great basin lcc webinar series · a recording of today’s webinar and slides from the presentation...
TRANSCRIPT
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Great Basin LCC Webinar SeriesThe Salmonid Population Viability Project: Developing decision-support tools to improve at-risk trout population management
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The Salmonid Population Viability Project
Lahontan Cutthroat Trout
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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
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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?
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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
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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.
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Pop
ula
tion
size
Population Viability Analysis (PVA)
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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’
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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
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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
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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
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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)
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MPVA: A Hierarchical Model
Observation Model Sampling Model Process Model
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MPVA: A Hierarchical Model
Observation Model Sampling Model Process Model
Field data: how
many fish are in
the sites we
sampled this
year?
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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
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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
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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
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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
…
… …
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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
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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
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MPVA: A Hierarchical Model
Observation Model Sampling Model Process Model
Time (t)
Popula
tion S
ize (
N)
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MPVA: A Hierarchical Model
Observation Model Sampling Model Process Model
Project
Forward
Extinction
Probability
Time (t)
Popula
tion S
ize (
N)
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LCT data
given back to agency
partners
1982-2016
Field data from
NDOW
ODFW
CDFW
UNR
TU
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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)
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Habitat quality, flow, temperature, fire and non-native trout
Need environmental characteristics available for
all populations and relevant to fish:
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Many of which can be captured with remote
sensing:
Ecological Forecasting
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Covariates: Normalized Difference
Vegetation Index (Landsat, 1985-present)
1992 – Dry year 2011 – Wet year
NDVI: Active photosynthesis and vegetation
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Covariates- Stream Temperature
Annual estimates
of mean August
stream
temperature for
every 1km stream
segment
Current and
future climate
conditions
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Covariates- Flow
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Covariates- Non-native trout
Project forward at
most recent density
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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
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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?
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Management scenarios
We have built a tool to let users examine these
alternatives.
http://trout.shinyapps.io/lahontanFull modelReal-time simulations
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
(Can enter negative numbers to look
at impact of removals from potential
source population)
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
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LCT Population Simulator
Enables user-evaluation of management actions/priorities
http://trout.shinyapps.io/lahontan
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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?
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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
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Desert redband and Bonneville cutthroat trout to come…
Photo: CDFW
Photo: Wikipedia
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THE SALMONID POPULATION VIABILITY PROJECT: DEVELOPING DECISION-SUPPORT TOOLS TO IMPROVE AT-RISK TROUT POPULATION MANAGEMENT
Helen Neville, [email protected]
Jon Sjoberg, [email protected]
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, [email protected], (775) 861-6492
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