Abstract

A standard approach to improving the accuracy of reef fish population estimates derived from underwater visual censuses (UVCs) is the application of species-specific correction factors, which assumes that a species’ detectability is constant under all conditions. To test this assumption, we quantified detection rates for invasive Indo-Pacific lionfish (Pterois volitans and P. miles), which are now a primary threat to coral reef conservation throughout the Caribbean. Estimates of lionfish population density and distribution, which are essential for managing the invasion, are currently obtained through standard UVCs. Using two conventional UVC methods, the belt transect and stationary visual census (SVC), we assessed how lionfish detection rates vary with lionfish body size and habitat complexity (measured as rugosity) on invaded continuous and patch reefs off Cape Eleuthera, the Bahamas. Belt transect and SVC surveys performed equally poorly, with both methods failing to detect the presence of lionfish in >50 % of surveys where thorough, lionfish-focussed searches yielded one or more individuals. Conventional methods underestimated lionfish biomass by ~200 %. Crucially, detection rate varied significantly with both lionfish size and reef rugosity, indicating that the application of a single correction factor across habitats and stages of invasion is unlikely to accurately characterize local populations. Applying variable correction factors that account for site-specific lionfish size and rugosity to conventional survey data increased estimates of lionfish biomass, but these remained significantly lower than actual biomass. To increase the accuracy and reliability of estimates of lionfish density and distribution, monitoring programs should use detailed area searches rather than standard visual survey methods. Our study highlights the importance of accounting for sources of spatial and temporal variation in detection to increase the accuracy of survey data from coral reef systems.

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