Fraser River sockeye salmon: data synthesis and cumulative impacts

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Life stagefor FraserRiversockeyesalmonRelevantreportsectionExplanatoryImportanceRelevancetoManagementActionsComments and recommended research and monitoringactivitieshealth, condition), as well as oceanographicconditions, would help distinguish mortality occurringduring the open ocean phase from mortality prior toleaving the continental shelf.16. Information on non-Fraser populations, useful innarrowing down the processes affecting Frasersockeye, managing those stocks, and detectingshifting sockeye distributions with climate change.Migrationback tospawn4.6 Low High Recommended activities include:17. continued evaluation of the accuracy of inseasonand post-season sockeye assessments,and improvements in those assessments;18. accurate estimates of sockeye in-river mortality(en-route mortality, in-river harvest, pre-spawnmortality);19. management strategies to maximize thepotential for persistence of sockeye underincreasing stress from climate change;20. climate change modelling to quantify the impact offuture climate warming on Fraser River sockeyesalmon productivity and abundance;21. improved estimates of the spawning escapement forFraser pink salmon;22. improved escapement goals for each stock and runtiminggroup; and23. research on gender differences in upstream survival,impacts of fisheries capture on en route and prespawnmortality, intergenerational effects.110
6.0 ReferencesAinsworth, L.M., Routledge, R., and Cao, J. 2011. Functional Data Analysis in EcosystemResearch: the Decline of Oweekeno Lake Sockeye Salmon and Wannock River Flow.Journal of Agricultural, Biological, and Ecological Statistics. Available online (DOI:10.1007/s13253-010-0049-z).Arnold, T.W. 2010. Uninformative Parameters and Model Selection Using Akaike’s InformationCriterion. Journal of Wildlife Management 74(6): 1175-1178.Bates, Douglas M. 2010. lme4: Mixed-effects modeling with R (Draft Book Chapters) Springer.http://lme4.r-forge.r-project.org/book/. Accessed on April 13, 2011.Berube, M. 2007. Cumulative effects assessments at Hydro-Québec: what have we learned?Impact Assessment and Project Appraisal. 25(2): 101-109.Burgner, R.L. 1991. The life history of sockeye salmon (Oncorhynchus nerka). Pages 3-117 inC. Groot and L. Margolis (eds), Pacific Salmon Life Histories. Univ. British ColumbiaPress.Cain, J. 2001. Planning Improvements in Natural Resources Management: Guidelines for UsingBayesian Networks to Support the Planning and Management of DevelopmentProgrammes in the Water Sector and Beyond. Centre for Ecology and Hydrology (CEH),Wallingford, UK, 124 pp.Burkhardt-Holm, P. and K. Scheurer. 2007. Application of the weight-of-evidence approach toassess the decline of brown trout (Salmo trutta) in Swiss Rivers. Aquatic Sciences. 69:51-70.Burnham, K.P. and D.R. Anderson. 1998. Model Selection and Inference: A PracticalInformation-Theoretic Approach. Spring-Verlag, New York.Christensen, V. and A.W. Trites. 2011. Predation on Fraser River sockeye salmon. CohenCommission Tech. Rep. 8. Vancouver, B.C. www.cohencommission.caCouncil on Environmental Quality, Executive Office of the President. 1997. ConsideringCumulative Effects Under the National Environmental Policy Act.Counterpoint Consulting Inc. 2011. Status of DFO management and science. Cohen CommissionTech. Rep. 11. In prep. Vancouver, B.C. www.cohencommission.caDevore, J.L. 1995. Probability and Statistics for Engineering and the Sciences. Fourth Edition.Duxbury Press, Brooks/Cole Publishing Company, Pacific Grove, CA, USA.Dixon, P. M., and J. H. K. Pechmann. 2005. A statistical test to show negligible trend. Ecology86:1751-1756.111
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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
Page 75 and 76: assumption that exposure occurs whe
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Page 79 and 80: Johannes et al. (2011) demonstrate
Page 81 and 82: “likely” contributor to the ove
Page 83 and 84: Table 4.4-2. Model specifications f
Page 85 and 86: Region Variable M1 M2 M3 M4 M5 M6 M
Page 87 and 88: 3. survival rates within key portio
Page 89 and 90: 2011). The thermal limit hypothesis
Page 91 and 92: Historically, the majority of retur
Page 93 and 94: salinity. There is much evidence th
Page 95 and 96: declines (discussed in section 4.2
Page 97 and 98: There is indisputable evidence of t
Page 99 and 100: Figure 4.6-2. Number of years that
Page 101 and 102: correlation was statistically signi
Page 103 and 104: 4.6.7 Key things we need to know be
Page 105 and 106: al (2010). The combined effect of a
Page 107 and 108: more likely to suffer en-route and
Page 109 and 110: Table 4.7-2. Variables included in
Page 111 and 112: However, an important limitation is
Page 113 and 114: Alternative PreyVariablesModelsM1 M
Page 115 and 116: will likely have a high correlation
Page 117 and 118: 5.0 Conclusion5.1 Important Contrib
Page 119 and 120: Stage 5: Migration back to SpawnWhi
Page 121 and 122: More specifically, the extended res
Page 123 and 124: The twelve highest priority recomme
Page 125: Life stagefor FraserRiversockeyesal
Page 129 and 130: Johannes, M.R.S., R. Hoogendoorn, R
Page 131: Schaller et al. 2007. Comparative S
Page 134 and 135: utilized to clarify the full range
Page 137 and 138: 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
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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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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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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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