Fraser River sockeye salmon: data synthesis and cumulative impacts

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sockeye stocks tended to coincide with periods of high productivity in western Alaskanstocks, and vice versa.The Cohen Commission is interested in factors affecting the Fraser sockeye fishery, not onlyFraser sockeye productivity. Over the last two decades there has been an increasing amount ofen-route mortality of returning Fraser sockeye spawners (i.e., mortality between the Missionenumeration site and the spawning ground), as illustrated for late run sockeye in Figure 4.1-5.This results in reduced harvest, as fishery managers do their best to ensure enough spawnersreturn to the spawning ground in spite of considerable mortality along the way. Since en-routemortality is already included in estimates of recruits, it does not affect estimates of productivity,but it does affect the fishery.Other patterns noted by McKinnell et al. (2011) have particular relevance to the low 2009 returns(2007 ocean entry for most sockeye), and provide some interesting contrasts among stocks withdifferent life history patterns and migratory pathways:o most Fraser River sockeye stocks had very poor returns/spawner in 2009, but;o Columbia River sockeye had double their average returns in 2009 (recruits/spawner notavailable),o hatchery-reared sockeye from Cultus Lake showed typical survival rates through theStrait of Georgia in 2007 (estimated from tracking acoustic tags), ando there were record high returns of Harrison River sockeye in 2010, from underyearlingsthat reared in the Strait of Georgia in 2007.32
Figure 4.1-3. Estimates of long term trends in total life cycle productivity for the four Fraser sockeye run timinggroups, by brood year. The graph is based on productivity estimates for each stock, using a smoothedKalman filter, using the stock-recruitment model that best fit the data (methods explained in Peterman andDorner 2011). Brood year is year of spawning. The productivity estimates are in the same units for allstocks, plotted relative to each stock’s mean and standard deviation. Four stocks show no trend in thissmoothed Kalman filter indicator (i.e., Raft, Scotch, Portage, Weaver). This may be due to the absence ofany long term trend, a masking of the underlying trend by high year to year variability, and/or gaps in thetime series. Annual residuals in productivity for these four stocks have however been well below their longterm means in several brood years since 2000. Source: Peterman and Dorner (2011)33
Page 1: April 2011technical report 6Fraser
Page 7 and 8: Stage 2: Smolt OutmigrationWe analy
Page 9 and 10: of multiple stressors and factors,
Page 11 and 12: 4.3.5 Other evidence ..............
Page 13 and 14: List of TablesTable 4.2-1. Evaluati
Page 16 and 17: List of FiguresFigure 2.3-1. Cumula
Page 18 and 19: these integrative frameworks, conve
Page 21 and 22: 2.0 Cumulative Impacts or Effects2.
Page 23 and 24: assumed that there is no potential
Page 25 and 26: classes of stressors. However, if s
Page 27: affected by many stressors over its
Page 30 and 31: examples illustrate this problem --
Page 32 and 33: possibly even negligible component
Page 34 and 35: Figure 3.3-1. The conceptual model
Page 36 and 37: 3.3.3 Life history perspective/appr
Page 38 and 39: additional analyses to gain further
Page 40 and 41: Figure 3.3-3. Flow diagram used to
Page 42 and 43: This project is unusual in its scop
Page 45 and 46: 4.0 Results, Synthesis and Discussi
Page 47: Peterman and Dorner (2011) have thr
Page 51 and 52: Figure 4.1-5. A) Total run size of
Page 53 and 54: Figure 4.1-6. Aggregate returns to
Page 55 and 56: o were generally worse during the l
Page 57 and 58: Freshwater predators on juvenile so
Page 59 and 60: copper, iron, mercury and silver).
Page 61 and 62: Several analyses by MacDonald et al
Page 63 and 64: abundances (Sproat, Klukshu, Chilka
Page 65 and 66: feel reasonably confident in this c
Page 67 and 68: Nelitz et al. (2011; Table 18) foun
Page 69 and 70: in the Lower Fraser than other Fras
Page 71 and 72: stressors. Thus our conclusions hav
Page 73 and 74: There are many marine predators tha
Page 75 and 76: assumption that exposure occurs whe
Page 77 and 78: observations that are then averaged
Page 79 and 80: Johannes et al. (2011) demonstrate
Page 81 and 82: “likely” contributor to the ove
Page 83 and 84: Table 4.4-2. Model specifications f
Page 85 and 86: Region Variable M1 M2 M3 M4 M5 M6 M
Page 87 and 88: 3. survival rates within key portio
Page 89 and 90: 2011). The thermal limit hypothesis
Page 91 and 92: Historically, the majority of retur
Page 93 and 94: salinity. There is much evidence th
Page 95 and 96: declines (discussed in section 4.2
Page 97 and 98: There is indisputable evidence of t
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Figure 4.6-2. Number of years that
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correlation was statistically signi
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4.6.7 Key things we need to know be
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al (2010). The combined effect of a
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more likely to suffer en-route and
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Table 4.7-2. Variables included in
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However, an important limitation is
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Alternative PreyVariablesModelsM1 M
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will likely have a high correlation
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5.0 Conclusion5.1 Important Contrib
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Stage 5: Migration back to SpawnWhi
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More specifically, the extended res
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The twelve highest priority recomme
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Life stagefor FraserRiversockeyesal
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6.0 ReferencesAinsworth, L.M., Rout
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Johannes, M.R.S., R. Hoogendoorn, R
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Schaller et al. 2007. Comparative S
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utilized to clarify the full range
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Appendix 2. Reviewer Evaluations an
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the conclusions of the Expert Panel
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Response: Figure numbers have been
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Response: This section has been com
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ased on time or other stocks) to
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them in terms of how changes in spa
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efer to some variable being include
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... (Table xx)". Structures of thes
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Report Title: Fraser River sockeye
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show stronger correlations. Hence,
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Fraser and non-Fraser sockeye popul
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a single database for other researc
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Response: We have removed the itali
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evidence unique to each life stage.
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Report Title: Data Synthesis and Cu
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Response: We have further emphasize
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5. I would also encourage the autho
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events occur, it should be possible
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I don’t have anything to add beyo
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constitutes an exposure to human ac
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3.3.1 has been revised to say “As
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most likely contributors to the rec
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A3.2.1 Integrative quantitative met
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Table A3.3-1. A summary of data set
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ProjectNumber Project Name Variable
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ProjectNumber Project Name Variable
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A3.4 Data PreparationContractor dat
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Table A3.4-2. An example entry in t
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Table A3.4-5. Brood year adjustment
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Table A3.4-7. Example output from t
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Table A3.4-9. The table of contents
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ProjectNumberProject Variable Subse
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Page 208 and 209:
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The objective of our approach is to
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investigated ecosystems” (Burkhar
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Figure A3.5-1. Flow diagram used to
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multiple stresses simultaneously. T
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Change point analysis of productivi
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Figure A3.5-1. This is an example o
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ecruits for this analysis as we wan
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exclude covariates with limited yea
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Figure A3.5-3. Average chlorophyll
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Status only data setsIn many cases
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The A-series of model sets based on
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with this report given the vast sco
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Table A3.5-5. Example of the model
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categories of stressors. We cannot
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o In some cases it may be the timin
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Appendix 4. Quantitative ResultsA4.
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alance” over time and so this it
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Figure A4.2-3. Stock composition fo
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Figure A4.2-5. Stock composition fo
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A4.3 Multiple Regression ResultsA4.
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Life stage Stressor category Variab
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The results show strong support for
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ModelSet_A4c_VarName M1 M2 M3 M4 M5
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Table A4.3-7. Estimates for all fix
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A4.3.3Analyses by stressor category
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Table A4.3-10. Estimates for all fi
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Model: B4bBrood years: 1969-2001We
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A4.3.4Analysis by regionModel: C4a1
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suggest any underlying mechanism, b
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Model: C1a1996-2004For 1996-2004, i
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Table A4.3-23. SoG C1a candidate mo
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Appendix 5. Data Template User Guid
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Metric Connected to Biologically-su
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Initial Conceptual Model (Worksheet
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Commentsopen again. It is acceptabl
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Appendix 6. Workshop Report 1 (Nov.
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Table of ContentsTable of Contents
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PresentationsProductivity Dynamics
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and scope for improvement, particul
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Workshop participants pointed out t
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o Can you find the same shared tren
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generally better for Alaska sockeye
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Relative Likelihood of Alternative
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There was widespread agreement with
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Appendix A: List of Projects and In
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Peer Reviewers: Provide constructiv
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MacDonald Environmental Sciences Lt
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Appendix C: Workshop MinutesContent
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Levy urged researchers to bear in m
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within-population, within-brood-yea
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To address potential skepticism ove
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instead of migrating directly out i
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considered a good surrogate of temp
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Bristol Bay review: There are subst
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Method: The approach included formu
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Staley: Our project needs to compar
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Levy: It will go ahead in January.
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preliminary assessment of potential
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MacDonald: We’re waiting for all
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including Shuswap and North Thompso
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and biological variables. The combi
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temperatures. Notably, it doesn’t
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Seasonal population distribution pa
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Information gaps: The most importan
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Fraser sockeye salmon habitat analy
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survey data, but they were looking
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was also shown that tagged fish ret
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English: There was extensive holdin
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periods showed that 4 to 6 stocks (
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Q/A: Researchers should also feel f
Page 360 and 361:
Peterman: We’re lacking the big p
Page 362 and 363:
Appendix D: Table of likelihood/ hy
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