steelhead and snow

Steelhead and Steelhead and SnowSnow

Linkages to Climate Linkages to Climate Change ?Change ?

Recruitment CurvesRecruitment Curves Fact or Fiction?Fact or Fiction?

0

1000

2000

3000

4000

0 2000 4000 6000

S a l m o n b e r r y

0

1000

2000

3000

4000

0 1000 2000 3000

U m a t i l l a

0

1000

2000

3000

4000

5000

0 1000 2000 3000 4000 5000

U p p e r J o h n D a y

0

2000

4000

6000

8000

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

0

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

0

1000

2000

3000

4000

5000

1974 1980 1986 1992 1998

0

1000

2000

3000

4000

5000

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

0

1000

2000

3000

4000

5000

1974 1980 1986 1992 1998

0

1000

2000

3000

4000

5000

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

400

450

500

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