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High Seas Marine Protected Areas: Benthic Environmental Conservation Priorities From A Gis Analysis Of Global Ocean Biophysical Data

机译:公海海洋保护区:全球海洋生物物理数据的地理信息系统分析得出的底栖生物环境保护优先事项

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Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed "seascapes". A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.
机译:设计公海海洋保护区(MPA)的代表性网络需要一种可接受的方案来对海洋底栖生物区(以及中上层)进行生物分类。鉴于缺乏足够的生物学信息来完成此任务,我们使用具有6个生物物理变量(深度,海床坡度,沉积物厚度,初级产量,底部水溶解氧和底部温度)的多元统计方法将海床客观地分类为53,713包含11个不同类别的单独多边形,我们称之为“海景”。通过将海景与现有的海底地貌和海底沉积物类型地图进行比较,并通过GIS分析单独多边形的数量,多边形面积和周长/面积比,对海景分类进行交叉检查。我们得出的结论是,使用多元统计方法得出的海景是海床在生物学上有意义的细分,可以预期包含不同的生物关联,就像不同的地貌单位所做的一样。在某些海洋景观中,不到20%发生在公海,而其他海洋景观则主要限于公海,这表明其保护和养护需要国际合作的特定类型的环境。我们的研究说明了如何通过对海底地貌和海景分类图进行简单的GIS分析来完成公海海洋保护区潜在地点的识别。使用这种方法,生成了海景和地貌异质性地图,其中异质性热点将自己标识为MPA候选对象。计算机辅助绘图工具的使用消除了MPA设计过程中的主观性,并为利益相关者提供了更大的信心,使他们能够获得公正的结果。

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