Predicted Deep-Sea Coral Habitat Suitability for the U.S. West Coast

Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.

区域尺度生境适宜性模型（Regional scale habitat suitability models）可提供更高的空间分辨率，对物种潜在分布区域作出更具针对性的预测。既往建模方法多聚焦于局地和/或全球尺度，而区域尺度的模型相对匮乏。本研究针对美国西海岸（加利福尼亚州、俄勒冈州与华盛顿州）的深海珊瑚构建了区域尺度预测性生境模型。本模型结果旨在助力未来研究与制图工作，可用于评估现有底拖网禁渔区（即关键鱼类生境（Essential Fish Habitat, EFH））内外的潜在珊瑚生境适宜性，并识别美国国家海洋保护区（U.S. National Marine Sanctuaries, NMS）内的适宜生境。本研究以500米×500米的空间分辨率构建深海珊瑚生境适宜性模型，选取了一系列已知或被认为会影响深海珊瑚分布的物理、化学与环境变量。采用空间分区交叉验证方法，通过最大熵模型（maximum entropy models）识别出坡度、水温、盐度与水深为多数深海珊瑚类群的重要预测因子。模型预测显示，现有底拖网禁渔区与NMS边界内外均分布有大面积高度适宜的深海珊瑚生境。当前区域尺度的生境适宜性预测尚无法精准定位珊瑚分布区域，且由于模型本身的局限性以及未纳入已知会限制珊瑚分布的变量（如硬质底质分布数据），预测结果可能会高估实际的珊瑚分布范围。本研究的预测生境结果应与多波束测深、地质制图及其他工具结合使用，以指引未来研究聚焦于最有可能存在深海珊瑚的区域。还需对预测生境开展野外验证，以量化模型的预测精度，尤其是在尚未开展采样的区域。