Identifying where vulnerable species occur in a data-poor context: combining satellite imaging and underwater occupancy surveys

Marine ecology progress series

, Vasilis Gerovasileiou¹  , Nikoletta Koukourouvli¹  , Michalis Ragkousis¹  Stelios Katsanevakis¹  , Kostantinos Topouzelis¹  , Thanos Dailianis¹  *, Maria Sini¹ 

[1] University of the Aegean, Department of Marine Sciences, University Hill, 81100 Mytilene, Greece

关键词: Occupancy;    Species distribution;    Biodiversity mapping;    Underwater visual survey;    Detectability;    Marine conservation;   

DOI  :  10.3354/meps12232

学科分类：海洋学与技术

来源: Inter-Research

【 摘 要 】

For the effective conservation of vulnerable marine populations, knowledge of their distributions and spatially explicit management actions are essential. The use of physical features or coarse habitat types as surrogates of species distribution often does not provide an accurate enough (and hence useful) mapping of where species occur. This is further exacerbated in data-poor regions, where habitat maps in the marine environment are often patchy. A combination of satellite imaging analysis (for a rough classification of the main habitat types in shallow waters) and occupancy modelling based on data collected through dedicated underwater surveys is proposed as a relatively inexpensive and timely way to identify priority areas for the conservation of selected benthic species. The occupancy surveys provide estimates of the probability of presence, which can be used as weights of the importance of the available suitable habitat types in a potential habitat index (PHI). This approach was applied in the Aegean Sea (eastern Mediterranean) for 6 benthic hard-bottom species of conservation importance. Repetitive SCUBA diving surveys were conducted at six 5 m depth zones between 0 and 30 m at 47 locations in the Aegean Sea to detect the presence of the target species. Occupancy was modelled using several environmental spatial covariates. The applied method explicitly incorporated imperfect detectability in the modelling process. Predictive distributional maps of PHI were produced for each species, identifying areas that could be prioritized for conservation measures. Despite some limitations, this approach can provide a baseline for the protection of vulnerable species, in the framework of adaptive management for marine conservation planning.

【 授权许可】

Unknown