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首页> 外文期刊>Ecological informatics: an international journal on ecoinformatics and computational ecology >Seafloor geomorphic features as an alternative approach into modelling the distribution of cetaceans
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Seafloor geomorphic features as an alternative approach into modelling the distribution of cetaceans

机译:海底地貌特征作为替代鲸类分布的替代方法

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摘要

Bathymetric proxies tend to indicate the relationships between the distribution of cetaceans and the seafloor in species distribution models (SDMs). Usually, seafloor features are described arbitrary to explain these relationships. Currently, a global seafloor geomorphic features dataset is available, with an objective identification and full representation for each seafloor geomorphic feature. Models based on common bathymetric proxies were compared with models with seafloor predictors, by a standardized ensemble SDM framework. Occurrences of two species with different foraging strategies and relationships with the seabed were selected: the sperm whale (Physeter macrocephalus) and the striped dolphin (Stenella coeruleoalba).. For sperm whales, GLM models had a significant better performance with seageomorphic features than with the common bathymetric proxies. In GAM and MARS models, the performance was similar for both seabed features and bathymetric proxies' models. In relation to striped dolphins, all models obtained had a significant better performance with seafloor features than with bathymetric proxies, regardless the modelling technique. The models showed preference of sperm whales for areas distant from the continental shelf and continental rise areas which consists of submarine canyons with adjacent submarine fans. Striped dolphins showed a clear preference for continental slope areas. The modelling based on seafloor geomorphic features support the hypothesis that the use of this type of predictors can improve the modelling performance and provide a complementary understanding of the relationship between cetaceans and the seafloor.
机译:碱基替代代理倾向于表示鲸类和物种分布模型(SDMS)中的鲸类和海底之间的关系。通常,Seafloor特征被描述任意解释这些关系。目前,可以提供数据集的全球海底地貌特征,每个海底地貌特征都有客观识别和全面代表。将基于常见的浴权代理的模型与带有海底预测器的模型进行比较,通过标准化的集合SDM框架。选择了两种具有不同的觅食策略和与海底关系的物种的发生:精子鲸鱼(物质麦芽糖)和条纹海豚(Stenella Coeruleoalba)..对于精子鲸,GLM模型具有比与海关特征更好的性能常见的沐浴床。在GAM和MARS模型中,对海底特征和沐浴店的型号相似。与条纹海豚有关,所获得的所有模型都具有与海底特征具有显着更好的性能,而不是与碱基代理有关,无论建模技术如何。该模型显示出距离大陆架子和大陆覆盖区域远处的区域的精子鲸,由带有相邻的潜艇风扇的潜艇峡谷组成。条纹海豚对大陆坡面积表示清晰的偏好。基于海底地貌特征的建模支持的假设,这种类型的预测因子的使用可以提高建模性能,并提供对鲸类和海底之间关系的互补理解。

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