海景
水深测量
海洋保护区
拖网捕鱼
环境生态位模型
地理
地中海气候
渔业
海洋学
地中海
环境科学
生态学
地质学
垂钓
生态位
栖息地
生物
考古
作者
Fábio L. Matos,Joan B. Company,Marina R. Cunha
标识
DOI:10.1016/j.dsr.2021.103496
摘要
Ecological niche modelling is used in deep-sea research to investigate the environmental preferences and potential distribution of data-poor species. We present a mesoscale assessment of Mediterranean seascape suitability for the cold-water coral Lophelia pertusa (= Desmophyllum pertusum, Linnaeus, 1758). We estimated seascape suitability and uncertainty maps using an ensemble approach of three machine-learning algorithms (Generalized Boosting Model, Random Forest, Maximum Entropy) based on environmental predictors. Bathymetry, bathymetric slope and pH were the most important predictors for the models. Overall the models reached good to excellent performance, with a very reliable prediction of the most suitable areas. In the Mediterranean Sea, L. pertusa encounters environmental settings close to its physiological limits but, despite the highly variable quality of the Mediterranean seascape, we identified high suitability areas mostly along the upper slope and at submarine canyons of the Western and Central margins. The existing MPAs do not overlap with high suitability areas, and therefore L. pertusa is only protected at the deepest fringe of its potential distribution by the implementation of the bottom trawling exclusion beyond 1000 m depth. This seascape suitability assessment may assist future research, including high-resolution modelling targeting high-suitability areas, investigation on the resilience of L. pertusa populations and development of conservation actions.
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