Comparison of virtual population analysis and statistical kill-at-age analysis for a recreational, kill-dominated fishery

Abstract

We used simulations to compare the distributions of estimation errors for virtual population analysis using forward calculation (FVPA) and three variants of statistical kill-at-age analysis (KAA). The KAA variants assumed constant, time-blocked, and nonadditive selectivity. Simulations were based on a recreational walleye (Sander vitreus) fishery in Lake Mille Lacs, Minnesota. The focus of our experiments was on how model mis-specification (incorrect assumptions about selectivity for KAA or that kill had no error for FVPA) interacted with the magnitude of measurement errors and fishing mortality. We found that KAA models outperformed FVPA when they assumed the correct selectivity pattern, even when kill was measured without error. Of particular concern was a strong tendency by FVPA to overestimate stock size when kill was measured with substantial error. When KAA was based on an incorrect assumption regarding fishery selectivity and kill was measured with little error, wide distributions of errors and substantial biases sometimes resulted. KAA models that allowed fishery selectivity to change over time performed about as well as a constant-selectivity KAA model when selectivity was constant, and they performed much better when selectivity changed over time. Careful consideration of alternative fishery selectivity models should be a fundamental part of any age-structured assessment.