Salmonid (Brook trout) population persistence - PowerPoint Presentation

Slide1

Salmonid (Brook trout) population persistence

Development of a DSS

Ben LetcherUSGS, Conte Anadromous Fish Research Center, Turners Falls, MA Keith NislowUSFS, Northern Research Station, Amherst, MASlide2

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 – what’s the key scale?Important component of aquatic communityAbundant Predation, food source, nutrient dynamicsInvaders in the westImportant to understand population dynamicsImportant fisheryNative and stockedIndicator of functioning habitatSensitive species, harbingerGood data availableDistribution, local abundanceIndividual-based studiesSlide3

Who cares about brook trout?

Eastern Brook Trout Joint VentureCoalition of state and federal managersThe Nature Conservancy

Connecticut River programUSFWSLCC projectUSFSLong-term fundingTrout unlimitedSea-run brook trout coalitionSlide4

Threats to population persistence

Habitat fragmentationIsolated populations Water withdrawals

Seasonal effects of stream flowLand use/land changeRiparian buffer, impervious surfacesClimate changeAir temperature and precipitation affecting:Stream flow and temperature Interactions with climate changeSlide5

Overall goal

Understand 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 scenariosEastern brook trout joint venture, 2007Slide6

LCC project tasks

Task 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 modelsTask 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. Slide7

Approach

Synthetic 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,ObservationProcess[survival…]Inputs[environment,GCC]Run-to-run

Outcome[Persistence]Slide8

Approach

Fine-scale data collection at multiple sites

~ 1 km, 20-m unitsSeasonalTagged individuals, >35,000 since 1997Model dynamics and uncertainty using Bayesian estimation

Growth

Survival

Reproduction

Movement

Combine statistical models into simulations

Link components- interactions

Develop management tool - DSS

Web-based

Evaluate alternate management strategiesSlide9

What questions can we address?

Habitat fragmentationWhich barriers do we prioritize for removal/repair?Water withdrawal

How 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?Slide10

Approach

Reproduction

Body growthSurvivalMovementAge structureBody size distributions

Population

processes

Abundance

N

e

,

N

b

Environment

Outcome

Stream Temperature

Stream flow

Habitat

Fish community

Catchment scale model (< 1 Km)

Density dependenceSlide11

Probability of persistence

Fish model

Fish modelLinks to Terrestrial projectHydrologic modelDriversClimate changeFish model

Seasonal setting

Precip

, air T

Stream flow, water T

Resulting DSS: evaluate alternate management strategies

Drivers

Urban growth, etc

Decadal setting

Impervious…

Succession

Scenarios

Habitat

Caps

Probability of persistence

Probability of persistence

Seasonal

DecadalSlide12

Near-term linkages between projects

Working 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 Slide13

Project components

USFWS 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 Technician

USFS

Air temperature/stream temperature relationship

Several technicians

UMass

Hydrologic model

Dept of Civil and Environmental Engineering

1 post-doc, ~Austin

PolebitskiSlide14

Decision support

Good 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 simulationsSlide15

Decision support

How will the DSS work?Identify management question

Identify 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 alternativesSlide16
Slide17

Approach – working across scales

Hierarchical modelsScale up

Propagate errorWatershedSub-watershedCatchmentAmong-watershedMultiple study sitesSlide18

Fine scale (10 Km)Westfield River, western MA

100-m long sample sites12 microsatellitesPairwise Fst 0.11 – 0.24

Assignment tests using StructureSimilar results in NH, VT, VACatchment and sub-watershed scalesNeed detailed data, ~ 1 kmSpatial population genetics – what’s the right minimal scale?Slide19

Approach

Sub-watershed scale model (1-5 km)

OutcomesConnected catchment scale modelsSub-watershed abundance and body size

Movement patterns and catchment-specific production

Movement

Movement

Movement

Movement is

observed

with repeat sampling and PIT tag antennasSlide20

Approach

Connected sub-watershed scale models

Watershed scale model (5-50 Km)Watershed-scale abundance and body sizeMeta-population and genetic population structure

Outcomes

Movement

Movement is

observed

with radio-tagged fish and is

inferred

with genetic dataSlide21

Approach – broad questions

Do we need a detailed tagging study for each catchment?Define catchment typesSize, connectivity

Apply 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 FebDefining these relationships is keySlide22

Progress to date

Development of linear models for Growth, survival, movementPopulation dynamics simulation incorporating existing estimates

Climate change scenariosNot hierarchicalHigh QLow QControl T x Control F = 174 yrsStronger climate change effect Slide23

Task

Year 1

Year 2

Year 3

1. Hierarchical

model development

1. Determine statistical model structure

2. Estimate statistical model parameters

3. Develop simulation model based on #2

4. Combine all statistical models into simulation model

5. Incorporate simulation model into user interface

2.

Air

temperature/ stream temperature model

1 Deploy paired temperature recorders

2. Develop statistical model for paired temperature recorder data

3. Apply statistical model to selected watersheds

3. Climate

change modeling

1. Obtain downscaled stream flow and temperature predictions for the West brook

2. Develop model to apply downscaled estimates to selected watersheds

4. Decision

support system

1. Develop web-based user interface

2. Incorporate simulation model into web-based user interface

5. Model

use/application workshops

1. Develop training tools

2. Conduct training class at USFWS Region 5 office Slide24

Probability of persistence

Fish model

Fish modelLinks to Terrestrial projectHydrologic modelDriversClimate changeFish model

Seasonal setting

Precip

, air T

Stream flow, water T

Resulting DSS: evaluate alternate management strategies

Drivers

Urban growth, etc

Decadal setting

Impervious…

Succession

Scenarios

Habitat

Caps

Probability of persistence

Probability of persistence

Seasonal

DecadalSlide25
Slide26

Big questions

Which barriers should be prioritized for repair/removal?How much water can be extracted from a stream?

Minimum flowsHow 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 GCCWhat are the best strategies to mitigate future challenges?Slide27

Challenges

ScaleHow 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?PopulationIndividualGenotypeUncertaintyHow 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 persistenceEastern brook trout joint venture, 2007Slide28

NA LCC

Landscape

ConservationCooperative