Embracing uncertainty to reduce bias in hydroacoustic species apportionment

Abstract

Species-specific abundance estimates lend insight into fish ecology, inform sustainable fisheries management, and remain the goal of hydroacoustic fisheries sampling. The apportionment process, assigning aggregate hydroacoustic data to individual species, is affected by uncertainties in both hydroacoustic and species composition data. These uncertainties have associated biases that can propagate through the apportionment process and degrade abundance estimates. We developed an apportionment procedure that reduces the influence of sampling, threshold, and misclassification biases leading to more accurate species-specific abundance estimates. We applied our method to Lake Erie walleye, using paired hydroacoustic and gillnet sampling data, and generated distribution and abundance estimates supported by known ecological patterns. Flexibility in this approach performed better than traditional threshold methods that ignore uncertainty in catch composition, threshold choice, and target-strength uncertainty.