1. Importance of Habitat in salmon declines and recovery Ray Hilborn School of Aquatic and Fishery Sciences UW

2. What is wrong with salmon? The 4-H’s Harvest –We take too many Habitat –We degrade their streams Hydroelectric –We block passage, turn rivers into lakes Hatcheries –We try to “mitigate” for habitat loss by artificial production

3. Structure of talk Trends in abundance –How bad is the problem Ocean conditions – the BIG driver Hydroelectric Harvest Hatcheries Habitat

4. Myth I We are running out of wild salmon The “truth”: there are nearly as many wild salmon in western North America now as any time since Europeans arrived But: this due primarily to Alaska, and in the Lower 48 many stocks are extinct and most are well below historical levels

5. Bristol Bay wild sockeye

8. Puget Sound Coho Wild Returns

9. 400 300 200 100 Run Size Year AB C DEF Chinook salmon past Bonneville Dam

10. Myth II The ocean is big, unlimited and salmon abundance is driven by freshwater and habitat The “truth”: most large scale variation in salmon abundance is driven by ocean changes But: this only means it is harder to detect anthropogenic impacts

11. Lake Nerka, SW Alaska 0 10 20 30 246810 Sediment  15 N (‰) Salmon density (1000s/km 2 ) Mixing model reference lakes sockeye Historical sockeye population dynamics Schindler and Leavitt (2001)

12. Lake Nerka, SW Alaska Historical sockeye population dynamics 175018501950180019002000 0 4 8 12 Year Salmon density (1000s/km 2 ) + fishery catch escapement Schindler and Leavitt (2001)

13. 0 4 8 12 Sockeye (1000s/km 2 ) 175018001850190019502000 Sockeye density Effects of sockeye population on phytoplankton production Algal pigments in lake sediments Schindler and Leavitt (2001)

14. Survival rate by Realm Arctic SE Alaska Coastal BC Georgia Strait Puget Sound Coastal Washington Columbia Basin Coastal Oregon California Coho Fall chinook Spring chinook Avg survival rate

15. Coho survival rate by Domain Release year Survival rate

16. Fall chinook survival rate by Domain Release year Survival rate

17. Spring chinook survival rate by Domain Release year Survival rate

18. Coho survival~SST regression

19. Coho survival~SST regression (incl. resid)

20. Gulf of Alaska – Small set of structuring variables operating at different speeds - Whammo!

21. Myth III The decline of NW salmon is due to dams The “truth”: systems without dams have had similar trends But: clearly dams are not good for salmon and are part of the problem

24. Chinook survival by river segment Fall chinookSpring chinookFall chinook Columbia Fraser Survival rate 100% 10% 1% 0.1% 0.01% 0.001% B W A S L T U 100% 10% 1% 0.1% 0.01% 0.001% B: Columbia below dams W: Willamette River A: Columbia above dams S: Snake River L: Lower Fraser T: Thompson River U: Upper Fraser

25. Chinook survival in Columbia Basin Fall chinook Spring chinook Survival rate

26. Chinook survival in Fraser Basin Fall chinook Survival rate

27. Myth IV Hatcheries are necessary to mitigate for lost of habitat and over-harvest The “truth”: hatcheries have strong negative impacts on wild salmon But: if we eliminate hatcheries we might have no salmon left in some places

28. Hatcheries The basic assumptions –Freshwater habitat is limiting –Egg to smolt survival in the wild is about 5% –Hatcheries can usually obtain 80% egg to smolt survival –Release smolts ready to go to sea – they don’t need any freshwater habitat

29. Why hatcheries were built To compensate for over-harvesting To compensate for habitat destruction To mitigate for dam impacts To buffer natural variation To provide extra fish for harvest To conserve threatened stocks

33. Did Hatcheries Work We have over 300 hatcheries in the Pacific Northwest “If hatcheries were the solution, we wouldn’t have a problem!” Much disagreement, what would have happened without hatcheries

35. Concerns about hatcheries Generate over-harvesting on wild fish in mixed stock fisheries Compete with wild fish in freshwater and ocean Introduce and exacerbate diseases Genetically degrade wild fish by domestication and hybridization Provide an excuse to allow habitat loss

36. Pink salmon hatcheries in Prince William Sound Largest hatchery program in North America 600 million fish stocked each year Competing hypotheses re marine fish stocking –stocking augments wild production –stocking replaces wild production We have BACI !!!!!!

37. Prince William Sound salmon production

38. Total return

39. Wild fish production

41. Myth V The collapse of salmon in the late 80s and 90s is due to habitat changes The “truth”: habitat has not changed that much But: habitat is definitely declining

42. Few (if any) attempts to integrate all factors in combined analysis We have detailed harvest models We have no hatchery impact models in use Changes in ocean conditions are being better understood but not used in evaluating recovery plans A number of habitat models, EDT the most used

43. Framework for impact of habitat Multi-stage life history model from Moussalli and Hilborn 1986 –each life history stage as a Beverton-Holt curve with a productivity (initial slope or survival) and a capacity Key question is how to relate habitat to productivity and capacity

44. Sharma coho carrying capacity

45. Key Model Components SHIRAZ Spatially explicit – reaches or estuarine areas Life stages as many as you want Stocks may be life histories, wild/hatchery etc Capacity and productivity – any life history Habitat characteristics by reach Stochastic factors (flows, ocean survival etc) Functional relationships between habitat characteristics and stochastic factors and productivity and capacity

46. Reach Characteristics Passage Square meters spawning gravel Distance Square meters rearing habitat Percent fines in gravel Watershed area by reach Percent impervious by reach Temperature, DO etc.

47. Functional relationships Spawning gravel and egg capacity % fines in gravel and egg to fry survival Up the the user to define what you want to use Will ultimately build a “library” of functional relationships much like EDT … –But the user will decide which ones to use from the library

48. General model framework Read in the data –reach-specific habitat –hatchery input –Functional relationships –Hatchery practice –Harvest and ocean conditions specification –habitat interventions Loop over time –Calculate the change in habitat –Calculate the change in population size End the loop

49. Habitat Changes Annual habitat change: habitat degradation Habitat change due to a 1-time event: habitat restoration

50. Hatchery Influence Affect wild fish through competition Interbreeding can cause domestication of wild fish, and reduced survival

51. Functional Relationships Mark I version Spawner capacity depends on gravel area Egg survival as a function of fines Fry survival as a function of percent impervious and rearing area

52. Spawners to Egg capacity depends on gravel area productivity depends on age specific fecundity and age distribution of spawners

53. Eggs to Fry capacity is unlimited productivity depends upon % fines

54. Fry to Smolt capacity determined by rearing area productivity determined by % impervious

55. Other outstanding issues Beyond current efforts Allow for parameter uncertainty Formalize reality checks Potentially imbed the above in formal Bayesian framework

56. Current status Muckelshoot tribe using to meet TRT requirements for a rebuilding plan – Green River chinook well developed, White and Lake Washington just beginning Joint work with NMFS and Mark Sheuerell to interface SHIRAZ with PRISM dynamic hydrology models

57. Essential Fish Habitat: SHIRAZ provides a format To calculate the sensitivity of population size to each habitat indicator in each area This allows a quantitative ranking of the importance of different habitat characteristics and sites This ranking can be used to define “essential”, much like NMFS defines “overfishing”

58. Summary I Current work in evaluating natural and anthropogenic impacts on salmon suffer from lack of unified modelling framework SHIRAZ can serve as an initial general model structure for cost benefit analysis, policy evaluation, and parameter estimation

59. Summary II The Ocean, and the four H’s are all important We need to identify where time, effort and money will be best spent in salmon restoration This will require a new generation of models, data collection and analysis