Repeatability of baited remote underwater video station (BRUVS) results within and between seasons

Abstract

Baited remote underwater video stations (BRUVS) are increasingly being used to evaluate and monitor reef communities. Many BRUVS studies compare multiple sites sampled at single time points that may differ from the sampling time of another site. As BRUVS use grows in its application to provide data relevant to sustainable management, marine protected area success, and overall reef health, understanding repeatability of sampling results is vital. We examined the repeatability of BRUVS results for the elasmobranch community both within and between seasons and years, and explored environmental factors affecting abundances at two sites in Indonesia. On 956 BRUVS, 1139 elasmobranchs (69% rays, 31% sharks) were observed. We found consistent results in species composition and abundances within a season and across years. However, elasmobranch abundances were significantly higher in the wet season. The elasmobranch community was significantly different between the two sites sampled, one site being more coastal and easily accessed by fishermen. Our results demonstrate that while BRUVS are a reliable and repeatable method for surveying elasmobranchs, care must be taken in the timing of sampling between different regions to ensure that any differences observed are due to inherent differences amongst sampling areas as opposed to seasonal dissimilarities.

Elasmobranch diversity around the southern Caribbean island of Tobago: opportunities for conservation in a regional trade hub

“…Briefly, habitat relief is calculated in a 5 by 4 grid overlayed on a screenshot from each video and is a measure of complexity. Every rectangle in the grid is given a score following Polunin and Roberts (1993) between 0 (no relief) and 5 (high relief) and the mean is calculated from all rectangles that do not contain open water (MacNeil et al, 2020;Sherman et al, 2020). We examined error structure using the R package 'DHARMa' (Hartig, 2020) to check residual diagnostics for all response variables, selecting a Poisson structure for both aggregated large sharks and Caribbean reef sharks, Carcharhinus perezi, and a negative binomial (NB) error structure for all other species and aggregated species (Table 1).…”

Camera methods for the assessment of coastal biodiversity in low visibility environments

“…Furthermore, morphologically indistinguishable species (cryptic) also become lost when implementing these tools. Seasons should be considered when interpreting data from BRUV deployments, especially across years as these may also influence the species present as well as relative abundances in any one deployment (Sherman et al, 2020). Of the nine habitats targeted during the 457 BRUV deployments, only 7% were conducted in midwater habitats.…”