Effects of resource spatial distribution, tow overlap, and positional error in the estimation of dredge efficiency

Abstract

Assessing the efficiency of fishing gears, i.e. the fraction of fish in the gear path that are caught and retained, is essential for providing reliable abundance estimates in the management of sedentary invertebrate fisheries. While various methods have been proposed for estimating gear efficiency from experiments, each approach has its strengths and weaknesses, influenced by factors such as resource distribution, tow overlap, and positional errors. In this study, we conducted simulations to gauge the accuracy and precision of four different methods commonly used for estimating gear efficiency and initial density in depletion experiments: Leslie-Davis, DeLury, Removal, and Patch; considering different spatial arrangements of resources, degrees of tow overlap, and positional inaccuracies. We followed designs used in depletion experiments conducted in the Patagonian scallop fishery, commonly employed in scallops and other sedentary species’ fisheries. Our findings reveal that the Patch model, which is specifically harnessed to account for the spatial impact of tows, outperforms the others in terms of accuracy and precision, provided there is no positional error. Estimation of initial density in the simulated depletion experiments showed a similar pattern than that for gear efficiency. The spatial distribution of scallops had no noticeable effect on the precision and bias of efficiency and intial density estimates for any of the models. This holds across all scenarios of spatial clustering and tow overlap. However, when high positional errors in tow locations are at play, the Patch model’s performance is comparable to the other methods. The study highlights the advantages of the Patch model, especially in light of the current availability of high-precision GPS systems that can accurately track tow locations. We also discuss why traditional models may be less suitable for sedentary benthic species, underscoring the importance of selecting appropriate methodologies for specific fishery management tasks.