Embracing uncertainty to reduce bias in hydroacoustic species apportionment

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.

Automated summary

In this study, a novel apportionment procedure was developed to reduce biases caused by uncertainties in hydroacoustic and species composition data, resulting in more accurate species-specific abundance estimates. Applied to Lake Erie walleye, this approach demonstrated better performance compared to traditional methods, taking into account uncertainties in catch composition, threshold choice, and target-strength uncertainty, and generating accurate distribution and abundance estimates.