Fraser River sockeye salmon: data synthesis and cumulative impacts

categories of stressors. We cannot evaluate or make conclusions about how they relate to othercategories of stressor not included in that particular analysis.Summary of approachThe basic steps we used to complete this analysis were:1. Generate model setso Generate hypotheses linking all data we received to the appropriate life stage(Appendix 3.4-3-3.4-9)o Summarize the available data by time period and type (Table A3.5-1)o Select windows of time where different covariates could be compared. Forexample, we identified which covariates were available for a ‘Very Long’ time(i.e., 54 years).o Identify questions/hypotheses that could be tested within each model set. Forexample, the ‘Very Long’ time period would not enable us to compare modelswith sea surface temperature and chlorophyll, but the ‘Short’ time period would.2. Generate candidate modelso Identify logical groupings of covariates that can be included or excluded to testspecific questions/hypotheses (e.g., which life stage is limiting sockeyeproductivity?)o Consider whether or not to include any non-linear termso Consider whether or not to include any interaction terms3. Data Reductiono Reduce the number of variables based on our best understanding of the biologicalhypotheses, correlation analysis, and principal components analysiso Extract the data for a given model set and time period4. Final processing and analysiso Process the data to produce a complete data set for each model set (i.e., removeany rows with missing data for any of the covariates within the model set andtime period)o Fit each model (i.e., estimate the parameters) in the model set and generate a tableof AICc values to compare the relative fit of each model.222