abundance and productivity trends of alaskan chinook ...gaining perspective on the magnitude of the...
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![Page 1: Abundance and productivity trends of Alaskan Chinook ...gaining perspective on the magnitude of the problem Matt Catalano Fisheries and Allied Aquacultures, Auburn University . Joe](https://reader033.vdocuments.mx/reader033/viewer/2022051811/601c428418f31476181188a2/html5/thumbnails/1.jpg)
Quantitative Fisheries Center at Michigan State University
Abundance and productivity trends of Alaskan Chinook salmon stocks:
gaining perspective on the magnitude of the problem
Matt Catalano Fisheries and Allied Aquacultures, Auburn University Joe Spaeder AYK-SSI Research Coordinator
![Page 2: Abundance and productivity trends of Alaskan Chinook ...gaining perspective on the magnitude of the problem Matt Catalano Fisheries and Allied Aquacultures, Auburn University . Joe](https://reader033.vdocuments.mx/reader033/viewer/2022051811/601c428418f31476181188a2/html5/thumbnails/2.jpg)
Quantitative Fisheries Center at Michigan State University
Analysis Background • Arctic-Yukon-Kuskokwim Sustainable Salmon
Initiative – Seven hypotheses about possible causes of declines of AYK
region Chinook populations
– Thirteen member AYK SSI sponsored Expert Panel
– Development of a “Chinook Research Action Plan” for the AYK region
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Quantitative Fisheries Center at Michigan State University
Outline
• Chinook stock status, trends, evidence of declines
• Comparative analysis of productivity trends among stocks
• Evidence for density-dependent effects on productivity
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Quantitative Fisheries Center at Michigan State University
Outline
• Chinook stock status, trends, evidence of declines
• Comparative analysis of productivity trends among stocks
• Evidence for density-dependent effects on productivity
![Page 5: Abundance and productivity trends of Alaskan Chinook ...gaining perspective on the magnitude of the problem Matt Catalano Fisheries and Allied Aquacultures, Auburn University . Joe](https://reader033.vdocuments.mx/reader033/viewer/2022051811/601c428418f31476181188a2/html5/thumbnails/5.jpg)
Quantitative Fisheries Center at Michigan State University
What is the pattern we seek to explain?
• Episodes of low abundance and productivity
• Failure to meet escapement goals
• Restrictions on subsistence harvest
• Infrequent directed commercial fisheries
• Changes in age/length/sex composition
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Quantitative Fisheries Center at Michigan State University
What data do we have? • 12 Chinook salmon stocks • Escapement
– Weirs, air surveys, counting towers, telemetry, mark-recapture
• Harvest – Commercial trip tickets – Subsistence post-season surveys
• Age/sex/length composition • Often cannot enumerate the entire escapement
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Quantitative Fisheries Center at Michigan State University
Alaska Chinook Data Sets Stock Region Years Kuskokwim AYK 1976-2011 Yukon AYK 1982-2010 Anchor Cook Inlet 1977-2011 Deshka Cook Inlet 1979-2010 Ayakulik Kodiak Island 1976-2010 Karluk Kodiak Island 1976-2010 Nelson Alaska Peninsula 1976-2011 Alsek Southeast Alaska 1976-2007 Blossom Southeast Alaska 1975-2007 Situk Southeast Alaska 1982-2010 Stikine Southeast Alaska 1981-2009 Taku Southeast Alaska 1973-2010
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Quantitative Fisheries Center at Michigan State University
The State-Space Model • Estimation of observation and process errors
• Age-structured: incorporates maturity variation
• Uncertainty due to missing data
• Recruitment is treated as unobserved
• Estimation of time-varying parameters
• Method of choice for ADFG
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Quantitative Fisheries Center at Michigan State University
Abundance
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Quantitative Fisheries Center at Michigan State University
Yukon River Harvest
1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009
Year
Thou
sand
s of
Sal
mon
050
100
150
200
250
CommercialSubsistence
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Quantitative Fisheries Center at Michigan State University
Kuskokwim River Harvest
1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009
Year
Thou
sand
s of
sal
mon
050
100
150
200
commercialsubsistence
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Quantitative Fisheries Center at Michigan State University
Maturity
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Quantitative Fisheries Center at Michigan State University
Source: Ken Harper USFWS
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Quantitative Fisheries Center at Michigan State University
Source: Ken Harper USFWS
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Quantitative Fisheries Center at Michigan State University
Yukon Length-At-Age (Hamazaki 2009)
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Quantitative Fisheries Center at Michigan State University
Growth: Scale Pattern Analysis Kuskokwim (Ruggerone 2007) Yukon (Ruggeronne et al. 2009)
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Quantitative Fisheries Center at Michigan State University
Summary: Stock Status and Trends • Nearly all stocks currently experiencing low returns
• The returns are the lowest on record for half of stocks
• Decrease in mean length-at-age (Kusko and Yukon)
• Decrease in eggs per female (Kusko and Yukon)
• Differential growth patterns (Kusko and Yukon)
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Quantitative Fisheries Center at Michigan State University
Outline
• Chinook stock status, trends, evidence of declines
• Comparative analysis of productivity trends among stocks
• Evidence for density-dependent effects on productivity
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Quantitative Fisheries Center at Michigan State University
Measures of “Productivity” 1. Recruits per spawner
– Does not account for density dependence effects
2. Recruits per spawner residuals – Removes density dependence effects on
productivity
3. Time varying alpha parameter from SR model – “filters” out white noise to “uncover” underlying
productivity trends
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Quantitative Fisheries Center at Michigan State University
1. Productivity: Recruits Per Spawner
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Quantitative Fisheries Center at Michigan State University
2. Productivity: Recruits Per Spawner Residuals
• How do we obtain the residuals? – Fit Ricker stock-recruitment models
• lnRy = ln(α)+ln(Sy)-β*Sy+ϕ*vy-1+εy
– Differences between observed and model-predicted recruitment
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Quantitative Fisheries Center at Michigan State University
Stock Recruit Models
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Quantitative Fisheries Center at Michigan State University
Recruits Per Spawner Residuals
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Quantitative Fisheries Center at Michigan State University
Correlations: ln(R/S) Residuals AYK Cook Inlet Kodiak Island Southeast
Kusko Yukon Anchor Deshka Ayakulik Karluk Nelson Alsek Blossom Situk Stikine Taku
Kusko
Yukon
Anchor
Deshka Pos Neg
Ayakulik 0.67 – 1.00 Karluk 0.33 – 0.67 Nelson 0.00 – 0.33 Alsek
Blossom
Situk
Stikine
Taku
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Quantitative Fisheries Center at Michigan State University
3. Productivity: Time-Varying Alpha
• Fit Bayesian state-space Ricker models • The productivity parameter, α, allowed to vary
over time via random walk process: lnRy = ln(αy) + ln(Sy) - β*Sy + εy
ln(αy) = ln(αy-1) + wy
• Similar results to Kalman Filter estimates
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Quantitative Fisheries Center at Michigan State University
Time-Varying Alpha
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Quantitative Fisheries Center at Michigan State University
Correlations: Time-Varying Alpha AYK Cook Inlet Kodiak Island Southeast
Kusko Yukon Anchor Deshka Ayakulik Karluk Nelson Alsek Blossom Situk Stikine Taku
Kusko
Yukon
Anchor
Deshka Pos Neg Ayakulik 0.67 – 1.00 Karluk 0.33 - 0.67 Nelson 0.00 – 0.33 Alsek
Blossom
Situk
Stikine
Taku
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Quantitative Fisheries Center at Michigan State University
Summary: Comparative Productivity Analysis
• Moderate positive residual correlation between Yukon and Kuskokwim
• Positive correlations among Yukon CA, Anchor and Kodiak stocks
• No obvious correlation patterns with/among southeast AK stocks
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Quantitative Fisheries Center at Michigan State University
Outline
• Chinook stock status, trends, evidence of declines
• Comparative analysis of productivity trends among stocks
• Evidence for density-dependent effects on productivity
![Page 30: Abundance and productivity trends of Alaskan Chinook ...gaining perspective on the magnitude of the problem Matt Catalano Fisheries and Allied Aquacultures, Auburn University . Joe](https://reader033.vdocuments.mx/reader033/viewer/2022051811/601c428418f31476181188a2/html5/thumbnails/30.jpg)
Quantitative Fisheries Center at Michigan State University
Questions
• How much of the temporal pattern in productivity is attributable to density dependence?
• How much evidence is there for over-compensatory density dependence?
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Quantitative Fisheries Center at Michigan State University
Density-Dependence: Methods
• Magnitude of alpha estimates
• Model comparison: Ricker vs. Beverton-Holt
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Quantitative Fisheries Center at Michigan State University
Probability(alpha>7.4)
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Quantitative Fisheries Center at Michigan State University
Probability(Ricker Model)
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Quantitative Fisheries Center at Michigan State University
Conclusions
• Alpha was large enough to induce stable population oscillations for Kusko and Yukon
• Weak evidence for over-compensatory recruitment dynamics, except for the Kusko
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Quantitative Fisheries Center at Michigan State University
Next Steps • Additional stocks
– Bayesian analysis of Chena/Salcha, Goodnews, Unalakleet R. stocks and possibly others
• Dec. 10-11 AYK SSI Chinook Salmon Outreach Workshop – New analyses – Management strategy evaluation workshop
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Quantitative Fisheries Center at Michigan State University
Acknowledgments
Brian Bue - Bue Consulting Bob Clark - ADFG Steve Fleischman - ADFG Hamachan Hamazaki - ADFG Mike Jones - MSU ADFG staff HPCC at MSU