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探究沙质海滩地理连续体上的宏观无脊椎动物物种在区域和局部尺度上的分布情况。

Exploring macroinvertebrate species distributions at regional and local scales across a sandy beach geographic continuum.

机构信息

Departamento de Ecología y Biología Animal, Universidad de Vigo, Vigo, Spain.

出版信息

PLoS One. 2012;7(6):e39609. doi: 10.1371/journal.pone.0039609. Epub 2012 Jun 25.

Abstract

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.

摘要

暴露的沙滩是高度动态的生态系统,其中无脊椎动物物种应对极其多变的环境条件。大多数沙滩生态学研究将暴露的沙滩呈现为物理主导的生态系统,其中非生物因素在很大程度上决定了大型底栖生物群落的结构和分布。然而,不同尺度的沙滩物种模式可以通过不同环境变量之间的相互作用来改变,包括生物相互作用。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 个沙滩上常见大型底栖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,这是机器学习领域的一项新技术。我们的研究表明,暴露沙滩上的无脊椎动物群落不是由单一的物理因素构成的,而是由包括生物化合物在内的一组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(就物种数量和丰度而言)主要由食物供应的替代物(如叶绿素 a)来解释。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,因为来自不同沙滩的关系对大多数物种表现出相似的响应。然而,通过大尺度模型可以获得有关沙滩物种分布方面的其他信息。这项研究表明,物种-环境模型应针对空间范围的变化进行验证,并说明了 BRT 作为生态学数据洞察的强大分析工具的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/782b/3382464/d5f2caff69a8/pone.0039609.g001.jpg

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