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, MA

Why care about brook trout?

Widespread Found in most northeastern

streams with decent habitat Small isolated streams, rivers,

lakes, bogs, sea-run… Indicator of water quality

Temperature, acidity Sensitive to land use change

Mobile Habitat connectivity important

– what’s the key scale? Important component of

aquatic community Abundant Predation, food source,

nutrient dynamics

Invaders in the west Important to understand

population dynamics Important fishery

Native and stocked Indicator of functioning

habitat Sensitive species, harbinger

Good data available Distribution, local

abundance Individual-based studies

Who cares about brook trout?

Eastern Brook Trout Joint Venture Coalition of state and federal managers

The Nature Conservancy Connecticut River program

USFWS LCC project

USFS Long-term funding

Trout unlimited Sea-run brook trout coalition

Threats to population persistence

Habitat fragmentation Isolated populations

Water withdrawals Seasonal effects of stream flow

Land use/land change Riparian buffer, impervious

surfaces

Climate change Air temperature and

precipitation affecting: Stream flow and temperature

Interactions with climate change

Overall goal

Understand how populations work

What affects local population persistence?

Endpoint – probability of persistence after x years Body size distributions

Develop DSS tool for managers Probability of population

persistence under varying management scenarios

Eastern brook trout joint venture, 2007

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 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.

Approach

Data

Analysis

Model

Simulation

Management tool

Synthetic data collection and analysis to:

Account for multiple sources of

uncertainty Allow error propagation Provide answers in form of

statistical distribution How certain are we of result?

UncertaintiesMeasurement,Observation

Process[survival…]

Inputs[environment,GCC]

Run-to-run

Outcome[Persistence]

Approach

Data

Analysis

Model

Simulation

Management tool

Fine-scale data collection at multiple sites ~ 1 km, 20-m units Seasonal Tagged individuals, >35,000 since 1997

Model 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 strategies

What questions can we address?

Habitat fragmentation Which barriers do we prioritize for

removal/repair? Water withdrawal

How much water can be extracted? Importance of water source

How does extent of groundwater input affect persistence?

Climate change forecasts What are the effects of variation in

stream flow, temperature? Interactions

How much will effects of isolation and water supply be magnified under GCC?

Approach

ReproductionBody growth

SurvivalMovement

Age structureBody size

distributions

Population processes

AbundanceNe, Nb

Environment

Outcome

Stream TemperatureStream flow

HabitatFish community

Catchment scale model (< 1 Km)

Density dependence

Probability of

persistence

Fish modelFish

model

Links to Terrestrial project

Hydrologic model

DriversClimate change

Fish model

Seasonal settingPrecip, air TStream flow,

water T

Resulting DSS: evaluate alternate management strategies

DriversUrban

growth, etc

Decadal settingImpervious…Succession

Scen

ario

s

Habitat Caps

Probability of

persistence

Probability of

persistence

SeasonalDecadal

Near-term linkages between projects

Working with terrestrial group Develop models for catchments in three large

watersheds South, James River, VA Middle, ~Westfield River, MA North, Kennebec River, ME

Expand models to entire watersheds Collaborate with Eastern Brook Trout Joint Venture to

estimate occupancy in specific catchments Collaborate with Dept C+E Engineering and terrestrial

group to generate downscaled predictions of P and T and to develop hydrologic models

Project components

USFWS LCC Tasks 1-5

1 Post-doc, Paul Schueller (Feb 2012 - 2013)

1 PhD student, Krzysztof Sakrejda (current – 2013)

1 Programmer (2012-2013) USFWS LCC holdback

Flow modeling 1 post-doc, TBD (2011 – 2013)

USGS LCC Assist with tasks 1-5

1 post-doc, Doug Sigourney (current – 2013)

Add in evolutionary dynamics 1 post-doc, Michael Morrisey (Jan

2011 - 2013)

TNC fragmentation project Barrier removal/repair

prioritization 1 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 Polebitski

Decision support

Good understanding of catchment and sub-watershed population persistence models in MA

USFWS LCC and TNC funding to Scale up to watershed models Identify minimum data needs to scale up to among-

watershed models Evaluate GCC effects on the landscape Develop tools for managers to use

Not limited to well-studied systems Apply to specific sites to address management needs Can we apply models range-wide? Need test sites Better local data = more realistic simulations

Decision support

How will the DSS work? Identify management question Identify space and time scales Pick stream segments on web-based map Load local data

Environmental conditions, size distributions, community, genetics, movement data, etc

Simulation will automatically fine-tune model to local conditions

Run simulations Evaluate alternatives

Approach – working across scales

Hierarchical models Scale up Propagate error

Watershed Sub-watershed

Catchment

Among-watershed Multiple study sites

Fine scale (10 Km) Westfield River, western MA 100-m long sample sites 12 microsatellites Pairwise Fst 0.11 – 0.24 Assignment tests using Structure

Similar results in NH, VT, VA

Catchment and sub-watershed scales

Need detailed data, ~ 1 km

Spatial population genetics – what’s the right minimal scale?

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 antennas

Approach

Connected sub-watershed scale models

Watershed scale model (5-50 Km)

Watershed-scale

abundance and body size

Meta-population and genetic population structure

Outcomes

Movement

Movement is observed with radio-tagged fish and is inferred with genetic data

Approach – broad questions Do we need a detailed tagging

study for each catchment? Define catchment types

Size, connectivity Apply type to each unstudied

catchment Use 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, NH Planned for VA, PA/NJ (DEWA) Workshop in Feb

Defining these relationships is key

Progress to date

Development of linear models for Growth, survival,

movement Population dynamics

simulation incorporating existing estimates Climate change

scenarios Not hierarchical

High Q

Low Q

Control T x Control F = 174 yrs

Stronger climate change effect

Task Year 1 Year 2 Year 31. Hierarchical model development

1. Determine statistical model structure

2. Estimate statistical model parameters3. Develop simulation model based on #24. 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 interface2. 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

Probability of

persistence

Fish modelFish

model

Links to Terrestrial project

Hydrologic model

DriversClimate change

Fish model

Seasonal settingPrecip, air TStream flow,

water T

Resulting DSS: evaluate alternate management strategies

DriversUrban

growth, etc

Decadal settingImpervious…Succession

Scen

ario

s

Habitat Caps

Probability of

persistence

Probability of

persistence

SeasonalDecadal

Big questions Which 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 contraction Effects of stream flow and temperature Interactions between fragmentation and GCC

What are the best strategies to mitigate future challenges?

Challenges Scale

How to scale up? Space

Define a population – how big? Where are the fish? Importance of local adaptation? Can we apply models to unstudied or poorly studied systems?

Time Can 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? Population Individual Genotype

Uncertainty How propagate across scales?

For example, downscaled predictions of temperature and precipitation are uncertain in space and time

Need an approach to propagate this (and other) uncertainty all the way to projections of population persistence

Eastern brook trout joint venture, 2007

NA LCC

LandscapeConservationCooperative