Longitudinal analyses of catch-at-age data for reconstructing year-class strength, with an application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron

We investigated using longitudinal models to reconstruct year-class strength (YCS) from catch-at-age data, with an example application to lake trout (Salvelinus namaycush) in the main basin of Lake Huron. The best model structure depended on the age range used for model implementation. The YCS trajectory from the full age range (3-30 years) was similar to the trajectory from a narrow age range that approximated the age of recruitment to the fishing gears (5-7 years), but YCS estimates from the full age range included additional variations due to time-dependent selectivity and mortality. When using ages younger or older than the likely ages of recruitment, YCS estimates did not represent recruitment abundances and were also biased by trends in agespecific selectivity and mortality across years. Longitudinal YCS estimates are likely more robust than single-age recruitment indices, which are often subject to interannual changes in catchability and selectivity. Our findings provide guidance for future applications of the longitudinal YCS reconstruction that in turn may inform and supplement more comprehensive research and management programs for understanding fish recruitment dynamics.

Automated summary

We investigated the use of longitudinal models to reconstruct year-class strength (YCS) and applied it to lake trout in Lake Huron. The best model structure depended on the age range used for model implementation. YCS estimates from the full age range included variations due to time-dependent selectivity and mortality, while using ages outside the likely recruitment range resulted in biased estimates. Longitudinal YCS estimates are likely more robust than single-age recruitment indices and can inform research and management programs on fish recruitment dynamics.