Figure A shows correlations between adult Chinook salmon counts at the Bonneville Dam and coho salmon smolt to adult survival (%) versus a simple composite integrative indicator — the mean rank of all the ecosystem indicators (the second line from the bottom) in Table 2. This index explains about 50% of the variance in adult returns. A weakness of this simple non-parametric approach is that each indicator is given equal weight, an assumption that may not be true. Therefore, we are exploring a more quantitative analysis of the ocean indicators shown in Table 3, using principal component analysis (PCA).
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| Figure A. |
Salmon returns versus the mean rank of ecosystem indicators. Arrows show the forecasted returns of Chinook salmon in 2013 and 2014 (upper four panels) and coho salmon in 2013 (lower left panel). With a mean rank of the ecosystem indicators of 5.9 in 2011, the spring and fall Chinook salmon forecast for 2013 (top left two panels) is 200,000 and 440,000 adults returning to the Bonneville dam respectively. With an only slightly more favorable mean rank (5.5) of the ecosystems indicators in 2012, the forecasted adult returns of spring and fall Chinook salmon are expected to be slightly higher at 215,000 and 460,000 adult fish returning to the Bonneville dam in 2014 (upper right two panels). The smolt to adult survival of coho salmon to Oregon coastal streams is expected to be approximately 3% in 2013 (lower left panel). |
Principal component analysis (PCA) was run on the indicator data. This procedure reduces the number of variables in the dataset as much as possible, while retaining the bulk of information contained in the data (a sort of weighted averaging of the indicators). Another important feature of PCA is that the principal components (PCs) are uncorrelated. This eliminates one of the original problems with the indicator data set (i.e., multi co-linearity).
The first principal component (PC1) explains 52% of the ecosystem variability among years while the second principal component explains only 14%. The indices associated with PC2 were the three upwelling indicators- physical spring transition, upwelling anomaly and length of the upwelling season. Because these three indicators contribute little to our understanding of the ecosystem variability among years, they were removed from the overall ranking system in the stoplight chart.
We used PC1 as a new predictor variable in a linear regression analysis of adult salmon returns (this process is termed principal component regression, or PCR) and those results are shown below in Figure B.
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| Figure B. |
Salmon returns versus the first principal axis scores (PC1) from a Principal Component Analysis on the environmental indicators from Table 2. |
Although the PCA scores represent a general description of ocean conditions, we must acknowledge that the importance of any particular indicator will vary among salmon species/runs. We are therefore working towards stock-specific salmon forecasts by using methods that can optimally weight the indicators for each response variable in which we are interested (Burke et al. 2013). Figure C compares the actual adult returns of adult yearling Chinook salmon, at three different locations along the Columbia River, to the forecasted returns derived from a maximum covariance analysis (MCA) of the ecosystem indicators. This technique is similar to the principal component regression illustrated in Figure B. We chose these three locations because they roughly represent different salmon populations: Bonneville Dam counts represent all Columbia River spring Chinook salmon, Ice Harbor Dam counts represent Snake River spring/summer Chinook salmon, and Priest Rapids Dam counts represent Upper Columbia River spring Chinook salmon. This is work being conducted by Brian Burke (NWFSC/FE).
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| Figure C. |
Time series of observed (blue circles) yearling Chinook salmon adult returns to Bonneville Dam (top), Ice Harbor Dam (middle), and Priest Rapids Dam (bottom). We used Maximum Covariance Analysis to summarize the indicator data and linear regression to fit the adult return data (orange diamonds) with 95% confidence intervals. We also used the model to predict adult returns in 2013 (purple diamonds) with 95% prediction intervals. The model forecasted that 221,000 adult spring Chinook salmon will return to Bonneville Dam in 2013, 97,000 will return to Ice Harbor Dam, and 19,500 to Priest Rapids Dam. The x-axis is the smolt out-migration year that corresponds to the year characterized with ecosystem indicators. Results are from work done by Brian Burke (NWFSC/FE).
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Similar to the past several years, individual indicators have sent a mixed message. Certain indicators suggest the potential for above average returns: i.e. persistence of strong La Niña conditions, a negative PDO, positive copepod indicators from May-September, and high catches of spring Chinook in the June survey. However, negative indicators include a late start to the upwelling season (first week of May), nearly a two month delay until upwelling became strong (not until early July), and very warm sea surface temperatures in June and July. The upwelling season was among the shorter ones, only 161 days (as compared to more than 200 days in 1999, 2002, and 2009). Our best guess is to expect average to above-average returns of coho in 2013 and Chinook in 2014, but similar to the statement we made last year, the mixed signals add greater uncertainty to our predictions.
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