Transcript preliminary - Trout Unlimited

The Salmonid Population Viability Project
Lahontan Cutthroat Trout Viability
The Salmonid Population Viability Project Team
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Seth Wenger, Doug Leasure, UGA River Basin Center
Helen Neville, Dan Dauwalter, Robin Bjork, Kurt Fesenmyer and Jean Barney,
Trout Unlimited
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Erin Landguth, University of Montana

Jason Dunham, Nate Chelgren, USGS
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Dan Isaak, Charlie Luce & Zach Holden, USFS Rocky Mountain Research
Station
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Mary Peacock, University of Nevada-Reno
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Joe Glassy, Lupine Logic, Inc.

Doug Peterson, US Fish & Wildlife Service
The motivation: better conservation planning
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How “healthy” is each
population?
Which would benefit most
from what management
actions?
Which ones are hopeless?
Where could we reintroduce?
How might climate change
affect populations?
What we really want: Estimates of population
viability
In practice…
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We often use surrogates or rules of thumb
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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
Trout Unlimited’s Conservation Success
Index for Westslope Cutthroat trout
Why aren’t we using PVA more?
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Data-intensive: 7-10 years of consecutive abundance
estimates are the minimum for each population.
Each population is modeled separately. Limited options for
extrapolation.
Alternative modeling approaches (e.g., RAMAS) require
parameters that must be estimated from literature values–
make limited use of field data.
Alternative approach: STPVM
The Spatio-Temporal Statistical Population Viability Model (STPVM)
• PVA on many populations at once
• Provides quantitative extinction estimates for each population
• Can test effects of management actions
preliminary
How STPVM works:
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Models are fit using
actual observations of
organisms across
populations simultaneously
Applicable to any species
with appropriate data;
not limited to fish
P1
P3
P2
?
NPS.gov
P4
The advantages
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Models produce actual estimates of viability for
each population– this is what we really want
Enable range-wide quantitative assessment of
overall status – also what we really want
They use all available field *data*
Simultaneous estimation across multiple
populations 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
S. Walsh
Applying ST-PVM to Lahontans
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Lahontan cutthroat trout are ideal for ST-PVM
because they are found mostly in small, isolated
populations
They have been intensively sampled (lots of data)
Building the fish database
The full database will be available to project partners
• 154 populations total
• 63 FWS conservation
populations
• 1,907 sampling sites
• 6,227 sampling events
• 33,750 individual fish
ST-PVM: A Hierarchical Model
Observation Model
Sampling Model
Process Model
ST-PVM: Observation Model
Observation Model
Sampling Model
Process Model
Population 1
1995
2001
Site
Pass 1
Pass 2
Pass 3
Site
Pass 1
A
10
7
2
B
17
B
23
12
D
C
12
1
E
0
Pass 2
Pass 3
9
2
0
15
1
Population 2
1991
…
2010
Site
Pass 1
Pass 2
Pass 3
Site
Pass 1
Pass 2
Pass 3
A
14
7
6
D
20
B
0
0
0
E
14
12
0
C
9
8
0
F
1
0
…
…
…
ST-PVM: Observation Model
Detection Probability
Observation Model
Sampling Model
Process Model
1
Detection at pass 1:
Drainage Area + Flow Conditions
0.5
0
1
2
Pass Number
3
ST-PVM: Observation Model
Observation Model
Year: 1995
Sampling Model
Process Model
Fish: 12 ± 5
Fish: 31 ± 11
Fish: 42 ± 15
Fish: 8 ± 4
Fish: 10 ± 7
Lets us use # of fish
caught to estimate
# not caught, with
error
ST-PVM: Sampling Model
Observation Model
Sampling Model
Process Model
Year: 1995
Proportion of
Population Size in 1995:
Population Sampled:
757 ± 132 fish
13.6% ± 5
Total fish at sampled sites: 103 ± 42
Total sampled length: 340 m
Population Extent: 2,500 m
ST-PVM: Process Model
Observation Model
Sampling Model
Process Model
Based on a modified Ricker Model, with covariates
Pop. Growth Rate (r)
Carrying Capacity (K)
• Stream Temperature
• High Flow Magnitude
• Low Flow Magnitude
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Population Extent
Brook Trout
Low Flow Magnitude
NDVI
Density-Independent
Mortality (d)
• Severe floods
• Wildfires
ST-PVM: Population Assessments
Population Size
Observation Model
Sampling Model
preliminary
Process Model
ST-PVM: Population Assessments
Population Size
Observation Model
Sampling Model
Process Model
preliminary
Population Viability: 2025 Extinction Probability
For current
LCT
Conservation
Populations
as well as
other historic
habitats
preliminary
The Covariates
Ecological Forecasting
Covariates: Normalized Difference
Vegetation Index (Landsat, 1985-present)
Active photosynthesis and vegetation
1992 – Dry year
2011 – Wet year
Maximum NDVI (for catchment) by Population
Dry year
Wet year
high precipitation year
Covariates- Stream Temperature
Developed new stream temperature database,
also available to partners
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Data from 14 agencies
502 thermograph sites
741 site-years
Covariates- Stream Temperature
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Annual estimates
of mean August
stream
temperature for
every 1km stream
segment
Current and
future climate
conditions
Covariates- Stream flow
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Currently from the VIC macroscale hydrologic model
Working on alternative, updatable approach
Stream drying
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Many streams are intermittently dry
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Jason Dunham is deploying sensor
networks range-wide to model desiccation
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Will incorporate results in future
Covariates: Brook Trout Densities
Scenarios:
what if we…
Management scenarios
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Brook trout suppression/removal scenarios
Reintroduction potential of different habitats
Metapopulation reconnection
Cattle fencing/riparian restoration?
 Thermal
degradation
We are building a tool to let users
examine these alternatives.
What if we remove brook trout?
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BKT: SD = +4
preliminary
What if we remove brook trout?
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BKT: SD = 0
preliminary
What is best way to reintroduce?
10 fish
10 + 10 + 10
preliminary
100 fish
Metapop Reconnect
Metapop Reconnect
preliminary
Climate Change
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We can estimate changes in covariates in coming
decades
 Still
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working on flow projections
We can’t do desiccation very well, yet but coming
soon…
Next phase
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We hope to work with LCT management teams to
provide a useful tool for a “Recovery Roadmap”
 Hand
over LCT database for continued update
 Publish in peer-reviewed journal
 Continue to update models and scenarios
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Beginning data phase for Bonneville cutthroat trout
and interior redband trout
Acknowledgements: Funding
NASA grant number NNX14AC91G
 Bureau of Land Management, National co-op
 Trout Unlimited
 US FWS
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