Columbia River Plume and California Current Ecosystem: Role in Salmon Productivity

Transcription

1 Columbia River Plume and California Current Ecosystem: Role in Salmon Productivity NOAA Fisheries Northwest Fisheries Science Center Estuary and Ocean Ecology Program Ed Casillas Program Manager

2 Why study the ocean? Ocean productivity sets salmon recruitment levels - return rates can vary >1x with similar freshwater conditions/survival The coastal pelagic ecosystem is dynamic and the variability seems to be increasing need to put FW actions in this context Objective Understand processes and develop tools (models and ocean indices) for forecasting salmonid survival and returns

3 Egg-smolt Potential- Snake River 16 Spring Chinook SF Salmon Marsh Catherine Proportion per Bar Egg to Smolt Survival Rate Recent good ocean 1 yr ave ocean Poor ocean

4 CHART OF SEA SURFACE TEMPERATURE Note: warm water between the equator and ~ 3 N Because of upwelling off North America, S. America N. Africa and S. Africa, cool water is found at the coast. Without upwelling, the coasts would be ~ 5-1EC warmer during summer because offshore waters would move shoreward.

5 55 N W Plankton, Salmon and Pelagic Fish Sampling Sample in May, June and September (5 stations) since 1998 Sample Columbia River and Willapa Bay every 1 days from April through July (AT NIGHT) at ~ 1 stations; since 1998 Sample off Newport every two weeks, since 1996 Have historical data on hydrography and zooplankton from 197s and 1983; salmon abundance data from but only some of these data are part of this talk

6 State of the Northern California Current Ecosystem Influenced by large scale forces acting at the local scale to affect biological process important for salmon Alaska 65N 6 Alaskan Low Local Conditions Upwelling Spring Transition SST British Columbia U.S.A ENSO W Local Biological Conditions

7 My Task Ocean entry timing and plume research Ocean productivity, variability, and PDO

8 Overview Ocean Factors Growth bottom up process Predation Top down process Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

9 Where Are Juvenile Salmon in the Coastal Ocean? 44.5 N 44. N August 2 Chinook and Coho Abundance # of Individuals/catch-Chinook 1 to 5 5 to to 15 # of Individuals/catch-Coho 1 to 5 5 to to 15 Newport Salmon - Habitat Linkages: Salmon are not everywhere in the coastal ocean! 43.5 N Latitude 43. N 42.5 N Cape Blanco µg/l Salmon Associated with Hot Zones of Ocean Productivity 42. N Oregon California 126. W W 125. W W 124. W Longitude

10 Juvenile Chinook Stock Compositions off Oregon and Washington from analysis of microsatellite DNA variation May June September 95% Columbia R. 96% Columbia R. 7% Columbia R. Interior Columbia Basin springs Lower Columbia springs Coastal Mid & Upper Columbia River summer / falls Willamette springs Lower Columbia Falls Snake Falls

11 Grays Harbor to LaPush Genetic Stock Identification of Juvenile Chinook Salmon Columbia River Plume Study Area September Cruises Source Populations North of Columbia River Lower Columbia Fall Lower Columbia Spring Cape Falcon to Willapa Bay Upper Willamette Spring Spring Creek Group Fall Deschutes Fall Upper Columbia Summer/Fall Newport to Cape Meares Snake Fall Interior Columbia Basin Spring Charts show stock compositions in three regions of the study area N North Oregon Coast Mid Oregon Coast South Oregon Coast Klamath / California Coast Central Valley 1 2 km

12 Overview Ocean Factors Growth bottom up process Predation Top down process Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

13 IGF in ocean caught juvenile salmon is related to adult returns SAR (smolt yr) 4.5 r 2 = coho igf (ocean entry year) IGF is a critical growth related hormone reflecting recent (2 wk) ocean conditions

14 IGF in ocean caught juvenile salmon related to available food supply Chinook IGF relates to food and abundance similarly to relations found with coho June Chinook IGF vs prey field/june Chin (5T) CPUE 58 June Chinook IGF R^2 = Variation influenced by temperature preyfield/junechin5tran

15 Axis Half Meter Vertical Net Copepods & Coho Copepod Community Composition in June related to Coho Survival 25 Added since meeting (white dots to the left with 1998) All June HM Copedensshelflog1norare5, NMS Axis 1 Year Coho Smolt to Adult Survival (%) Coho 1998 Salmon Survival Versus Warm Cold 1999 Year Axis Ordination Score R 2 =.59 P = NMS Ordination Median Axis-1 Score (98-5) NMS Ordination Median Axis-1 Score (98-5)

16 Phase shifts are tracked by the Pacific Decadal Oscillation (PDO): negative values = cool phase; positive values = warm phase s 198s PDO Time Series Cool phase Cool phase Cool phase 26?? Warm phase Warm phase 22-25

17 PDO Index 2-2 Sea surface temperature (SST) data from weather buoy off Newport shows similar patterns & shows that SST off Newport is related to the PDO = downscaling Cooler water in late 1998 associated with PDO change. SST Anomaly Buoy YEAR Note: time lags between PDO and SST change, associated with advection of different water types to Oregon. Warmer water in late 22 associated with PDO change. Most months cooler since late 25

18 Copepod species richness anomaly and the PDO PDO Copepod Species Richness Anomaly YEAR Suggests different water types appear off Oregon with persistent changes in PDO. Now, changing again, Species richness reflects origins of the animals. Low = subarctic; ; high = subtropical Species richness declined in fall 1998 but began to increase in Nov 2 due to phase shift of PDO Richness in similar to the El Niño event As with SST, 3-53 months following PDO change, copepod species richness switches.

19 PDO v Northern and Southern copepod biomass anomalies PDO Strong positive anomalies of Northern species when PDO is negative; Value of PDO Northern Copepods Southern Copepods Strong positive anomalies of southern species when PDO positive and during El Niño events (83, 97/98); especially anomalous with regards to copepod species, looking very El Niño like! YEAR

20 Summary Survival relates to growth Growth relates to food Adult return IGF-I IGF-I Salmon food Salmon food Food relates to ocean conditions April upwelling

21 State of the Northern California Current Ecosystem Influenced by large scale forces acting at the local scale to affect biological process important for salmon Alaska 65N 6 Alaskan Low Local Conditions Upwelling Spring Transition SST British Columbia U.S.A ENSO W Local Biological Conditions

22 Overview Ocean Factors Growth bottom up process Predation Top down process (Fish, Bird and Disease) Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

23 Predatory Fishes Jack mackerel (Trachurus symmetricus) Pacific mackerel (Scombrus japonicus) Pacific hake (Merluccius productus) Spiny dogfish (Squalus acanthias)

24 Predator Densities off the Columbia River 3 Number/1 6 m Pacific hake Jack mackerel Chub mackerel Spiny dogfish Year

25 Important Forage Fishes Pacific herring (Clupea pallasi) Whitebait smelt (Allosmerus elongatus) Eulachon (Thalichthys pacificus) Chinook salmon (Oncorhynchus tshawytscha) Northern anchovy (Engraulis mordax) Pacific sardine (Sardinops sagax)

26 Forage Fish Densities off the Columbia River Northern anchovy Pacific herring Pacific sardine Whitebait smelt Density (#/1 6 m 3 ) Year

27 Predator/Prey Interactions Top Down Forces Frequency Pacific hake Chinook.-age Chinook salmon 1.-age age Number Coho salmon (1.) Fish prey length 5 Number Chinook salmon (1.) Number Chinook salmon (.) Number All forage fish Fork length (mm)

28 Model the Impact of Piscine Predation on Juvenile Salmon Half-saturation constant (Ks) Pacific hake Pacific hake population Fish eaten/day Forage fish and Juvenile salmon eaten Juvenile salmon Forage fish + juvenile salmon smolts entering Juvenile salmon population Salmon eaten by hake smolts migrating Forage fish Forage fish arrival Forage fish population Forage fish eaten by hake

29 Coho salmon Fall Chinook salmon OPI % survival Predicted Observed Log (number of jacks) Predicted Observed Year Year Spring Chinook salmon Summer Chinook salmon Log (number of jacks) Predicted Observed Year Log (number of jacks) Predicted Observed Year

30 3% 3% 4% 3% 1% 2% 3% 29% May-June coastal ocean dominated by shearwaters, murres 1% 4% MAY 23 sooty shearwater 47% Common murre Sooty shearwater Sabine's gull Unidentified phalarope Western gull Unidentified gull Immature gull Rhinoceros auklet Black-footed albatross 1% Red phalarope 2% Other 2% 2% 1% 3% common murre JUNE 23 3% Sooty shearwater Common murre Immature gull Pink-footed shearwater Western gull Northern fulmar Rhinoceros auklet Other 68%

31 Predation concentrated in Plume Region Predation directly in salmon migration path along continental shelf Common murre Tatoosh Island, WA La Push, WA Queets River, WA Grays Harbor, WA Willapa Bay, WA Columbia River, OR Observed murres per km Expected murres per km Tatoosh Island, WA La Push, WA Queets River, WA Grays Harbor, WA Willapa Bay, WA Columbia River, OR Cape Meares, OR Cape Meares, OR Cascade Head, OR Cascade Head, OR Newport, OR Newport, OR Count per km Photo credit Peter LaTourrette,

32 7 6 Temperature ( C) Salinity Sooty shearwater Common murre Birds aggregate OCEAN RIVER at strong fronts 2 1 Strong fronts Longitude west WA OCEAN Temperature ( C) Salinity Sooty shearwater Common murre RIVER OR Longitude west Surface salinity

33 Birds abundant, but vary with tide 3X as many birds on spring vs. neap 73 vs. 25 birds per km 2 Two-tailed t-test, t test, log (x+1) transform: p =.43 Log( mean daily count + 1) Bird abundance vs. tide type Mean Mean±SE Mean±1.96*SE Spring Other Neap n = 23 n = 43 n = 12

34 Disease as a Mortality Agent Ceratomyxa shasta Prevalence in Juvenile salmon 3 25 % Infected Columbia River Estuary 21 Columbia River Estuary 22 Columbia River Estuary 23 La Push- New port 21 La Push- New port 22 CR transect only 23 New port - Crescent City 2 New port - Crescent City 22 Estuary Ocean Juvenile salmon tested included a total of 662 yearling coho salmon, 495 yearling Chinook salmon, and 657 subyearling Chinook salmon

35 Prevalence and Intensity of Nanophyetus salmincola in juvenile coho salmon caught off Oregon and Washington Prevalence May June Sept % Infected 6 4 * * * Year

36 Prevalence of Nanophyetus salmincola in juvenile coho salmon during first summer in Pacific Ocean ( ) Prevalence (% infected) * * * May June Sept * N = CA-OR Columbia WA Coast PS Genetic assignment of origin

37 State of the Northern California Current Ecosystem Influenced by large scale forces acting at the local scale to affect biological process important for salmon Alaska 65N 6 Alaskan Low Local Conditions Upwelling Spring Transition SST British Columbia U.S.A ENSO W Local Biological Conditions

38 Overview Ocean Factors Growth bottom up process Predation Top down process (Fish, Bird and Disease) Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

39 Juvenile salmon catches off Oregon and Washington directly relate to number of returning adult salmon: Average Catch per Kilometer Towed June Coho yearling Chinook subyearling Chinook yearling September Adult Abundance (thousands) '3 '98 '1 Columbia River Basin Coho ' Average Columbia River Coho Catch (# per km towed) in September '99 R 2 =.74 p =.3 ' Adult Returns at Bonneville (thousands) Interior Columbia River Basin Spring Chinook '1 '2 '3 ' R 2 =.82 p = Average Columbia River Chinook Catch (# per km towed) in June '99

40 Ocean Index Forecasting Future Salmon Returns Juvenile migration year Forecast of adult returns Large-scale ocean and atmospheric indicators PDO MEI Local and regional physical indicators Sea surface temperature Coastal upwelling Physical spring transition Deep water temp. & salinity Local biological indicators Copepod biodiversity Northern copepod anomalies Biological spring transition Spring Chinook--June -- Coho--September -- to June 27 Coho 27 Chinook 28

41 Current Forecast Yearling Chinook Spring Chinook Jack Counts at Bonneville (3/1-6/15) '5 '98 '1 '4 ' Average Yearling Chinook Catch (# per kilometer towed) in June BPA surveys '6 '2 ' 27 preliminary prediction R 2 =.8 p =.1 '99

42 Overview Ocean Factors Growth bottom up process Predation Top down process (Fish, Bird and Disease) Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

43 The CR Plume where the river meets the ocean Plume Ocean

44 Plume: Variable and Dynamic 48 N 47 N June 16-24, m Salinity LaPush Washington N 47 N June 17-25, 2 1m Salinity LaPush Washington N 47 N June 24 - July 1, 21 1m Salinity LaPush Washington N Astoria Oregon 46 N Astoria Oregon 46 N Astoria Oregon Tillamook Tillamook Tillamook 45 N 45 N 45 N Newport Newport Newport 125 W 124 W 123 W 125 W 124 W 123 W 125 W 124 W 123 W

45 Plume Daily variability - May (peak of the salmon migration season) Plume Structure related to flow and atmospheric/oceanographic forces 1999 daily salinity anomalies

46 Plume Fronts as Habitat- Juvenile Salmon & Steelhead # Salmonid/km^ Yearling Chinook Yearling Coho Steelhead (x.1) * * * * * 4 2 Ocean Front Plume

47 Large plume extends offshore Plume Structure Affects SARs The number of adult Steelhead returning to the Columbia River is related to plume structure Small plume hugs coastline A larger plume that is further offshore 7 to 1 days after juvenile steelhead enter the ocean leads to higher numbers of returning adults (yearling Chinook salmon also benefit from a larger plume, but to a lesser degree)

48 Overview Ocean Factors Growth bottom up process Predation Top down process (Fish, Bird and Disease) Development of ocean condition indices Plume and salmon survival Ocean habitat, variable ecosystem, forecasting

49 Habitat Characterization Analysis Issues Use presence/absence and abundance to define habitat Expanse of ocean habitat might relate to salmon marine survival Problems: Excessive zeros Non-homogeneous variance Over-dispersed

50 Logistic regression Zero-catch probability = chlorophyll + depth + salinity + temperature Stepwise selection

51 Model physical and biological attributes of the habitat to characterize variation in salmon abundance and distribution - Forecasting Generalized linear mixed model with a negative binomial distribution Y = a * X + b * Z + e Response variable: Juvenile salmon abundance Predictor variables: copepod indices, chl,, depth, temperature, salinity Copepod indices developed from principal factor analysis

52 Model Prediction vs Reality

53 Yearling Chinook spatial pattern > 3 indicate good habitat Inter-annual variation: Spatial variation

54 Conclusions Growth and survival related to ocean conditions Ecosystem productivity varies at interdecadal, interannual,, seasonal, and daily rates Understanding the interactions of the processes leads to forecasting tools to gauge the contribution of ocean conditions to the number of returning salmon and to value fw actions