Fraser River sockeye salmon: data synthesis and cumulative impacts

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how effects at different life history stages can accumulate over the whole life cycle, increasingthe cumulative stress on an individual salmon to the point where it dies. The accumulation ofstress may be concentrated in one life history stage or distributed across multiple life historystages. The stress experienced within each life history stage may be insufficient to causemortality, but the cumulative effect of stressors in multiple life history stages can cause death.However, mortality events at an early life history stage can also result in a compensatoryreduction in competitive stress for those fish which survived, reducing their cumulative stressand increasing their chances of survival. These two sets of processes illustrated in Figure 3.3-1and 2.3-1 (i.e., cumulative impacts from many stressors within each life history stage, cumulativeeffects on each fish over its life) occur concurrently within each generation of sockeye.Table 4.7-1 summarizes the results of our analyses by life history stage. We found only twofactors (marine conditions and climate change) which were likely to have been a primary factorin the observed declines in Fraser sockeye productivity (recruits/spawner) over the last twodecades. While en route mortality has definitely had an impact on the sockeye fishery andnumbers of fish reaching the spawning ground, it is unlikely to have affected total productivity,since en route mortality is already included in the calculation of total recruits (i.e., recruits =spawners + en-route mortality + harvest). The effects of predators during the marine phase of thesalmon life cycle (stages 3 and 4 in Table 4.7-1) were judged to be possible primary contributorsto these declines. Due to lack of data it is not possible to draw conclusions about thecontributions of pathogens, which is a particularly important data gap that we discuss further inour recommendations (Section 5). Aquaculture was not considered in our report as theCommission Technical Reports on this potential stressor were not available, but will beconsidered in an addendum to this report. All other factors (i.e., forestry, mining, large hydro,small hydro, urbanization, agriculture, water use, contaminants, density dependent mortality,human activity and land uses in the Lower Fraser and Strait of Georgia) were judged to beunlikely as primary causes of long term productivity declines, though they may still have beencontributory factors. That is, stressors which we consider unlikely to be primary causes ofproductivity declines, may combine with other factors to create sufficient cumulative stress tokill salmon (i.e., through additive or greater than additive (synergistic) interactions) in somestocks in some years.The coastal migration phase of the sockeye’s life history provides a good example of multiplestressors interacting to cause cumulative impacts. There is indirect evidence that while oceantemperatures were not high enough to directly kill sockeye smolts in the summer of 2007, thesewarmer temperatures may have decreased the quantity and quality of available food andincreased other stressors (e.g., metabolic demands during inshore migration, vulnerability topredators, the level of pathogens and harmful algae); see McKinnell et al (2011) and Peterman et88
al (2010). The combined effect of all these factors may have caused significant smolt mortality in2007, while each of them independently would have been insufficient to kill smolts. Inlaboratory situations there is sufficient experimental control to explore the cumulative effects ofmultiple factors across the full range of possible stressor combinations. However in the oceanenvironment, multiple stressors will tend to covary together (like those described above which allincrease with warmer temperatures), so it is much more difficult to discern their relative impactson survival.89
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April 2011technical report 6Fraser
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Stage 2: Smolt OutmigrationWe analy
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of multiple stressors and factors,
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4.3.5 Other evidence ..............
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List of TablesTable 4.2-1. Evaluati
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List of FiguresFigure 2.3-1. Cumula
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these integrative frameworks, conve
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2.0 Cumulative Impacts or Effects2.
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assumed that there is no potential
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classes of stressors. However, if s
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affected by many stressors over its
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examples illustrate this problem --
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possibly even negligible component
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Figure 3.3-1. The conceptual model
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3.3.3 Life history perspective/appr
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additional analyses to gain further
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Figure 3.3-3. Flow diagram used to
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This project is unusual in its scop
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4.0 Results, Synthesis and Discussi
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Peterman and Dorner (2011) have thr
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Figure 4.1-3. Estimates of long ter
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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
Page 99 and 100: Figure 4.6-2. Number of years that
Page 101 and 102: correlation was statistically signi
Page 103: 4.6.7 Key things we need to know be
Page 107 and 108: more likely to suffer en-route and
Page 109 and 110: Table 4.7-2. Variables included in
Page 111 and 112: However, an important limitation is
Page 113 and 114: Alternative PreyVariablesModelsM1 M
Page 115 and 116: will likely have a high correlation
Page 117 and 118: 5.0 Conclusion5.1 Important Contrib
Page 119 and 120: Stage 5: Migration back to SpawnWhi
Page 121 and 122: More specifically, the extended res
Page 123 and 124: The twelve highest priority recomme
Page 125 and 126: Life stagefor FraserRiversockeyesal
Page 127 and 128: 6.0 ReferencesAinsworth, L.M., Rout
Page 129 and 130: Johannes, M.R.S., R. Hoogendoorn, R
Page 131: Schaller et al. 2007. Comparative S
Page 134 and 135: utilized to clarify the full range
Page 137 and 138: Appendix 2. Reviewer Evaluations an
Page 139 and 140: the conclusions of the Expert Panel
Page 141 and 142: Response: Figure numbers have been
Page 143 and 144: Response: This section has been com
Page 145 and 146: ased on time or other stocks) to
Page 147 and 148: them in terms of how changes in spa
Page 149 and 150: efer to some variable being include
Page 151 and 152: ... (Table xx)". Structures of thes
Page 153 and 154: 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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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
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Peterman: We’re lacking the big p
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Appendix D: Table of likelihood/ hy
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