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首页> 外文期刊>Ecological informatics: an international journal on ecoinformatics and computational ecology >Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data
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Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data

机译：利用水下遥感数据对冷水珊瑚栖息地分布进行生态位建模

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摘要

Despite a growing appreciation of the need to protect sensitive deep sea ecosystems such as cold-water corals, efforts to map the extent of their distribution are limited by their remoteness. Here we develop ecological niche models to predict the likely distributions of cold-water corals based on occurrence records and data describing environmental parameters (e.g. seafloor terrain attributes and oceanographic conditions). This study has used bathymetric data derived from ship-borne multibeam swath systems, species occurrence data from remotely operated vehicle video surveys and oceanographic parameters from hydrodynamic models to predict coral locations in regions where there is a paucity of direct observations. Predictions of the locations of the scleractinian coral, Lophelia pertusa are based primarily upon ecological niche modelling using a genetic algorithm. Its accuracy has been quantified at local (similar to 25 km(2)) and regional scales (similar to 4000 km(2)) along the Irish continental slope using a variety of error assessment techniques and a comparison with another ecological niche modelling technique. With appropriate choices of parameters and scales of analyses, ecological niche modelling has been effective in predicting the distributions of species at local and regional scales. Refinements of this approach have the potential to be particularly useful for ocean management given the need to manage areas of sensitive habitat where survey data are often limited.
机译：尽管越来越需要保护敏感的深海生态系统（如冷水珊瑚），但绘制地图的程度受到其偏远地区的限制。在这里，我们基于出现记录和描述环境参数（例如海底地形属性和海洋条件）的数据，开发了生态位模型来预测冷水珊瑚的可能分布。这项研究使用了来自船载多波束测绘带系统的测深数据，来自远程车辆视频调查的物种发生数据以及来自水动力模型的海洋学参数来预测缺乏直接观测的地区的珊瑚位置。巩膜珊瑚Lophelia pertusa的位置预测主要基于使用遗传算法的生态位建模。使用各种误差评估技术，并与另一种生态位建模技术进行比较，已在爱尔兰大陆坡的局部（类似于25 km（2））和区域范围（类似于4000 km（2））上量化了其精度。通过适当选择参数和分析规模，生态位模型可以有效地预测当地和区域尺度上物种的分布。鉴于需要管理经常受到调查数据限制的敏感栖息地区域，这种方法的改进可能对海洋管理特别有用。

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