Fraser River sockeye salmon: data synthesis and cumulative impacts

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Figure A3.5-1. This is an example of residual diagnostic plots used to assess the fit of a single straight line trend intime across the full data set for Stellako productivity (i.e., ln(R/S)). Notice the remaining pattern inresiduals when plotted against time (lower left panel); the later brood years are much more negative andthere appears to be a parabolic shape to the residuals suggesting a single trend line doesn’t adequately fitthe data.206
Figure A3.5-2. This is an example of residual diagnostic plots used to assess the fit of a piece-wise regression modelwith two straight lines for Stellako productivity (i.e., ln(R/S)). The most likely model suggests a changepoint in 1985 (brood year).Stock portfolio summariesSchindler et al. (2010) found that stock composition plays an important role in the overallvariability of a regional stock complex (in their case Bristol Bay sockeye). In particular theyfound that having a portfolio of many stocks results in less variability across the whole regionalstock complex, than if the portfolio was represented by only a few individual stocks. The FraserRiver Sockeye regional stock complex consists of 36 Conservation Units (CUs) (refer to theFreshwater Technical Report (# 3) for CU status assessments). We were interested in finding out,for the 19 stocks where we have data, how balanced the portfolio of Fraser River sockeye stocksis. Additionally, we were interested to see whether that balance has changed over time. We used207
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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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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 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
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
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
Page 248 and 249: Figure A4.2-5. Stock composition fo
Page 250 and 251: A4.3 Multiple Regression ResultsA4.
Page 252 and 253: Life stage Stressor category Variab
Page 254 and 255: The results show strong support for
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
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suggest any underlying mechanism, b
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Model: C1a1996-2004For 1996-2004, i
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Table A4.3-21. Estimates for all fi
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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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Fraser River sockeye salmon: data synthesis and cumulative impacts

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