Fraser River sockeye salmon: data synthesis and cumulative impacts

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Overview of Required Input DataIntegrative Quantitative MetricsEach contractor (excepting #7 and 11) should provide preliminary data for a few integrativemetrics (or indices) of the stressors that he or she is examining. Key characteristics include:Few: Limit submission to 1-5 metrics per contractor. Additional metrics can be added ifjustified – i.e., metric represents an important but independent source of variation.Integrative: Each study will likely have a lot of data. The few integrative metricsprovided to ESSA should synthesize these data. Each contractor is a discipline expert thatwill know which variables are most important or how best to integrate data intointegrative metrics.Independent: Integrative metrics should be chosen to reflect independent sources ofvariation (i.e. not be highly correlated with each other).Annual: The metrics provided by each contractor need to be provided annually, for thoseyears where data exist. Each contractor will know the most relevant approach tosummarize intra-annual data into an annual metric (e.g., maximum weekly averagetemperature experienced during upstream migration of each stock of Fraser sockeye).Stock specific: Provide only one data point per stock per year. The same data point mayapply to multiple stocks; contractors can specify which ones. Do not submit many data series. For example, there may be data on 100s ofindividual contaminants or 100s of temperature buoys. Choose the mostcritical data series or decide how to integrate similar series into an index. If temperature data are hourly or daily, decide how best to integrate into anannual metric. An average over a particular season may make more sensethan an annual average. Some freshwater variables may contain more than one data point for asingle stock in a single year (i.e. multiple nursery lakes for one stock). Decidehow best to integrate these values into a single value for the stock.Ultimately, each metric will provide a SINGLE VALUE PER YEAR PER STOCK, thoughmany metrics may apply to all stocks equally.266
Metric Connected to Biologically-supported HypothesisEach reported metric should be clearly connected with a biologically-supported hypothesis thatemphasizes WHY this metric is potentially important in explaining patterns in sockeyeproductivity over time and/or space. Consider where these hypotheses fit within the initialconceptual model provided in the template. As stated in David Levy’s letter of Sept 8,hypotheses should be expressed in the form of questions. A temperature index may be developed that only integrates temperaturedata from one season because that is when sockeye would be most affectedby temperature or pass by that region. If a statistical method such as multiple regression or PCA is used todetermine that January temperatures are most significant but this is notbiologically supportable (e.g., sockeye are not in the area in January), thenthat would be a poor index.Metadata – Sources and MethodsThe original data sources and analytical methods need to be explicitly described to communicateHOW this integrative metric was generated. The leaders of each project are expected to be theexperts on how to best integrate stressor-specific data over space and time, but all users(intermediate and final) must be able trace the analysis pathway of a particular metric from itssources to its final form. Key metadata components are included in the template (specific detailsbelow).Qualitative EvaluationIt is anticipated that many important metrics will have a limited data record. To overcome thislimitation and to facilitate additional analyses over the entire time period of data on Fraser Riversockeye stock productivity, we would like to have Contractors supply a qualitative data whichprovides estimates/ educated guesses for the entire time period. This would complement thequantitative data set.Contractors will be required to fill in a second, complete data set with qualitative assessments (5point scale) of the same integrative metrics over time. This is based on the expert experience ofeach contractor in their respective field. This qualitative assessment will also be collected basedon each contractor’s expert knowledge of their particular stressor outside of the Fraser system aswell.267
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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
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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
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
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
Page 281: Appendix 5. Data Template User Guid
Page 285 and 286: Initial Conceptual Model (Worksheet
Page 287 and 288: Commentsopen again. It is acceptabl
Page 289 and 290: Appendix 6. Workshop Report 1 (Nov.
Page 291 and 292: Table of ContentsTable of Contents
Page 293 and 294: PresentationsProductivity Dynamics
Page 295 and 296: and scope for improvement, particul
Page 297 and 298: Workshop participants pointed out t
Page 299 and 300: o Can you find the same shared tren
Page 301 and 302: 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
Page 310 and 311: Peer Reviewers: Provide constructiv
Page 312 and 313: MacDonald Environmental Sciences Lt
Page 314 and 315: Appendix C: Workshop MinutesContent
Page 316 and 317: Levy urged researchers to bear in m
Page 318 and 319: within-population, within-brood-yea
Page 320 and 321: To address potential skepticism ove
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Page 324 and 325: considered a good surrogate of temp
Page 326 and 327: Bristol Bay review: There are subst
Page 328 and 329: Method: The approach included formu
Page 330 and 331: 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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