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Great Basin LCC Webinar SeriesThe Salmonid Population Viability Project: Developing decision-support tools to improve at-risk trout population management

The Salmonid Population Viability Project

Lahontan Cutthroat Trout

The Salmonid Population Viability Project Team

Seth Wenger, Doug Leasure, UGA River Basin Center

Helen Neville, Dan Dauwalter, Robin Bjork, Kurt Fesenmyer and Jean Barney, Trout Unlimited

Erin Landguth, University of Montana

Jason Dunham, Nate Chelgren, USGS

Dan Isaak, Charlie Luce & Zach Holden, USFS Rocky Mountain Research Station

Mary Peacock, University of Nevada-Reno

Acknowledgments: Funding

The motivation: better conservation planning

Managers of any species of conservation interest need to know things like:

Which populations are most likely to persist?

Which would benefit most from what management actions?

Where could we reintroduce?

How might climate change affect populations?

What we really want:

Quantitative estimates of population viability –

or, conversely, extinction risk

Understanding of major drivers of population

dynamics to identify management opportunities

National Wildlife Federation Wikkipedia

Quantitative estimates are necessary for

defensible management

“… the Court concludes that in the absence of evidence of

the current population level, the lack of projected decline in

that population, and the failure

to define an extinction threshold,

the evidence is insufficient to

support a finding that Arctic

ringed seals are threatened

with extinction in the foreseeable

future.”-District Court of Alaska,

vacating the listing of the Arctic

ringed seal under the ESA.

Pop

ula

tion

size

Population Viability Analysis (PVA)

We don’t use PVA as much as we could: why?

Data-intensive – 7-10 years of consecutive abundance

estimates are the minimum for each population

Each population is modeled separately. Limited options for

extrapolation across populations for an understanding of

landscape-scale influences

In alternative modeling approaches (e.g., RAMAS),

parameters* are defined from literature values – make limited

use of field data

*parts of the equation that define/constrain

behavior of populations, e.g. ‘population growth

rate’

In practice…

We often use surrogates, or rules of thumb

• Habitat size (Hilderbrand and Kershner 2000: 8-25 km)

• Land cover, land use

• Climate vulnerability

These surrogates may not be validated, and often

cannot be validated as related to actual viability

Part of TU’s Conservation Success

Index: assessment for prioritizing conservation

strategies

P3

P1

P4

P2

?

NPS.gov

We developed an alternative approach:

Multiple Population Viability Analysis (MPVA)

Statistical model

PVA on many populations at once

Models are fit using actual

observations of organisms (data)

across populations simultaneously

Simultaneous estimation lets us

borrow information to estimate

viability for populations with

little/no data

Allow us to explore which

variables across the landscape

most affect viability

The advantages

Models produce quantitative estimates of

viability – this is what we really want

Enable range-wide assessment of status – also

what we really want

Use all available *data*

Let us test effects of management actions

Applicable to any species with appropriate data;

not limited to fish

S. Walsh

Applying MPVA to Lahontan cutthroat trout (LCT)

Lahontan cutthroat trout are ideal for MPVA:

They are ESA listed, of high conservation interest

They are found mostly in small, isolated populations

They have been intensively sampled (lots of data)

(also applying to redband trout and Bonneville cutthroat

trout)

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

Field data: how

many fish are in

the sites we

sampled this

year?

Uses all field data

Observation Model Sampling Model Process Model

Pass 1: 10 fish

Pass 2: 7 fish

Pass 3: 2 fish

TOTAL caught: 19 fish

Year: 1995 How many fish did we miss?

Estimated # fish at site =

observed + unobserved

Depletion estimator

# o

f fi

sh

Uses all field data

Observation Model Sampling Model Process Model

Year: 1995 Depletion estimators often

assume unrealistic things -- like

same capture probability for

all passes -- and don’t

incorporate site-level

environmental variables

Pass 1: 10 fish

Pass 2: 7 fish

Pass 3: 2 fish

TOTAL caught: 19 fish

Uses all field data

Observation Model Sampling Model Process Model

Year: 1995 We’ve incorporated a data-

driven, site-level estimator of

capture probabity that includes

watershed size and flow, and

captures error

Pass 1: 10 fish

Pass 2: 7 fish

Pass 3: 2 fish

TOTAL caught: 19 fish

Uses data collected in various ways

Site Pass 1 Pass 2 Pass 3

A 10 7 2

B 23 12

C 12 1 0

1995

Pop

ula

tion

1 Site Pass 1 Pass 2 Pass 3

B 17

D 9 2 0

E 15 1

2001

…

Site Pass 1 Pass 2 Pass 3

A 14 7 6

B 0 0 0

C 9 8 0

1991

Pop

ula

tion

2 Site Pass 1 Pass 2 Pass 3

D 20

E 14 12 0

F 1 0

2010

…

… …

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

Field data: how

many fish are in

the sites we

sampled this

year?

How big is the

population this

year?

Scales up site-level

information to estimate

population size, with error

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

Field data: how

many fish are in

the sites we

sampled this

year?

How big is the

population this

year?

What happens

over time…

Scales up site-level

information to estimates of

population size

Uses relationships with

environmental and

biological influences to

predict over time

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

Time (t)

Popula

tion S

ize (

N)

MPVA: A Hierarchical Model

Observation Model Sampling Model Process Model

Project

Forward

Extinction

Probability

Time (t)

Popula

tion S

ize (

N)

LCT data

given back to agency

partners

1982-2016

Field data from

NDOW

ODFW

CDFW

UNR

TU

Built a new database for LCT

given back to agency

partners

232 populations

69 FWS conservation populations

2,233 sampling sites

34,062 individual LCT

44,966 individual trout (including non-natives)

Information on eradications and reintroductions Have given this back to the

agencies – NDOW to host and

update

(Needed individual-level detail)

Habitat quality, flow, temperature, fire and non-native trout

Need environmental characteristics available for

all populations and relevant to fish:

Many of which can be captured with remote

sensing:

Ecological Forecasting

Covariates: Normalized Difference

Vegetation Index (Landsat, 1985-present)

1992 – Dry year 2011 – Wet year

NDVI: Active photosynthesis and vegetation

Covariates- Stream Temperature

Annual estimates

of mean August

stream

temperature for

every 1km stream

segment

Current and

future climate

conditions

Covariates- Flow

Covariates- Non-native trout

Project forward at

most recent density

Model output: 2045 Extinction Probability

**Note that any currently-

unoccupied waters are

identified as ‘extinct’, but the

viability of reintroduced LCT

can be evaluated in our user-

friendly simulation module

Management scenarios: what if

we…

Remove nonnatives?

Reintroduce LCT to a given habitat?

Remove fish from LCT population to restore another?

Improve flows, reduce temperatures?

Management scenarios

We have built a tool to let users examine these

alternatives.

http://trout.shinyapps.io/lahontanFull modelReal-time simulations

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

(Can enter negative numbers to look

at impact of removals from potential

source population)

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

LCT Population Simulator

Enables user-evaluation of management actions/priorities

http://trout.shinyapps.io/lahontan

LCT Population Simulator

Will are building a batch capacity to address needs for large-scale

recovery planning, e.g., “How does extinction risk change

rangewide/by GMU if we…”:

…remove all non-natives?

…experience X% warming across the range?

LCT Population Simulator

Models can/should be updated with new data on fish and covariates

(environmental influences)

Working with partners on planning and funding for future updating

Range-wide comparison of risk estimates with genetic metrics

Desert redband and Bonneville cutthroat trout to come…

Photo: CDFW

Photo: Wikipedia

Thanks! And now Jon Sjoberg…

THE SALMONID POPULATION VIABILITY PROJECT: DEVELOPING DECISION-SUPPORT TOOLS TO IMPROVE AT-RISK TROUT POPULATION MANAGEMENT

Helen Neville, HNeville@tu.org

Jon Sjoberg, sjoberg@ndow.org

A recording of today’s webinar and slides from the presentation will be available at www.GreatBasinLCC.org.

For more information on the Great Basin LCC webinar series contact:

John Tull, Science Coordinator, john_tull@fws.gov, (775) 861-6492

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