Incorporating Variable Ocean Conditions into Steelhead Fisheries Management

1. 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

2. Environmental variability is large Sept 1997 El Niño Sept 1998 La Niña

3. OPI (hatchery) coho marine survival Why? Leading hypothesis: changes in ocean conditions impact the entire marine food-web

4. upwelling food webs in our coastal ocean: the California Current Cool water, weak stratification high nutrients, a productive “subarctic” food-chain with abundant forage fish and few warm water predators Warm stratified ocean, few nutrients, low productivity “subtropical” food web, a lack of forage fish and abundant predators

5. Upwelling impacts: August 2000 temperature Chlorophyll Columbia River mouth For the NW coastal ocean, spring/summer upwelling is a key and highly variable process that structures the coastal ocean food web

6. coastal ocean impacts on coho marine survival (Logerwell et al. 2003, Fish. Oceanogr.) • key factors? • Stratification • spring transition date • spring winds, upwelling and transport • key factors? • Stratification • winter winds, downwelling and transport ? ? 1st winter at sea 1st spring at sea A few to ~100 adults in 2nd summer 10’s to 100’s post-smolts early summer 1000 smolts

7. 4 index Ocean Conditions Model “hindcasts” for OPI coho marine survival, 1969-1998 Logerwell et al. 2003, Fish. Oc. R2= .75

8. n=37 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=43 n=40

9. Scales of coherence in the coastal ocean 2500 km • 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.) 1000 km 500 km J F M A M J J A S O N D

10. Commercial Sockeye Salmon Catches Since 1883 Bristol Bay, Alaska Commercial catch (millions) Composition Hilborn et al. 2003, PNAS

11. Recruits-per-spawner for Bristol Bay sockeye (by major river system) Year Hilborn et al. 2003, PNAS

12. Life in uncertain environments Risk 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

13. 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

14. What are we managing, and why?(McEvoy 1996) • What is a fishery? • (1) an ecosystem; (2) a group of peopleworking, and (3) a system of social control

15. 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 Sustainability? ECOLOGY POLITICS-ECONOMICS-ECOLOGY

16. 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 matters(Holling 1993 Ecological Applications)

17. 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)

18. The problem? • We can’t solve 2nd stream problems with 1st stream approaches

19. 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

20. What to do? • Acknowledge and embrace uncertainty • wild salmonids have evolved characteristics that cope with environmental uncertainty • choose Monitoring over Prediction • restore natural climate insurance for salmon • Diversity, abundance, and distribution • restoring lost diversity of life history behaviors; this diversity is directly linked to availability of healthy, complex freshwater habitat • Save the Fishery

21. Saving the Fishery • Save the Fish • Rethink/revise goals of fishery management • 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

22. Managing for sustainability Fish economy/interests Legal system nature

23. 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.

24. A climate scientist in the field

25. Coastal Oregon regional indices and large-scale Oct-Mar Aleutian Low variability AL Index AL Index AL Index AL Index Spring Uwp DJF SST0 DJF SST1 Spring Trans

26. “Ocean Conditions Model” predictions Predictions: RY 2000 4-6% RY 2001 3-5% RY 2002 4-8% RY 2003 Washington-Oregon-California coho landings 10 6 Catch in millions of coho 8 OPI survival rate (%) 6 4 4 2 2

27. WDFW coho marine survival recordscourtesy Dave Seiler WDFW 5 wild stocks 7 hatchery stocks