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Steelhead and Steelhead and SnowSnow
Linkages to Climate Linkages to Climate Change ?Change ?
Recruitment CurvesRecruitment Curves Fact or Fiction?Fact or Fiction?
0
1000
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0 2000 4000 6000
S a l m o n b e r r y
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4000
0 1000 2000 3000
U m a t i l l a
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0 1000 2000 3000 4000 5000
U p p e r J o h n D a y
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0 2000 4000 6000 8000
S o u t h S a n t i a m
Clues from ResidualsClues from Residuals
-3000
-2000
-1000
0
1000
2000
3000
4000
1974 1980 1986 1992 1998
Salmonberry S Santiam Upper John Day Umatilla
Possible CandidatesPossible Candidates
PDO PDO PNIPNI Stream flowStream flow Others Others
Mountain SnowfallMountain Snowfall
A guess based on my experiencesA guess based on my experiences Good skiing years = good fishing Good skiing years = good fishing
yearsyears
Data Sites for Snow Data Sites for Snow IndexIndex
Crater Lake
Mount Rainier
Which Measurement?Which Measurement?Seasonal Maximum Snow Seasonal Maximum Snow
DepthsDepths
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200
400
600
800
1000
1910 1930 1950 1970 1990 2010
M a
x i m
u m
S n
o w
D e
p t h
(c
m) ..........
Mt Rainier
Crater Lake
Snow Depth Index and Snow Depth Index and ResidualsResiduals
-3000
-2000
-1000
0
1000
2000
3000
4000
1974 1980 1986 1992 1998
Salmonberry S Santiam Upper John Day Umatilla
Snow Index
Evaluation of Evaluation of Crater Lk & Mt Rainier Snow Crater Lk & Mt Rainier Snow
Index (CRSI)Index (CRSI) Spawner-Recruit time series for 26 populations Spawner-Recruit time series for 26 populations
of Oregon steelheadof Oregon steelhead Evaluated 4 environmental indices as variablesEvaluated 4 environmental indices as variables
CRSICRSI CRFCRF nsPDO nsPDO nPNInPNI
Attempted fit of B-H function w/ and w/o Attempted fit of B-H function w/ and w/o environmental variableenvironmental variable
ComparisonComparison Was model statistically significant ?Was model statistically significant ? Which model had lowest AICc score ?Which model had lowest AICc score ?
Four Environmental IndicesFour Environmental Indices
The Last 80 YearsThe Last 80 Years
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
1910 1930 1950 1970 1990 2010
C R S I n s P D O n P N I C R F
Fitting Recruitment Curves Fitting Recruitment Curves OverviewOverview
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1974 1980 1986 1992 1998
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1974 1980 1986 1992 1998
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1974 1980 1986 1992 1998
Predictor Variable 1 Spawners
Predictor Variable 2 Environmental Index
Response Variable Recruits
Fitting Recruitment CurvesFitting Recruitment CurvesTiming / LagsTiming / Lags
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1974 1980 1986 1992 1998
0
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1974 1980 1986 1992 1998
Predictor Variable 1 Spawners
Predictor Variable 2 Environmental Index
Response Variable Recruits
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1974 1980 1986 1992 1998
Which Models Which Models Significant?Significant?
02468
101214161820222426
B H n s P D O n P N I C R F C R S I
Popu
lation
Cou
nt .....
AICc “Best Model” AICc “Best Model” FrequencyFrequency
CRSI
CRF
nsPDOnPNI
19 Populations
5 Populations
The Not So Cool PartThe Not So Cool PartDecreased Snow = Fewer Decreased Snow = Fewer
SteelheadSteelhead
0.00
0.25
0.50
0.75
1.00
0% 5% 10% 15% 20% 25% 30% 35%
S n o w I n d e x D e c l i n e
R e
l a
t i v
e A b
u n
d a
n c
e .....
Mountain Snow Levels are Mountain Snow Levels are in Declinein Decline
(from 1950 to present)(from 1950 to present)
Source: Mote et al. 2003
Air Temperature is the StoryAir Temperature is the Story(Willamette Valley 7-yr Running Avg)(Willamette Valley 7-yr Running Avg)
1895 1915 1935 1955 1975 1995
CRSI
AirTemp
Temperature Increase to Temperature Increase to ContinueContinue
Source: IPCC (2007)
Driven by Anthropogenic Driven by Anthropogenic FactorsFactors
Source: IPCC (2007)
Climate Change is Here Climate Change is Here
“The West’s snow resources are already declining as the climate warms ”
- Mote et al. (2003)
What Does this Mean for What Does this Mean for Steelhead ?Steelhead ?
Smaller Populations Smaller Populations Higher Risk of ExtinctionHigher Risk of Extinction How Much Higher ?How Much Higher ?
Attempt to Quantify Attempt to Quantify Extinction RiskExtinction Risk
Snow trends as proxy for climate Snow trends as proxy for climate change effect change effect
Forecast extinction risks with PVA Forecast extinction risks with PVA Tested three CRSI scenariosTested three CRSI scenarios
Slight decline (8% per 100 yrs)Slight decline (8% per 100 yrs) Moderate decline (15% per 100 yrs)Moderate decline (15% per 100 yrs) Large decline (34% per 100 yrs)Large decline (34% per 100 yrs)
S p a w n e r s
R e
c r u
i t s
....
PVA ModelPVA Model
Add Spawners
Recruits
Adjusted Recruits
CR
SI
0 10 20 30 40 50 60 70 80 90 100
S i m u l a t i o n Y e a r0 20 40 60 80 100
Y e a r
Slight Decline in CRSISlight Decline in CRSI
Prob Extinct < 0.05 Prob Extinct < 0.05 to 0.25to 0.25
Prob Extinct < Prob Extinct < 0.050.05
Prob Extinct < 0.25 Prob Extinct < 0.25 to 0.50to 0.50
Prob Extinct < 0.50 Prob Extinct < 0.50 to 0.80to 0.80
Prob Extinct > 0.80Prob Extinct > 0.80
Moderate Decline in Moderate Decline in CRSICRSI
Prob Extinct < 0.05 Prob Extinct < 0.05 to 0.25to 0.25
Prob Extinct < Prob Extinct < 0.050.05
Prob Extinct < 0.25 Prob Extinct < 0.25 to 0.50to 0.50
Prob Extinct < 0.50 Prob Extinct < 0.50 to 0.80to 0.80
Prob Extinct > 0.80Prob Extinct > 0.80
Large Decline in CRSILarge Decline in CRSI
Prob Extinct < 0.05 Prob Extinct < 0.05 to 0.25to 0.25
Prob Extinct < Prob Extinct < 0.050.05
Prob Extinct < 0.25 Prob Extinct < 0.25 to 0.50to 0.50
Prob Extinct < 0.50 Prob Extinct < 0.50 to 0.80to 0.80
Prob Extinct > 0.80Prob Extinct > 0.80
Grim PredictionsGrim Predictions
At least 50% of populations At least 50% of populations
vulnerable to extinctionvulnerable to extinction
Implication for Fish Implication for Fish ManagersManagers
Crafting a ResponseCrafting a Response Extreme Response
#1Extreme Response
#2
A More Measured A More Measured ResponseResponse
Accept that steelhead are in a Accept that steelhead are in a evolutionary race against a rapidly evolutionary race against a rapidly changing environmentchanging environment
Losing the race = extinctionLosing the race = extinction Management response should be:Management response should be:
1.1. Eliminate impediments to natural Eliminate impediments to natural process of genetic adaptationprocess of genetic adaptation
2.2. Support regional, national, and Support regional, national, and international actions to lessen and international actions to lessen and slow the impact of climate change slow the impact of climate change
Natural Evolutionary Natural Evolutionary ProcessesProcesses
Part 1 – Get all Pieces in Full PlayPart 1 – Get all Pieces in Full Play Enable full expression of species Enable full expression of species
diversitydiversity Functional populations across species rangeFunctional populations across species range Function distribution across diverse habitats Function distribution across diverse habitats
within a population’s rangewithin a population’s range Resident life history strategyResident life history strategy Repeat spawner life history strategyRepeat spawner life history strategy Older age smoltsOlder age smolts
Maximize abundance of wild spawners Maximize abundance of wild spawners to help retain genetic diversityto help retain genetic diversity
Natural Evolutionary Natural Evolutionary ProcessesProcesses
Part 2 – Don’t put Adaptive Gains at Part 2 – Don’t put Adaptive Gains at RiskRisk
Limit use of hatchery fishLimit use of hatchery fish Genetic (regardless of broodstock origin) Genetic (regardless of broodstock origin) EcologicalEcological
Expect phenotypic changes that depart Expect phenotypic changes that depart from the historical condition, for from the historical condition, for exampleexample More resident fishMore resident fish Smaller fishSmaller fish Different out-migration timing Different out-migration timing Different return timingDifferent return timing
Do not try to counteract these changesDo not try to counteract these changes
Natural Evolutionary Natural Evolutionary ProcessesProcesses
Part 3 – Change Definition of Part 3 – Change Definition of SuccessSuccess Steelhead management paradigm shiftSteelhead management paradigm shift
Old – Abundance, productivity, and fishery Old – Abundance, productivity, and fishery utilization goalsutilization goals
New - Facilitation of rapid evolutionary changeNew - Facilitation of rapid evolutionary change
Evidence of population response will be Evidence of population response will be much slower and more difficult to detectmuch slower and more difficult to detect
Determination if management strategy is Determination if management strategy is a success will not occur in our lifetimes.a success will not occur in our lifetimes.
Summary Summary
Mountain snowpack is linked to Mountain snowpack is linked to climatic factors that effect steelhead climatic factors that effect steelhead survival and recruitmentsurvival and recruitment
Climate change will greatly increase Climate change will greatly increase the vulnerability of steelhead the vulnerability of steelhead populations to extinctionpopulations to extinction
Facilitating the evolutionary process Facilitating the evolutionary process of population adaptation to climate of population adaptation to climate change should be the primary focus of change should be the primary focus of steelhead management in the futuresteelhead management in the future
Questions ?Questions ?
36 populations of 36 populations of steelhead, coho, and spring steelhead, coho, and spring
chinookchinooky = -2.9935x + 2.9167
R2 = 0.5639
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.00 0.20 0.40 0.60 0.80 1.00
Hatchery Fish Proportion
Ln(a
)
..
PreviewPreview Demonstrate an association between Demonstrate an association between
variations in mountain snowpack and variations in mountain snowpack and steelhead recruitment performancesteelhead recruitment performance
Quantify an increase in extinction risk due to Quantify an increase in extinction risk due to climate change based on linkages with climate change based on linkages with snowpacksnowpack
Suggest that facilitating the evolutionary Suggest that facilitating the evolutionary process of population adaptation to climate process of population adaptation to climate change should be the primary focus of change should be the primary focus of steelhead management in the futuresteelhead management in the future
Summary of Evaluation Summary of Evaluation ApproachApproach
General ModelGeneral ModelRecruits = (Beverton-Holt Equation) Recruits = (Beverton-Holt Equation) * exp(c * * exp(c * Indx)Indx)
Examined 29 variations of model per Examined 29 variations of model per populationpopulation
EvaluationEvaluation Was model statistically significant ?Was model statistically significant ? Which model had lowest AICc score ?Which model had lowest AICc score ?
Pretty Cool!Pretty Cool!
CRSI Reflects this CRSI Reflects this DeclineDecline
350
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550
1875 1895 1915 1935 1955 1975 1995
M a
x i
m u
m S
n o
w D
e p
t h
...
.
Air Temperature the Last Air Temperature the Last 1300 Years1300 Years
From 2007 IPCC Technical Summary Report
Major Extinction EventsMajor Extinction Events