Fraser River sockeye salmon: data synthesis and cumulative impacts

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The A-series of model sets based on life history were our primary focus and complement thequalitative and weight of evidence approach used throughout this project. The B-series of modelsets was completed to address the original scope of work for this project but was not consideredthe most appropriate approach. The C-series of model sets had fewer data limitations because ofthe reduced scope, in terms of potential variables to consider, and as a result probably providethe best opportunity for meaningful results. D-L series of model sets designed to focus within aparticular category of stressor. For example, a model set might be designed to ask the question,“within the category of contaminants, which measure has the greatest effect on productivity overthe whole sockeye life cycle?” Such model sets were not considered since they reflect a similarscale of stressor-centric investigation as had already been tasked to each of the other technicalreports. Within each series of model sets, we evaluated the available data for different timeperiods.We began with one of the simpler series of model sets (i.e., the C-series evaluating thedifference between QCS and SoG). This question was selected first as the hypotheses were morefocused (i.e., just marine conditions during coastal migration) and so required fewer covariates.Then we went to the most complex model sets (A-series and B-series) and started with thelongest time periods but found there were insufficient covariates available back to 1950 toperform meaningful analyses. The second longest time period (starting in 1969) had quite a fewcovariates available and so the A-series and B-series model sets over the 1969-2004 time periodwere the next set of models we evaluated. When moving to the period beginning in 1980, quite afew more covariates were available and we attempted to run the A-series and B-series model setsover the more recent time period. At this point we encountered data limitations as the number ofcovariates increased substantially but the number of dependent observations was reduced as aresult of the shortened time series. There should be sufficient data to work with this time periodgiven further investigation of the covariates and data reduction. Many of the smaller models inthis time period could run, but there were a few covariates that were still too strongly correlatedto run the larger models. The data reduction and candidate model selection (i.e., whichcovariates to include) would benefit from additional input from the authors of the other CohenCommission Technical Reports. Table A5.3-4 lists all model sets for which we present results inthis report.216
Table A3.5-4. Description of the 6 model sets that were examined as part of this project.Model Set name Description Time period (by Brood year)A4c Comparison across life stages 1969-2001A4bComparison across life stages, with pink 1969-2001salmon includedB4c Comparison across stressor categories 1969-2001B4bComparison across stressor categories with 1969-2001pink salmon includedC4aComparison of all available marine data 1969-2004between SoG and QCS. No data for QCSSST.C3aComparison of all available marine data 1980-2004between SoG and QCS. Including QCSSST.C1aComparison of all available marine dataincluding chlorophyll for SoG and QCSseparately.1996-2004Candidate modelsCandidate models refer to the list of alternative models compared within each model set. Each ofthe candidate models is fit using the same data set. Recall that models may differ in terms of thecombination of stressor covariates and the functional form of the model. Covariates could enterthe model in some non-linear way or interactions among covariates could be specified.However, all candidate models should be based on biological hypotheses. We did not feel wehad sufficient knowledge regarding the expected functional form of the relationship between thevast number of covariates and the response variable to assume anything beyond the simplestlinear relationship. Possible interactions were also considered based on the information providedby the Cohen Commission Technical Reports and our own qualitative synthesis. The onlyinteractions that were explicitly discussed in our report were:• Disease/Pathogens & temperature• Disease/Pathogens & pollutants• Disease/Pathogens & land use practices• Sea surface salinity & sea surface temperatureThe first three interactions were impossible to explore given the lack of disease/pathogen data.Interactions among marine factors during coastal migration could be explored with existing databut were not considered at this time. With more time and input from subject experts (e.g.,authors of the other Cohen Commission Technical Reports) the hypothesized links betweencovariates and productivity (Section A3.2-A3.4) could be refined and added to. Our approach217
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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
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Figure 4.1-6. Aggregate returns to
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o were generally worse during the l
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Freshwater predators on juvenile so
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copper, iron, mercury and silver).
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Several analyses by MacDonald et al
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abundances (Sproat, Klukshu, Chilka
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feel reasonably confident in this c
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Nelitz et al. (2011; Table 18) foun
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in the Lower Fraser than other Fras
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stressors. Thus our conclusions hav
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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
Page 182 and 183: A3.2.1 Integrative quantitative met
Page 184 and 185: Table A3.3-1. A summary of data set
Page 186 and 187: ProjectNumber Project Name Variable
Page 188 and 189: ProjectNumber Project Name Variable
Page 190 and 191: A3.4 Data PreparationContractor dat
Page 192 and 193: Table A3.4-2. An example entry in t
Page 194 and 195: Table A3.4-5. Brood year adjustment
Page 196 and 197: Table A3.4-7. Example output from t
Page 198 and 199: Table A3.4-9. The table of contents
Page 200 and 201: ProjectNumberProject Variable Subse
Page 212 and 213: The objective of our approach is to
Page 214 and 215: investigated ecosystems” (Burkhar
Page 216 and 217: Figure A3.5-1. Flow diagram used to
Page 218 and 219: multiple stresses simultaneously. T
Page 220 and 221: Change point analysis of productivi
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Page 226 and 227: exclude covariates with limited yea
Page 228 and 229: Figure A3.5-3. Average chlorophyll
Page 230 and 231: Status only data setsIn many cases
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Page 236 and 237: Table A3.5-5. Example of the model
Page 238 and 239: categories of stressors. We cannot
Page 240 and 241: o In some cases it may be the timin
Page 242 and 243: Appendix 4. Quantitative ResultsA4.
Page 244 and 245: alance” over time and so this it
Page 246 and 247: Figure A4.2-3. Stock composition fo
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Page 250 and 251: A4.3 Multiple Regression ResultsA4.
Page 252 and 253: Life stage Stressor category Variab
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Page 256 and 257: ModelSet_A4c_VarName M1 M2 M3 M4 M5
Page 258 and 259: Table A4.3-7. Estimates for all fix
Page 260 and 261: A4.3.3Analyses by stressor category
Page 262 and 263: Table A4.3-10. Estimates for all fi
Page 264 and 265: Model: B4bBrood years: 1969-2001We
Page 268 and 269: A4.3.4Analysis by regionModel: C4a1
Page 272 and 273: suggest any underlying mechanism, b
Page 274 and 275: Model: C1a1996-2004For 1996-2004, i
Page 278 and 279: Table A4.3-23. SoG C1a candidate mo
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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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Fraser River sockeye salmon: data synthesis and cumulative impacts

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