeStream TemperatureStream flowHabitatFish community Catchment scale model (< 1 Km)Density dependenceProbability of persistenceFish modelFish modelLinks to Terrestrial projectHydrologic modelDriversClimate changeFish modelSeasonal settingPrecip, air TStream flow, water TResulting DSS: evaluate alternate management strategiesDriversUrban growth, etcDecadal settingImperviousSuccessionScenariosHabitatCapsProbability of persistenceProbability of persistenceSeasonalDecadalNear-term linkages between projectsWorking with terrestrial groupDevelop models for catchments in three large watershedsSouth, James River, VAMiddle, ~Westfield River, MANorth, Kennebec River, MEExpand models to entire watersheds Collaborate with Eastern Brook Trout Joint Venture to estimate occupancy in specific catchmentsCollaborate with Dept C+E Engineering and terrestrial group to generate downscaled predictions of P and T and to develop hydrologic models Project componentsUSFWS LCCTasks 1-51 Post-doc, Paul Schueller (Feb 2012 - 2013)1 PhD student, Krzysztof Sakrejda (current 2013)1 Programmer (2012-2013)USFWS LCC holdbackFlow modeling1 post-doc, TBD (2011 2013)USGS LCCAssist with tasks 1-51 post-doc, Doug Sigourney (current 2013)Add in evolutionary dynamics1 post-doc, Michael Morrisey (Jan 2011 - 2013)TNC fragmentation projectBarrier removal/repair prioritization1 post-doc, Cailin Xu (2008 - 2010)1 PhD student, Paul Schueller (2008 2012)1 TechnicianUSFSAir temperature/stream temperature relationshipSeveral techniciansUMassHydrologic modelDept of Civil and Environmental Engineering1 post-doc, ~Austin PolebitskiDecision supportGood understanding of catchment and sub-watershed population persistence models in MAUSFWS LCC and TNC funding to Scale up to watershed modelsIdentify minimum data needs to scale up to among-watershed modelsEvaluate GCC effects on the landscape Develop tools for managers to useNot limited to well-studied systemsApply to specific sites to address management needsCan we apply models range-wide? Need test sitesBetter local data = more realistic simulationsDecision supportHow will the DSS work?Identify management questionIdentify space and time scalesPick stream segments on web-based mapLoad local dataEnvironmental conditions, size distributions, community, genetics, movement data, etcSimulation will automatically fine-tune model to local conditionsRun simulationsEvaluate alternativesApproach working across scales Hierarchical modelsScale upPropagate error

WatershedSub-watershedCatchment

Among-watershedMultiple study sites

17Fine scale (10 Km)Westfield River, western MA100-m long sample sites12 microsatellitesPairwise Fst 0.11 0.24Assignment tests using Structure

Similar results in NH, VT, VA

Catchment and sub-watershed scalesNeed detailed data, ~ 1 kmSpatial population genetics whats the right minimal scale?

ApproachSub-watershed scale model (1-5 km)OutcomesConnected catchment scale models

Sub-watershed abundance and body sizeMovement patterns and catchment-specific production

MovementMovementMovementMovement is observed with repeat sampling and PIT tag antennasApproachConnected sub-watershed scale modelsWatershed scale model (5-50 Km)Watershed-scale abundance and body sizeMeta-population and genetic population structureOutcomes

MovementMovement is observed with radio-tagged fish and is inferred with genetic dataApproach broad questions Do we need a detailed tagging study for each catchment?Define catchment typesSize, connectivityApply type to each unstudied catchmentUse existing data to tune catchment type model to local conditions (Hierarchical Bayesian modeling)

Can we apply models across watersheds?Minimum local data needs?

Existing studies in MA, ME, NHPlanned for VA, PA/NJ (DEWA)Workshop in Feb

Defining these relationships is keyProgress to dateDevelopment of linear models for Growth, survival, movementPopulation dynamics simulation incorporating existing estimatesClimate change scenariosNot hierarchical

High QLow Q

Control T x Control F = 174 yrsStronger climate change effect TaskYear 1Year 2Year 31. Hierarchical model development 1. Determine statistical model structure2. Estimate statistical model parameters3. Develop simulation model based on #24. Combine all statistical models into simulation model 5. Incorporate simulation model into user interface2. Air temperature/ stream temperature model 1 Deploy paired temperature recorders2. Develop statistical model for paired temperature recorder data3. Apply statistical model to selected watersheds 3. Climate change modeling1. Obtain downscaled stream flow and temperature predictions for the West brook2. Develop model to apply downscaled estimates to selected watersheds4. Decision support system1. Develop web-based user interface2. Incorporate simulation model into web-based user interface5. Model use/application workshops1. Develop training tools2. Conduct training class at USFWS Region 5 office Probability of persistenceFish modelFish modelLinks to Terrestrial projectHydrologic modelDriversClimate changeFish modelSeasonal settingPrecip, air TStream flow, water TResulting DSS: evaluate alternate management strategiesDriversUrban growth, etcDecadal settingImperviousSuccessionScenariosHabitatCapsProbability of persistenceProbability of persistenceSeasonalDecadalBig questionsWhich barriers should be prioritized for repair/removal?How much water can be extracted from a stream?Minimum flows

How do populations with very low effective population size persist?Adaptation to isolation? What is the minimum patch size for persistence?Strongholds or hopeless?

How will brook trout populations respond to climate change?Range contractionEffects of stream flow and temperatureInteractions between fragmentation and GCC

What are the best strategies to mitigate future challenges?

ChallengesScaleHow to scale up?SpaceDefine a population how big?Where are the fish? Importance of local adaptation?Can we apply models to unstudied or poorly studied systems?TimeCan we apply short-term studies (1-15 years) to long-range forecasts (>50 years)?Timing of local adaptation?At what organizational level do we collect data?PopulationIndividualGenotype

UncertaintyHow propagate across scales? For example, downscaled predictions of temperature and precipitation are uncertain in space and timeNeed an approach to propagate this (and other) uncertainty all the way to projections of population persistence

Eastern brook trout joint venture, 2007NA LCC

LandscapeConservationCooperative