Estimating length composition of fish observed with stereo-video cameras: A simulation study with application to red snapper (Lutjanus campechanus)

Abstract

Stereo-video cameras have become an important tool worldwide for enumerating abundance and length compositions of marine fish. The two most common approaches for enumerating are referred to as MaxN and MeanCount, where the former counts fish on the single video frame with the most individuals observed and the latter uses the mean across multiple frames. Previous studies have demonstrated that both approaches may work well for computing relative abundance. However, basic fish population age-structure (e.g. more younger fish) and fish schooling characteristics (e.g. fish of similar size/age swim together) suggest the potential for bias in length compositions computed from the MaxN approach, as the single video frame with the most individuals would tend to overrepresent smaller, more populous fish. To evaluate the two approaches, we simulated a stationary video system placed on a sampling site inhabited by moving fish, and we compared length compositions estimated from each approach to that of the true, underlying population. Indeed, MaxN appears biased over a range of potential factors, in which the bias is toward estimates of mean size that are smaller than the true values. The factors leading to biased age/length estimates from MaxN include 1) large fish counts in the single frame, 2) fish schooling by age/length, especially at moderate school densities, and 3) small camera viewing area relative to the site being sampled. In addition to the general evaluation, we applied the simulation framework to video parameters derived from data on red snapper (Lutjanus campechanus) in U.S. Atlantic waters. The results suggest that the MaxN length composition bias is small for red snapper due primarily to the low counts of fish on site and low levels of schooling observed.