Fraser River sockeye salmon: data synthesis and cumulative impacts

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A3.4 Data PreparationContractor data was received in Excel files of various formats - very few of the data setsreceived used the data template that had been developed. These data were imported to anAccess database to accomplish the brood year adjustments. The non-template data setsarrived in many different, non-standardized forms, adding a layer of complexity to theirintegration into a single database. Figure A3.4-1 shows the database diagram for thatcumulative impacts database.Figure A3.4-1. The Cohen Commission cumulative effects database diagram.174
Each data product received from the contractors was assigned a unique identifier in theMetadata table. Each data product was assigned to a variable name and where appropriatea variable subset was specified (for example, if August mean sea surface temperature wasreceived, the metadata record would specify “sea surface temperature” as the variable and“August mean” as the variable subset). The metadata table also specifies the location andunits of the data product among other supplementary information. Table A3.4-2 shows anexample entry in the Metadata table.175
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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
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
Page 155 and 156: show stronger correlations. Hence,
Page 157 and 158: Fraser and non-Fraser sockeye popul
Page 159 and 160: a single database for other researc
Page 161 and 162: Response: We have removed the itali
Page 163 and 164: evidence unique to each life stage.
Page 165 and 166: Report Title: Data Synthesis and Cu
Page 167 and 168: Response: We have further emphasize
Page 169 and 170: 5. I would also encourage the autho
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Page 173 and 174: I don’t have anything to add beyo
Page 175 and 176: constitutes an exposure to human ac
Page 177 and 178: 3.3.1 has been revised to say “As
Page 179: 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 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
Page 222 and 223: Figure A3.5-1. This is an example o
Page 224 and 225: ecruits for this analysis as we wan
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
Page 232 and 233: The A-series of model sets based on
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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
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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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