Climate insurance for NW steelhead fisheries: thoughts on incorporating the influence of variable ocean conditions in

steelhead management

Nate Mantua

Climate Impacts Group

University of Washington

Sept 1997 El NiñoSept 1997 El NiñoSept 1998 La NiñaSept 1998 La Niña

Environmental variability is large

OPI (hatchery) coho marine survival

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 19901992 1994 1996 1998

Return Year

Survival

Why? Leading hypothesis: changes in ocean conditions impact the entire marine food-web

upwelling food webs in our coastal ocean: the California Current

Cool water, weak stratificationhigh nutrients, a productive “subarctic” food-chain with abundant forage fish and few warm water predators

Warm stratified ocean, fewnutrients, low productivity “subtropical” food web, a lack of forage fish and abundant predators

Upwelling impacts: August 2000

temperature Chlorophyll

For the NW coastal ocean, spring/summer upwelling is a key and highly variable process that structures the coastal ocean food web

ColumbiaColumbia RiverRivermouthmouth

1000 smolts 10’s to 100’s post-smolts early summer

A few to ~100 adults in 2nd summer

key factors? •Stratification •spring transition date•spring winds, upwelling and transport

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1st s

prin

g at

sea

1st w

inte

r at

sea

key factors? •Stratification •winter winds, downwelling and transport

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coastal ocean impacts on coho marine survival (Logerwell et al. 2003, Fish. Oceanogr.)

4 index Ocean Conditions Model “hindcasts” for OPI coho marine survival, 1969-1998

Logerwell et al. 2003, Fish. Oc.

R2= .75

Observed coherence scales in stock specific salmon productivity

• Stock by stock R/S residuals have 50% decorrelation scales ~500 to 1000km

• Similar scales of coherence come from stock by stock marine survival estimates based on CWTs

(figure taken from Mueter et al., 2002, Fish. Oceanogr.)

n=37

n=40

n=43

Scales of coherence in the coastal ocean

• Coastal SST and upwelling wind decorrelation scales are largest in winter, smallest in summer

• Decorrelation scales for salmon productivity are similar to those for summertime SST and upwelling winds(Mueter et al., 2002, Fish.

Oceanogr.)

J F M A M J J A S O N D

2500 km

1000 km

500 km

0

10

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18931901190919171925193319411949195719651973198119891997Year

Sockeye catch (millions)

Togiak

Ugashik

Egegik

Naknek-Kvichak

Nushagak

0%

20%

40%

60%

80%

100%

18931901190919171925193319411949195719651973198119891997Year

Composition

Commercial Sockeye Salmon Catches Since 1883Bristol Bay, Alaska

Com

posi

tion

Com

mer

cial

cat

ch

(mill

ions

)

Hilborn et al. 2003, PNAS

Kvichak

0

2

4

6

8

10Naknek/Branch Egegik

Ugashik

0

2

4

6

8

10

1955 1975 1995

Wood

1955 1975 1995

Igushik

1955 1975 1995

Recruits-per-spawner for Bristol Bay sockeye

(by major river system)

Year

Hilborn et al. 2003, PNAS

Life in uncertain environmentsRisk spreading characteristics, at the

metapopulation level, one evolutionary response:

• diversity of time-space habitat use provides a buffer for stocks, metapopulations, and species– a variety of sensitivities for different streams

(e.g. Hymer WDFW, Hilborn et al. )– different ocean sensitivities (e.g. Waples,

NMFS, Hilborn et al.) for different stocks

So what?(what I’ve learned)

– Sustaining “fish” and sustaining a “fishery” are not the same things

• expectations and actions for these two goals are often at odds with each other

• right now, fishery managers generally failing to deal with “climate” – true for year-to-year and decade-to-decade

variations

What are we managing, and why? (McEvoy 1996)

• What is a fishery?– (1) an ecosystem; (2) a group of people

working, and (3) a system of social control

Sustainability?Saving the fish

• eliminate harvests• Restore diversity,

abundance, and distribution

• restore and protect habitat– remove barriers to fish

passage (breach dams)

• accept variability– acknowledge a lack of

predictability

Saving the fishery• Maximize harvests

– focus on productivity, biomass/numbers

• tweak the status quo– fish passage, hatcheries

• eliminate variability– use hatcheries, divorce

fish production from habitat

– emphasize prediction

EC

OL

OG

YP

OL

ITIC

S-E

CO

NO

MIC

S-E

CO

LO

GY

Where predictability matters(Holling 1993 Ecological Applications)

1st stream science• system is predictable, science of parts

– ex: the population, maximum sustained yield• Experimental, seeks explanation and prediction• implies we need certainty before taking action

Command and Control Management• Problem is perceived, a solution for its control is

developed (e.g. low salmon production, build a hatchery) • Reduce variability to make the system more predictable

Where Predictability doesn’t matter

2nd stream science• Unpredictable, science of integration

– ex: the ecosystem

• Comparative, seeks understanding, accepts inherent unknowability and unpredictability

The Golden Rule• “Resource management should strive to retain

critical types and ranges of variations in ecosystems” (Holling and Meffe 1996)

The problem?

• We can’t solve 2nd stream problems with 1st stream approaches

Summary and Conclusions• A large and growing body of evidence for climate

impacts on salmonids– climate information may aid in improving management

• short term help through monitoring+biophys models• At time frames > 1 year into the future,

predictability is severely limited

• environmental prediction issues now a source of conflict between managing fish and fisheries– scientists must own up to the fact that we cannot

predict the future

What to do?

• Acknowledge and embrace uncertaintyAcknowledge and embrace uncertainty– wild salmonids have evolved characteristics that

cope with environmental uncertainty

• choose choose MonitoringMonitoring over over PredictionPrediction

• restore restore natural climate insurancenatural climate insurance for for salmonsalmon – Diversity, abundance, and distributionDiversity, abundance, and distribution – restoring lost diversity of life history behaviors;

this diversity is directly linked to availability of healthy, complex freshwater habitat

• Save the FisherySave the Fishery

Saving the Fishery

• Save the FishSave the Fish

• Rethink/revise goals of fishery Rethink/revise goals of fishery managementmanagement– Industrial fishery model (MSY) fails to account

for environmental uncertainty and highly limited predictability of populations and their food webs, and it fails to value the role of variability in the ecology of populations

Managing for sustainability

nature

Legal systemFisheconomy/interests

Note that this talk borrows heavily from:

Mantua, NJ, and RC Francis (in press): Natural climate insurance for Pacific northwest salmon and salmon fisheries: finding our way through the entangled bank. To appear in E.E. Knudsen and D. MacDonald (editors). Fish in our Future? Perspectives on Fisheries Sustainability. A special publication of the American Fisheries Society.

A climate scientist in the field

Coastal Oregon regional indices and large-scale Oct-Mar Aleutian Low variability

DJF

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T0

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rin

g T

ran

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wp

DJF

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T1

AL Index AL Index AL Index AL Index

“Ocean Conditions Model” predictions

Washington-Oregon-Californiacoho landings

Cat

ch in

mil

lion

s of

coh

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OP

I survival rate (%)

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Predictions: Predictions: RY 2000 4-6% RY 2000 4-6% RY 2001 3-5%RY 2001 3-5%RY 2002 RY 2002 44--88%%RY 2003 RY 2003

WDFW coho marine survival recordscourtesy Dave Seiler WDFW

5 wild stocks

7 hatchery stocks