Fraser River sockeye salmon: data synthesis and cumulative impacts

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possibly even negligible component of the predators diet. This type of predator-prey relationshipmay be fundamentally important to the prey while being of virtually no importance to thepredator.The third challenge (really an extension of the second) is unknowables. We cannot know theexplanatory influence of a factor that has not been monitored in a given year or location. Whenthere are no data, one cannot make any inferences either in favour or opposed to a givenhypothesis.3.3 Current Framework3.3.1 OverviewOur approach to cumulative impacts analysis comprises three components:1. Understand the patterns of change in the productivity of Fraser River sockeye salmonstocks (and other sockeye stocks) over the past several decades. This is the patternthat we are seeking to explain. This component is the primary focus of Project 10(Peterman and Dorner, 2011), and is summarized in section 4.1 of this report.2. Identify factors that could feasibly have contributed to the observed patterns ofchanging productivity in Fraser sockeye salmon. These potential explanatory factorsdo not necessarily need to be mutually exclusive (i.e., there may be multiple causes ofthe observed patterns). The various factors are the focus of other Cohen CommissionTechnical Reports and are covered in much greater detail therein.3. Assess the relative likelihood of feasible explanatory factors and their potentialinteractions, the focus of sections 4.2 to 4.7 of this report. We have compiled theevidence presented within other Cohen Commission Technical Reports into a weightof evidence approach.3.3.2 Conceptual modelWe developed a conceptual model illustrating the factors potentially affecting each life stage(Figure 3.3-1), so as to:1. organize the factors identified within the Technical Reports as being potentialcontributors to the Fraser sockeye productivity declines, and indicate the life stagespossibly affected by each factor;.2. represent some of the key interactions among factors, both within and across TechnicalReports;16
3. provide the Cohen Commission with some insights into the underlying complexity of thisecological system 5 ; and4. provide an organizational framework for the analysis of cumulative impacts, identifyingall of the factors to be integrated into qualitative and quantitative analyses of each lifehistory stage, and across the overall life cycle.Figure 3.3-2 illustrates a simplified version of the conceptual model projected over thegeographic habitat range of Fraser River sockeye salmon. This representation of the sockeyesalmon life history does not show details of specific mechanisms or all interactions amongfactors, but instead is intended to represent the general movement patterns of Fraser Riversockeye salmon throughout their habitat range and indicate the broad spatial scales over whichdifferent factors may influence sockeye salmon health and survival.Further details on the value of conceptual models as a central component of analyticalframeworks and the development of this particular model are provided in Appendix 3.5 Though reasonably complex, our conceptual model is certainly not an exhaustive representation of all primary andintermediate factors that influence sockeye salmon productivity.17
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 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
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
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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
Page 202 and 203:
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
Page 303 and 304:
Relative Likelihood of Alternative
Page 305:
There was widespread agreement with
Page 308 and 309:
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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