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Exploring Macroinvertebrate Species Distributions at Regional and Local Scales across a Sandy Beach Geographic Continuum

机译:在沙滩地理连续区内探索区域和地方尺度上的大型无脊椎动物物种分布

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摘要

Exposed sandy beaches are highly dynamic ecosystems where macroinvertebrate species cope with extremely variable environmental conditions. The majority of the beach ecology studies present exposed beaches as physically dominated ecosystems where abiotic factors largely determine the structure and distribution of macrobenthic communities. However, beach species patterns at different scales can be modified by the interaction between different environmental variables, including biotic interactions. In this study, we examined the role of different environmental variables for describing the regional and local scale distributions of common macrobenthic species across 39 beaches along the North coast of Spain. The analyses were carried out using boosted regression trees, a relatively new technique from the field of machine learning. Our study showed that the macroinvertebrate community on exposed beaches is not structured by a single physical factor, but instead by a complex set of drivers including the biotic compound. Thus, at a regional scale the macrobenthic community, in terms of number of species and abundance, was mainly explained by surrogates of food availability, such as chlorophyll a. The results also revealed that the local scale is a feasible way to construct general predictive species-environmental models, since relationships derived from different beaches showed similar responses for most of the species. However, additional information on aspects of beach species distribution can be obtained with large scale models. This study showed that species-environmental models should be validated against changes in spatial extent, and also illustrates the utility of BRTs as a powerful analysis tool for ecology data insight.
机译:裸露的沙滩是高度动态的生态系统,其中的无脊椎动物物种可以应对极端多变的环境条件。大多数海滩生态学研究都将裸露的海滩视为以物理为主的生态系统,其中非生物因素在很大程度上决定了大型底栖动物群落的结构和分布。但是,可以通过不同环境变量之间的相互作用(包括生物相互作用)来改变不同规模的海滩物种分布。在这项研究中,我们研究了不同环境变量在描述西班牙北部沿海39个海滩上常见大型底栖动物物种的区域和局部尺度分布中的作用。分析是使用增强回归树进行的,该树是机器学习领域中的一种相对较新的技术。我们的研究表明,裸露海滩上的大型无脊椎动物群落不是由单一物理因素构成的,而是由包括生物化合物在内的一系列复杂驱动因素构成的。因此,在区域尺度上,大型底栖动物群落在物种数量和丰富度方面主要是由诸如叶绿素a等食物可获得性的替代物来解释的。结果还表明,局部尺度是构建一般预测物种-环境模型的可行方法,因为来自不同海滩的关系对大多数物种显示出相似的响应。但是,可以使用大型模型获得有关海滩物种分布方面的其他信息。这项研究表明,应该针对空间范围的变化对物种-环境模型进行验证,并且还说明了BRT作为实用的生态数据分析工具的实用性。

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