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Outline• Implementing single-population PVAs• Landscape models of habitat,
population structure, and persistence• Putting the pieces together for
management on the ground
Conservation biology in practice: lessons from a threatened fish
Cutthroat trout distribution-
Eight major subspeciesIn North America
*All listed under ESAor of “special concern”
Cutthroat trout distribution-
Eight major subspeciesIn North America
*All listed under ESAor of “special concern”
Lahontan cutthroat trout
Eastern Lahontan basin
Status
•Federally listed threatened species (1973)
•<15% of historical habitat occupied
•>20 populations gone since listing
Threats
•Habitat loss and fragmentation
•Nonnative trout
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Goldfield Nevada, ca. 1900 Rawhide Nevada, 1908
Cattle drive Elko Co. 1940 Cattle grazing, Washoe Co. 1940
Habitat loss: “legacy” effects of past land uses Continuing land uses that affect habitat
Roads andculverts
Livestock grazing(Elko BLM photos)Altered fire regimes
Mining Agricultural and municipal water use
Nonnative trout
Photo credit: USFS
Photo credit: USFS
Photo credit: R.M. McDowallPhoto credit: Pam Fuller
Brook trout Rainbow trout
Brown trout Cutthroat trout
Management issues
•How do we identify populations at risk?
•Single-population PVAs•Landscape models of persistence•Developing a conservation assessment
Population viability analysis
A comprehensive analysis of the many environmental and demographic factors affecting the survival of a population, usually applied to small populations at risk of extinction.
Population viability analysis
A comprehensive analysis of the many environmental and demographic factors affecting the survival of a population, usually applied to small populations at risk of extinction.
What are the four main factorsthat cause extinctions in small populations?
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PVA Model
GeneticsDemography
EnvironmentCatastrophe
PVA Model
GeneticsDemography
EnvironmentCatastrophe
What data do we need for a PVA???
PVA Model
GeneticsDemography
EnvironmentCatastrophe
A short list of possible things to know•Demography (age, stage, size…)
•Birth, death, maturity, fecundity, survival, etc.
•Relationships between demography and key drivers
•Intrinsic – density dependence, genetic factors•Extrinsic – environmental drivers, catastrophes
•Information on environmental variability•Models to relate the above and project dynamics
PVA Model
GeneticsDemography
EnvironmentCatastrophe
What outputs do we want from a PVA?
PVA Model
GeneticsDemography
EnvironmentCatastrophe
•What is the probability of persistence?•What is the minimum viable population size?•What factors are most important – model sensitivity?•What are the biggest sources of uncertainty?
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
1978
1979
1980
1981
1982
1983
1984
1985
1993
1994
1995
1996
1997
1998
1999
2000
Po
p S
ize
(Ag
es 1
+)
Developing a model for LCT(Chris Ray and Mary Peacock)
Total population trends in Gance Creek
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0
50
100
150
200
250
300
350
1978 1979 1980 1981 1982 1983 1984 1985 1993 1994 1995 1996 1997 1998 1999 2000
1+ 2+ 3+ 4+ 5+ 6+
reduced (but sufficient) sampling effort
Dynamics among age classes A very simple population growth model(simple is better)
What factors drive recruitment and survival???
N1 N2 N3 N4
Recruitment
Survival
Potential recruitment models
fall t
winter t-1
fall t-1
summer t-1
spring t-1
summer t
spring t
(-) (+)
Which model is most
consistent with the data?
Predicting recruitment
R 2 = 0.64
P = 0.02
0
500
1000
1500
2000
2500
3000
3500
4000
4500
0 500 1000 1500 2000 2500 3000 3500 4000
combined flow* predictorRt ~ flowt-1 – flowt
(*flow = March-June average daily CFS)
recr
uit
s th
is y
ear
(Rt)
flow last year
recr
uit
s th
is y
ear
flow this year
recr
uit
s th
is y
ear
Potential recruitment models
fall t
winter t-1
fall t-1
summer t-1
spring t-1
summer t
spring t
(-) (+)
Best recruitment model
fall t
spring t-1
spring t
(-) (+)
Survival is density-dependent
R 2 = 0.48**
R 2 = 0.48**
R 2 = 0.50**
-4
-3
-2
-1
0
1
2
0 1000 2000 3000 4000 5000
number in age class
survivalln(n t+1 /n t+.01)
age 1-2 yrs
age 2-3 yrs
age 3-4 yrs
5
Spring Flowaverage daily CFSMarch 1 - June 30
Marys River
0
100
200
300
400
500
600
1940 1950 1960 1970 1980 1990 2000
N0
0
500
1000
1500
2000
2500
3000
3500
4000
4500
0 500 1000 1500 2000 2500 3000 3500 4000
combined flow predictor
R0
N1
R2 = 0.48**
R2 = 0.48**
R2 = 0.50**-4
-3
-2
-1
0
1
2
0 1000 2000 3000 4000 5000number in class
S0
Projecting population dynamics
N1 N2 N3 N4
Survival = f (within-class density dependence)
# Age 1+ = f (stream discharge)
“Flow – density” model
Sensitivity AnalysisVariation in streamflows
basemodel
Foreman
Frazer
Gance
lowercapacity
lowerflows
higherflows
highervariancepop
> 5%
< 5%
< 1%
“risk”
Genetic bottlenecks and isolation(Helen Neville 2003)O R E G O NO R E G O N
II DD AA HH OOII DD AA HH OO
0 50 100 150 200 km0 50 100 150 200 km
NN EEVV AA DD AANN EEVV AA DD AA
ReeseReeseRiverRiver
CoyoteLake BasinCoyoteLake Basin
Walker LakeWalker LakeWalker RiverWalker River
Carson RiverCarson River
Lake TahoeLake Tahoe
HumboldtHumboldtRiverRiver
NNN
CALIFORNIACALIFORNIA
Truckee RiverTruckee River
Pyramid LakePyramid LakePyramid Lake
QuinnRiverQuinnQuinnRiverRiver
Summit LakeSummit Lake
Review• Factors affecting populations
– Small is not beautiful (but simple is)!• PVA simulations indicate loss of habitat is the largest
demographic risk• PVA inferences supported by evidence for genetic
bottlenecks or founder events in smaller isolated populations
• None of these places (so far) has nonnative trout…• And, none has been applied to more than a handful
of populations…
Zooming out to look at many populations – “landscape” models
• How to describe a “landscape” for trout?• How does landscape structure relate to
persistence?
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Defining the fish-scape• Fish populations are not uniformly distributed
across the landscape
Defining the fish-scape• Fish populations are not uniformly distributed
across the landscape• Fish distributions usually tied to specific habitat
features – both are patchy – both can be mapped
A thermal bull trout - scape
Spawningand rearing(suitable year-round)
Migratory(seasonal use)
Unsuitable
Refugium
“Latitude” (UTM north X 10“Latitude” (UTM north X 1066))4.34.3 4.44.4 4.54.5 4.64.6 4.74.7
14001400
16001600
18001800
20002000
22002200
24002400
26002600
28002800
Ele
vati
on
(m
) o
f E
leva
tio
n (
m)
of
do
wn
stre
am
do
wn
stre
am
dis
trib
uti
on
lim
its
dis
trib
uti
on
lim
its
R2 = 0.67-0.71P < 0.001
Streams with Lahontancutthroat trout onlyn = 19 from UNR surveys
n = 11 from agency surveys
Fish distributions among streams on a regional scale
4.3 4.4 4.5 4.6 4.7
1400
1600
1800
2000
2200
2400
2600
2800
“Latitude” (UTM north X 106)
Ele
vati
on
(m
) o
f d
ow
nst
ream
d
istr
ibu
tio
n li
mit
s
Effects of nonnative trout
Baseline predictionfrom “allopatric” model
GIS“PATCH”
DELINEATION
= “Pour”point
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Patch structure: Eastern Lahontan basin
Reese River sub-basin Patch networksand isolated patches
Patcheswithin networks
50 km
Defining Habitat Fragmentation
Patches = populations?
Within-patch
genetic structuring
(Neville 2003)
Patch area (ha)
103 104 105
0.00
0.25
0.50
0.75
1.00 Probability of occurrence
Habitat fragmentation and persistence of local populations
Few large, many very small
Patch area (ha)0 20000 40000 60000
0
20
40
60
80
100Percentage of patches
Var
ian
ce in
p
atch
qu
ality
Dispersal distanceInterpatch distance
Metapopulation dynamics – Key Factors
1) PATCH QUALITY (E.G. SIZE, PRODUCTIVITY)
2) PATCH ISOLATION
3) SPECIES’ DISPERSAL ABILITY
ISLAND-MAINLANDISLAND-MAINLAND
PATCHYPATCHYLEVINSLEVINSNON-EQUILIBRIUMNON-EQUILIBRIUM
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Landscape-metapopulation perspectives
• Emerging work shows key linkages• Least understood scale in management
Fausch et al. (2002)“Riverscapes”
Number and condition of DPSsRegion
Number and condition of recovery units in a DPS
Subbasin
Number of patches, overall pattern of connectivity, distribution of conditions among patches
Patch network
Size, connectivity, distribution of conditions within patches
Patch
Temperature, channel features, etc.
SitePotential indicatorsScale
Patches = “intermediate” scale?
(Dunham et al. 2002)
Review• Habitat loss and fragmentation is a major
threat• Nonnative trout also appear to be important,
but influences are highly variable• Effects of habitat fragmentation are
predictable• Effects of nonnative trout less predictable
Research on the Ground!
• Nice pubs aren’t enough
• Scientists need to be directly involved
“Judging by one criterion, it is Extinct!”
“Judging by one criterion, it is Extinct!”
“But judging by another, it is alive and healthy in places!”
Management questions – space, time, location•Where are the biggest risks?•What are the threats?•What do we do about them?•Where and when to do it?•How do we use the best available science?
Lahontan cutthroat trout
Problem:
Many local populations and habitats, limited resources
Management alternatives:
Opportunistic approach:
Driven by available $$, stakeholder support
Strategic approach:
Driven by a conservation assessment toprioritize efforts
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Conservation Assessments – Integratedanalysis of conservation units
AKA – putting the pieces together
The pieces:
1. Units – Conservation units can be delineatedusing genetic, demographic or ecologicalinformation.
2. Risks – The risk of extinction in a unit must be assessed (e.g., as indicated by probability of occurrence, PVA, etc.).
3. Threats – What specific factors contribute most to risks within each unit?
The pieces:
1. Units – Defined by landscape models: Patches
2. Risks – Defined by model of occurrence, with corroboration from local PVA and genetic analyses
3. Threats – Defined by studies of LCT distributions and influences of nonnatives
Conservation Assessment
Is the habitat isolated?
Are nonnatives sympatric?
Is the fish distribution limited
by habitat?
Is the habitat large?
Is the distribution limited by
nonnatives?
Is the habitat isolated?
Are nonnatives present?
Are nonnatives hybridizing?
Is the habitat large?
ReintroductionsNonnativesHabitat loss
Unoccupied Unoccupied patchespatches
Patches occupied by Patches occupied by cutthroat troutcutthroat trout
Is the habitat isolated?
Are nonnatives sympatric?
Is the fish distribution limited
by habitat?
Is the habitat large?
Is the distribution limited by
nonnatives?
Is the habitat isolated?
Are nonnatives present?
Are nonnatives hybridizing?
Is the habitat large?
ReintroductionsNonnativesHabitat loss
Unoccupied Unoccupied patchespatches
Patches occupied by Patches occupied by cutthroat troutcutthroat trout
Assessing management actions relative to potential threats Threat Classification: Example
Occupied patches Unoccupied
Reintroductionpotential
NonnativesHabitat
Classification/ranking of threats
- ID general management options, recovery activities
-Spatially explicit classification of recovery activities
-Importance of location
Why do we need a spatially explicit classification of recovery activities?
…Because – Improvements in recovery activities may not come from changing what we are doing, but where we are doing it.
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Prioritization: Importance of space
Biological perspective
LocalLocal
Subwatershed
Local-stream
Subbasin
Lahontan basin
Po
pu
lati
on
Rec
ove
ry u
nit
ES
U -
DP
S
Sp
ecie
s
Management perspective Strategic management:
Perspectives from a conservation assessment -
How do priorities compare to existing efforts?
Are we addressing the right threats in the right places?
Are we saving individuals or populations but losing the species?
Is management being driven by opportunities, priorities, or both?
Getting closer to the ground:Addressing threats within patches
Habitat loss
SourcesLivestock grazing
RoadsAgriculture
MiningEtc.
ResponsesTemperature
SedimentRiparianChannel
Etc.
What to manage? What to manage? What to measure? What to measure?
What is theproblem? What is theproblem?
Implementation
Assessment
?
Lessons Learned• Good conservation science:
– Identifies appropriate scales for applications– Addresses what we can do something about– Follows the KISS principle without sacrificing
rigor or reality– Produces operational results
• Reprints alone ? conservation biology– People on the ground need your expertise!
Where do barriers pose the biggest threats?
Effects of small dams on persistence of white-spotted charr(Morita and Yamamoto 2002)
Salvelinus leucomaenis
1.0
0.75
0.50
0.25
00.1 1.0 10.0
3 years
10
20
4050
30
1.0
0.75
0.50
0.25
00.1 1.0 10.0
3 years
10
20
4050
30
Prob
abili
ty o
f oc
curr
ence
Basin area (km2)
Persistence: a matter of space and time
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Will connectivity restoration allow nonnative invasions?