Statistical catch-at-age analysis (SCA) was used to estimate lake trout abundance and biomass through time (55, 56). The SCA model was estimated for lake trout age 2 and older (1998–2017). The model was fit to annual catch and age composition for suppression netting (1998–2017) and assessment netting (2010–2017; see below). Lake trout catch from trap nets and gill nets was pooled. Total effort in suppression netting was obtained for each year as the pooled catch among gill nets and trap nets divided by gill net CPUE. Instantaneous natural mortality was assumed to be 0.25 for age 2 and 0.16 for age 3 and older lake trout. Fishery selectivity was modeled as a logistic function of age for both suppression and assessment netting. Time-varying catchability was modeled with random deviations around a mean value for each netting type. For suppression netting, a different mean value was estimated for catchability in 1998–2000 and 2001–2017 to account for differences in fishery operation. The model was fit to catch and age composition from suppression netting and assessment netting datasets. Fits to observed catch in the suppression netting and CPUE in the assessment netting were modeled as lognormally distributed. Age compositions were assumed to follow multinomial distributions with a maximum effective sample size of 200 aged fish. Likelihood components for fits to suppression netting and assessment netting data sources were weighted by estimated SDs and effective sample sizes with additional weights not specified. Thus, suppression netting and assessment netting datasets influenced model results equally for years with both types of data. Wald approximations were used to compute approximate 95% confidence intervals (CIs) for abundance using asymptotic SDs produced by AD Model Builder (57).

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