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    The much-publicized threats to coral reef systems necessitate a considered management response based on comprehensive ecological data. However, data from large reef systems commonly originate from multiple monitoring programs that use different methods, each with distinct biases that limit united assessments of ecological status. The effective integration of data from different monitoring methods would allow better assessment of system status and hence, more informed management. Here we examine the scope for comparability and complementarity of fish data from two different methods used on Australia's Great Barrier Reef (GBR): underwater visual census (UVC) and baited remote underwater video stations (BRUVS). We compared commonly reported reef fish measures from UVC and BRUVS on similar reef slope habitats of three central GBR reefs. Both methods recorded similar estimates of total species richness, although ~30% of recorded species were not common to both methods. There were marked differences between methods in sub-group species richness, frequency of species occurrences, relative abundances of taxa and assemblage structure. The magnitude and orientation of inter-method differences were often inconsistent among taxa. However, each method better categorized certain components of fish communities: BRUVS sampled more predatory species in higher numbers while UVC was similarly better at sampling damselfishes (Pomacentridae). Our results suggest limited scope for direct or adjusted comparisons of data from UVC and BRUVS. Conversely, complementary aspects of the two methods confirm that their integration in monitoring programs will provide a more complete and extensive assessment of reef fish status for managers than from either method alone. Copyright © 2021 Elsevier Ltd. All rights reserved.

    Citation

    Alistair J Cheal, Michael J Emslie, Leanne M Currey-Randall, Michelle R Heupel. Comparability and complementarity of reef fish measures from underwater visual census (UVC) and baited remote underwater video stations (BRUVS). Journal of environmental management. 2021 Jul 01;289:112375

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    PMID: 33813301

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