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Fraser River sockeye salmon: data synthesis and cumulative impacts

Fraser River sockeye salmon: data synthesis and cumulative impacts

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estimates, escapement enumeration, escapement targets, over-harvesting <strong>and</strong> Cultus recoveryefforts. For Bristol Bay, pre-season <strong>and</strong> in-season forecasting, escapement <strong>and</strong> goals werereviewed.Key metrics: For each of the above elements, it was necessary to define what was meant byaccuracy (were estimates biased <strong>and</strong> were they based on modeling or known values), precision(what were the quantitative bounds) <strong>and</strong> reliability (level of confidence in estimates, quality <strong>and</strong>quantity of <strong>data</strong>).Quality of catch estimates: A table summarized the assessed accuracy, precision <strong>and</strong> reliabilityof catch estimates for all Canadian fisheries from 2001 to 2009, along with the relativeproportion of Canadian TAC (Total Allowable Catch) taken by each fishery. Many of the valuesfor precision were unknown. There was good accuracy for both First Nations fisheries. A closerlook at commercial fisheries showed inconsistent quality across gear types (e.g. sales slip in netfisheries not representing total catch).Pre-season forecasts: A summary of forecast error (mean absolute percent error) for the 19<strong>Fraser</strong> <strong>sockeye</strong> stocks from 1990 – 2009 showed similar error rates for most stocks except forthose in the Late Summer group, most of which were much higher. Error rates for each runtiminggroup <strong>and</strong> for total <strong>Fraser</strong> <strong>sockeye</strong> stocks (40%) were also provided.A second table summarizing the proportion of the return variation for each stock that wasexplained by forecasts from 1980 to 2009 (i.e. prediction ability of forecasts) showed significantdifferences between stocks. Forecasts for Late Shuswap (a strong cyclic stock) had the strongestpredictive relationship. The relationship was better for the run-timing groups <strong>and</strong> for the <strong>Fraser</strong>overall, but not so much for individual stocks.In-season run-size forecasts: Median percent error (accuracy - 1997-2009): In-season estimatesfor Early Stuart started high but correct rapidly by mid-July. (Does this allow enough time toplan the fishery?) For Early Summers, estimates have been under-estimating abundance early inthe season. By the time they correct, it is too late for a fishery. Summers start with a large overestimation<strong>and</strong> significant correction in late July to mid-August. There is lots of opportunity toharvest from there on. For lates, there was a lot more variability. Estimates start off close <strong>and</strong>then tend to go down.Measures of precision for the four run-timing groups, (median absolute percent error, 1997-2009) show that in-season forecasts can be off by 20 to 50% for most of the season, including thecritical period when the bulk of fishing must take place in marine areas. Reliability of in-seasonforecasts also improves for all run-timing groups towards the end of the season.Basis for recent escapement goals: Goals for <strong>Fraser</strong> <strong>sockeye</strong> low escapement benchmarks <strong>and</strong>fixed escapement targets are set by the FRSSI (<strong>Fraser</strong> Sockeye Spawning Initiative) model.Summaries were presented showing the four-year moving average escapement for each of thefour run-timing groups from 1960 to 2008, relative to the interim limit <strong>and</strong> target referencepoints for escapement. In recent years, only Early Stuart escapement has fallen below the limitreference point, although the Early Summers are getting close.Run size <strong>and</strong> exploitation rates: Comparison of run size <strong>and</strong> exploitation for each of the fourgroups show that over-harvesting may have been an issue in the 1960s, but not recently.36

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