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Fraser River sockeye salmon: data synthesis and cumulative impacts

Fraser River sockeye salmon: data synthesis and cumulative impacts

Fraser River sockeye salmon: data synthesis and cumulative impacts

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Challenges <strong>and</strong> OpportunitiesDave Marmorek, ESSAIt’s useful to think of all the science contractors as one science panel probing the evidence. Thiswork seeks to build on the most recent PSC report, regarding the evidence for <strong>and</strong> againstdifferent factors. Contractors should build on that report, but not be constrained by it. If those ofyou who attended the PSC workshop reached different conclusions (say you found betterindicators), provide evidence for changing your conclusions. Underst<strong>and</strong> the pattern <strong>and</strong> thenseek the causes. Look at patterns over space <strong>and</strong> time <strong>and</strong> between stocks to say which suspectsor combination of suspects are most likely.The <strong>cumulative</strong> effects project, which will be discussed further on Day 2, is looking at therelative importance of different factors <strong>and</strong> which are most relevant, <strong>and</strong> also at combined effectsor causal mechanisms that may be inter-related (e.g. various <strong>impacts</strong> stemming from climatechange).If the workshop produces a long list of priorities, that is not useful. Think about what decisionsare affected by the information (e.g. If I knew X what would I do differently) <strong>and</strong> whether thereis a role for real management experiments <strong>and</strong> if so on what scale.There are different forms of indirect evidence that we can think about. Even if there is imperfectevidence, can we still see contrast across different stocks or across time or space?Research program presentationsProductivity dynamics of <strong>sockeye</strong> <strong>salmon</strong>: patterns that need to beexplainedR<strong>and</strong>all Peterman & Brigitte DornerThis presentation covered <strong>data</strong> <strong>and</strong> methods, spatial <strong>and</strong> temporal patterns in productivity for<strong>Fraser</strong> <strong>and</strong> non-<strong>Fraser</strong> <strong>sockeye</strong> stocks, stocks with similar patterns, <strong>and</strong> conclusions <strong>and</strong> anemergent hypothesis.Background: The disastrous 2009 <strong>Fraser</strong> <strong>sockeye</strong> return (1.5 million adults, the lowest since1947) was just the latest in a decades-long decline in abundance <strong>and</strong> productivity (returningadults per spawner) for <strong>Fraser</strong> <strong>sockeye</strong>. The <strong>Fraser</strong> saw peak runs of up to 40 million <strong>sockeye</strong>every fourth year until the 1913 Hells Gate slide. Following that event, decades of slowrebuilding continued through the 1980s <strong>and</strong> then changed to a decline. The 4-year movingaverage for adult returns per spawner hovered around 5 or 6 adult returns per spawner from thelate 1960s until the early 1990s, then declined steadily to less than 1 in 2009, before returning toabout 6 in 2010. (This was the overall pattern across all <strong>Fraser</strong> <strong>sockeye</strong> stocks – trends differedamong individual stocks.)The study looked at 52 <strong>sockeye</strong> stocks with decent time series of spawners <strong>and</strong> the resultingadult recruits, covering an area extending from Lake Washington in Seattle to Alaska (19 ofthese stocks were from the <strong>Fraser</strong> <strong>River</strong>). It looked at st<strong>and</strong>ard productivity indices (recruits perspawner; plus for the <strong>Fraser</strong> only, there were <strong>data</strong> for effective female spawners, which is a bettermeasure). The stationary Ricker model (it assumes a <strong>and</strong> b are stationary) was used to calculateannual residuals. The Larkin model was included as an alternative to the Ricker model toinvestigate possible delayed-density dependence. Both the Ricker <strong>and</strong> Larkin models remove28

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