Reconciling conflicting survey indices of abundance prior to stock assessment

Abstract Indices of relative abundance are one the most important inputs into a stock assessment model. For many species, we must rely on several indices that routinely conflict with each other and which may result in biased uncertain outputs. Here, explored whether reconciled trends obtained from dynamic factor analysis (DFA) applied to conflicting can be used as trend input We simulated an age-structured population two coastal shark species southeast United States generate multiple disagreeing indices, using DFA, then inserted both survey simplified DFA-predicted respective models. compared results model values evaluate performance approach. found DFA-based generally performed similarly index-based useful tool situations where different selectivities, catchabilities, variances, missing data present. DFA were more consistent across simulation scenarios outperformed index assessments when surveys underwent shifts catchability underlying exhibited contrast.