Fraser River sockeye salmon: data synthesis and cumulative impacts

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Appendix 4. Quantitative ResultsA4.1 Trend and Change Point Analysis of Productivity by StockTrend analyses of sockeye productivity (i.e., ln(R/S)) over time found that 6 of the 19 Fraserstocks were better fit by the piece-wise regression model (allowing for 2 different trends over thetime-series) than a single straight line regression over time (Table A4.1-1). The recent trends for5 of these stocks (excluding Pitt) ranged from: -0.050 to -0.141, which is equivalent to annualdeclines on the R/S scale of: ~5% (Early Stuart) to 13% 22 (Quesnel). The earliest change-pointoccurred in 1965 (Early Stuart) and the latest occurred in 1988 (Chilko). Pitt is reportedseparately as we are not sure how reflective this stock is of other wild Fraser stocks due to itshigh hatchery influence. The recent trend in Pitt was -0.466, which corresponds to an averageannual decline of ~35% since 1999. Despite having only 5 years of data to estimate the post1999 trend, the p-value was
(Fennell), which is equivalent to annual declines on the R/S scale of: ~1.7% to 6.5% since~1950.Table A4.1-2. Summary of stocks where a single trend line was more appropriate. The estimated slope of the line isshown along with the associated test statistic and p-value (significant p-values are indicated by a *).Arrows indicate the direction of the trend.Stock Slope (b1) Test statisticfor b1p-value 23Trend overentire timeseriesBirkenhead -0.035 -4.059 < 0.001* ↓Bowron -0.017 -2.520 0.015* ↓Fennell -0.067 -5.374 < 0.001* ↓Gates -0.050 -4.071 < 0.001* ↓Harrison 0.012 0.978 0.332 ↔L.Shuswap -0.007 -0.889 0.378 ↔L.Stuart -0.027 -2.464 0.017* ↓Nadina -0.028 -1.849 0.074↓ (weakevidence)↓(weakevidence)Portage -0.021 -1.935 0.059Raft -0.005 -0.690 0.493 ↔Scotch -0.048 -3.346 0.002* ↓Seymour -0.023 -3.073 0.003* ↓Weaver -0.004 -0.294 0.770 ↔A4.2 Analyses of Stock CompositionThree time periods follow a very similar pattern both in terms of the shape of the concentrationprofile and the average number of recruits (between 4 & 6 million), these include the two earliesttime periods: 1948-1959, 1960-1971, and the most recent one: 1996-2006 (Figure A4.2-1). Theother two time periods have a similar shape but the average number of recruits was substantiallyhigher: 1972-1983 (~8 million) and 1984-1995 (~11 million). When the y-axis was scaled to 1to represent the cumulative proportion of total recruits, we see that the shape of the curves arevery similar across all time periods with 80% of the total recruits composed of only 4-6 stocksout of the 19 evaluated (Figure A4.2-2). The primary reason for plotting these figures was todetermine if the portfolio balance had changed over time and if that might be a potentialexplanation for the long-term decline in Fraser River sockeye productivity. While the totalnumber of recruits has varied substantially over time, the shape of the concentration profile hasnot. Contrary to our expectation, there has not been a substantial change in the “portfolio23 P-value is associated with the null hypothesis that the slope (b1) = 0. A small p-value (i.e.,
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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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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 228 and 229: Figure A3.5-3. Average chlorophyll
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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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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
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Page 283 and 284: Metric Connected to Biologically-su
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
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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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