Monitoring mosaic biotopes in a marine conservation zone by autonomous underwater vehicle

Benoist, Noëlie M.A.; Morris, Kirsty J.; Bett, Brian J.; Durden, Jennifer M.; Huvenne, Veerle A.I.; Le Bas, Tim P.; Wynn, Russell B.; Ware, Suzanne J.; Ruhl, Henry A.. 2019 Monitoring mosaic biotopes in a marine conservation zone by autonomous underwater vehicle. Conservation Biology. (In Press)

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The number of marine protected areas (MPAs) has increased dramatically in the last decade and poses a major logistic challenge for conservation practitioners in terms of spatial extent and the multiplicity of habitats and biotopes that now require assessment. Photographic assessment by autonomous underwater vehicle (AUV) enables the consistent description of multiple habitats, in our case including mosaics of rock and sediment. As a case study, we used this method to survey the Greater Haig Fras marine conservation zone (Celtic Sea, northeast Atlantic). We distinguished 7 biotopes, detected statistically significant variations in standing stocks, species density, species diversity, and faunal composition, and identified significant indicator species for each habitat. Our results demonstrate that AUV‐based photography can produce robust data for ecological research and practical marine conservation. Standardizing to a minimum number of individuals per sampling unit, rather than to a fixed seafloor area, may be a valuable means of defining an ecologically appropriate sampling unit. Although composite sampling represents a change in standard practice, other users should consider the potential benefits of this approach in conservation studies. It is broadly applicable in the marine environment and has been successfully implemented in deep‐sea conservation and environmental impact studies. Without a cost‐effective method, applicable across habitats, it will be difficult to further a coherent classification of biotopes or to routinely assess their conservation status in the rapidly expanding global extent of MPAs.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 0888-8892
Date made live: 27 Jun 2019 14:07 +0 (UTC)

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