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首页> 外文期刊>Frontiers in Marine Science >Santa Maria di Leuca Province (Mediterranean Sea): Identification of Suitable Mounds for Cold-Water Coral Settlement Using Geomorphometric Proxies and Maxent Methods
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Santa Maria di Leuca Province (Mediterranean Sea): Identification of Suitable Mounds for Cold-Water Coral Settlement Using Geomorphometric Proxies and Maxent Methods

机译:圣玛丽亚迪莱乌卡省(地中海):使用地物学代理和Maxent方法确定适合冷水珊瑚沉降的土丘

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The Santa Maria di Leuca (SML) cold-water coral province (northern Ionian Sea) has the largest occurrence of a living white coral community currently known in the Mediterranean Sea. Madrepora oculata and Lophelia pertusa, identified as marking sensitive habitats of relevance by the General Fisheries Commission for the Mediterranean, have been observed heterogeneously distributed on the summits of several mounds. This particularly patchy and uneven distribution in addition to their importance for regional biodiversity highlights the need to better understand their environmental preferences and predict their distribution. Bathymetric data (40m resolution) was used to derive the seafloor characteristics. A fine scale index quantifying the landscape elevation (Bathymetric Position Index at 120m resolution) was used to select all the elevated features considered as candidate morphologies for potential coral mounds. Statistics on 22 known coral topped mounds were computed. Two statistical methods were then used to identify other potential coral mounds based on predictive variables. The first method, the Geomorphometric proxies method, consists in computing basic statistics of terrain variables, using them for a step-by-step classification in a quantitative approach to select a subset of candidate morphologies. The second method consists in using a predictive Habitat Suitability Model (Maxent model). The Geomorphometric proxies method identified 736 potential coral mounds while the Maxent method predicted 1252 potential coral mounds. A subset of 517 potential coral mounds was common to both methods. The analysis of the contribution of each variable with the Maxent method showed that the variable "Vector Ruggedness Measure" at a resolution of 5 pixels (200 m) contributed to 53% of the final Maxent model, followed by the "Terrain Texture" index (31%) at a resolution of 11 pixels (440 m). The common potential coral mounds are mainly located in an area characterized by a mass transport deposit, also called the mounds area because of the roughness of the seafloor, in accordance with the high proportional contribution of the noticeable first roughness index to the Maxent model. The results highlight the importance of the global conservation of the entire Province, with white coral probably widespread over the entire 600 km2 SML area.
机译:圣玛丽亚莱乌卡(SML)冷水珊瑚省(北爱奥尼亚海)是地中海地区目前已知的活白珊瑚群落最多的地区。被地中海渔业总委员会确定为相关敏感敏感栖息地的斑节菜和南美白对虾被观察到异质分布在几座丘陵的山顶上。除了对地区生物多样性的重要性外,这种分布特别不规则和不均匀的现象突出表明,需要更好地了解其环境偏好并预测其分布。使用测深数据(40m分辨率)得出海底特征。使用量化景观高度的精细比例指数(分辨率为120m的测深位置指数)来选择所有被视为潜在珊瑚丘的候选形态的高地特征。计算了22个已知珊瑚顶丘的统计数据。然后使用两种统计方法根据预测变量确定其他潜在的珊瑚丘。第一种方法是“地物学代理”方法,该方法包括计算地形变量的基本统计信息,并以定量方法将它们用于逐步分类,以选择候选形态的子集。第二种方法包括使用预测性栖息地适应性模型(Maxent模型)。地貌代理方法确定了736个潜在的珊瑚丘,而Maxent方法预测了1252个潜在的珊瑚丘。两种方法共有517个潜在的珊瑚丘子集。使用Maxent方法对每个变量的贡献进行的分析表明,分辨率为5像素(200 m)的变量“ Vector Ruggedness Measure”占最终Maxent模型的53%,其次是“地形纹理”指数( 31%),分辨率为11像素(440 m)。根据显着的第一粗糙度指数对Maxent模型的高比例贡献,常见的潜在珊瑚丘主要位于具有大量沉积物特征的区域,由于海底的粗糙度,也称为丘域。结果突出了整个省的全球保护的重要性,白色珊瑚可能在整个600 km2 SML区域广泛分布。

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