Fraser River sockeye salmon: data synthesis and cumulative impacts

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2.3 Present Cumulative Effects AnalysisThe present cumulative effects analysis relies on data provided by each of the independentresearch projects investigating a different potential category of stressor. Some of the analysesexamine potential interactions among different types of stressors, but most of our quantitativework focuses on the relative impact of these different factors. Our analyses are be limited by: 1)the quality and extent of the data that are actually available; and 2) the degree of complexity inthe “true” underlying causes of the recent decline in productivity of Fraser River sockeye.We first address the issue of complexity. Figure 2.3-1 illustrates four different hypothetical pathsby which an individual sockeye salmon could be exposed to stressors over its lifetime, yet allleading to the same outcome - death as an adult. For the sake of simplicity, we have assumed it ispossible to integrate all stress factors into a single measure of cumulative stress where 0.0represents perfect health and 1.0 represents mortality. There are four scenarios described inFigure 2.3-1:o A1: the sockeye is severely affected by stressors as a fry (e.g., acquiring a disease thatalmost killed it and permanently affected its health), but does not suffer any further stressuntil, as an adult, a minor incremental impact results in death.o A2: the stressor that almost killed the sockeye as a fry killed off many other fry, reducingcompetition for food at the smolt stage, improving the health of surviving individuals;o B: the sockeye suffers moderate stress from many separate incidents over its lifetime,eventually dying at the same age as under the other scenarios even though none of thestressors experienced were even moderately severe.o C: the sockeye is only moderately affected by stressors over its lifetime until, as an adult,it is impacted severely by stressors that quickly result in death (e.g., low food, abundantpredators, high temperatures).In scenarios A and C, the rapid induction of severe stress could be either one severe stressor ormany stressors occurring simultaneously but within a similarly constrained window of time. Inscenario B, the slow induction of moderate stress could be either continued exposure to onestressor over the entire lifetime, or many different stressors occurring variably over time andspace.If scenario A or C accurately represent the “true” pathway, this relationship might be detected bytesting the fit to productivity indices of models that only include sets of factors limited to fry (A)and adult (C) life history stages. If scenario B represents the “true” pathway with one keystressor, this relationship might be detected by testing model sets limited to particular stressors or8
classes of stressors. However, if scenario B represents the “true” pathway with many stressorscombining and interacting over time and space, this relationship may be very difficult to detect.The quality and extent of available data severely limits the range of analyses that can beperformed, as we discuss later.The scope of the present cumulative effects analysis is limited to the scope of the CohenCommission technical research projects as a whole. Our cumulative effects analysis has beenconducted within the universe of the other technical projects and the data available from withinthose projects. This is not a cumulative effects study of Fraser River sockeye salmon within thebroader realm of all available scientific literature, research and reports.9
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: assumed that there is no potential
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 and 48: Peterman and Dorner (2011) have thr
Page 49 and 50: Figure 4.1-3. Estimates of long ter
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
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assumption that exposure occurs whe
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observations that are then averaged
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Johannes et al. (2011) demonstrate
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“likely” contributor to the ove
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Table 4.4-2. Model specifications f
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Region Variable M1 M2 M3 M4 M5 M6 M
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3. survival rates within key portio
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2011). The thermal limit hypothesis
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Historically, the majority of retur
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salinity. There is much evidence th
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declines (discussed in section 4.2
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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 204 and 205:
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
Page 212 and 213:
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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Page 268 and 269:
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
Page 305:
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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Fraser River sockeye salmon: data synthesis and cumulative impacts

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