Fraser River sockeye salmon: data synthesis and cumulative impacts

Table A4.3-22. Model specifications for the 1996-2004 (brood years) model set for the Strait of Georgia. This tableshows the variables included in each of the 8 models tested (i.e. M1 to M8) within this model set. Table4.4-1 explains which specific data sets were used for each of these variables. “Rank of model” reflects theAIC c score showing level of support (#1 ranked model had the highest level of support and lowest AIC cscore).Region Variable M1 M2 M3 M4 M5 M6 M7 M8 M9SoG Chlorophyll X X X X XSoG Temperature X X X X XSoG Salinity X X X X XSoG Discharge X XRank of model 3 9 8 6 2 1 5 4 7Within the SoG model set, Models M6 (SSS) and M5 (SSS and SST) have the strongest supportwithin the group (Table A4.3-23 and Table A4.3-24). M6 and M5 have very similar AICc scores(∆AICc = 1.53) and only differ by one parameter, this implies that SST is an uninformativeparameter relative to SSS (Arnold 2010). However, the ∆AICc show that there is also relativelylittle difference in support from the M1 global model (∆AICc = 2.59 and M6) despite theaddition of 5 extra parameters and therefore M1 is a legitimately competing model for SoG.Chlorophyll in SoG on its own does not appear to be an important explanatory variable for FraserRiver sockeye salmon productivity, at least over the period of 1996-2004.In summary, while the results show that QCS chlorophyll may be an important metric inexplaining the variation in sockeye salmon productivity over the period of 1996-2004, whereasQCS temperature and salinity are relatively uninformative parameters. To the contrary, withinSoG during this timeframe, salinity has strong support and the remaining parameters are found tobe uninformative, except when they are all included together in the global model. One should bevery cautious about drawing conclusions from patterns observed over such a very short period oftime, but these results do at least indicate that there may be strong regional differences in theimportance of the potential drivers examined. During the data processing steps of this project, itwas noted that the variance in chlorophyll measured in the Northern SoG was substantiallygreater than that measured in the Central SoG across all months where data were provided(Figure A3.5-3). It may be worth examining these regional differences more closely.261