Optimizing stereo‐baited remote underwater video sampling efficiency in turbid waters through horizontal field of view adjustments

Abstract

Accurate length data underpin many ecological and physiological analyses, from assessing population size structure to parameterizing biomass and bioenergetic models. Stereo‐baited remote underwater video systems (stereo‐BRUVs) provide a non‐intrusive means of collecting these data in situ, supporting management and conservation of motile marine assemblages. These systems are used across a range of habitats; however, their effectiveness in turbid waters is limited when using standard stereo‐BRUV configurations, designed to maintain accuracy at greater distances under good visibility. Under turbid conditions, individuals are usually only visible within the first few meters of the cameras, often falling outside the stereo‐overlap area, preventing measurements. To address this limitation, we characterized how camera horizontal field of view (H‐FOV) affects the minimum distance and area of stereo‐overlap, as well as measurement accuracy, using GoPro Hero 9 cameras across narrow, linear, and wide lens settings between ranges of 0.5–4.0 m. Wider H‐FOVs substantially increased the usable overlap area and improved nearfield coverage, although distortion at image peripheries reduced accuracy with distance. Spatial error mapping showed high accuracy across most of the overlap (< 1% at 4 m), with pronounced error (> 14%) confined to extreme edges. We recommend selecting the wide H‐FOV to increase the likelihood individuals fall within the stereo‐overlap in turbid conditions, while applying spatial constraints to exclude measurements from image peripheries beyond 2.5 m. This approach expands the effective measurement zone under reduced visibility without compromising accuracy, supporting robust length‐based biomass estimates and improving the applicability of stereo‐BRUV data for downstream ecological analyses in turbid environments.