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首页> 外文期刊>Ocean & coastal management >Defining soft bottom habitats and potential indicator species as tools for monitoring coastal systems: A case study in a subtropical bay
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Defining soft bottom habitats and potential indicator species as tools for monitoring coastal systems: A case study in a subtropical bay

机译：定义软底生境和潜在指标物种作为监测沿海系统的工具：以亚热带海湾为例

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摘要

The definition of habitats and indicator species is a prerequisite for monitoring and conservation programs. Nonetheless, defining habitats in marine soft-bottom environments is challenging given their spatiotemporal dynamics and apparent homogeneity. The selection of indicator species is also complicated given the large number of occasional species usually presented in benthic communities. This study aims to elaborate a framework based on well-established analytical methodologies to identify soft-bottom habitats and select indicator species to support monitoring and conservation programs. The proposed framework consists of four steps: 1) perform a Redundancy Analysis (RDA) on the community data to identify the community structure response to environmental gradients; 2) conduct a kernel density analysis on the RDA biplot to determine the habitats; 3) use the indicator values analyses (IndVal) to select indicator species of each habitat; 4) run polynomial quantile regression analysis to find the optimum distribution of each indicator species. Such framework allows the determination of habitats based on the association of environmental and biological datasets, instead of relying solely on abiotic surrogates. As a case study, we used data of macro and meiofauna of a biodiverse coastal ecosystem in Southeast Brazil which is under anthropogenic pressure. Three main habitats were identified in the bay, and macro and meiofaunal assemblages were influenced by similar environmental variables. Nevertheless, macrofauna was more sensitive to changes in sediment composition, whereas meiofauna responded strongly to changes in total organic content and water depth. Macro- and meiofauna indicator taxa showed high specificity and fidelity values to each habitat, supporting their use in monitoring and conservation programs. The spatio-temporal organization of each habitat and the optimum distribution of each indicator species provide baseline knowledge to be used to monitor environmental changes in the study area and help in its conservation.
机译：栖息地和指示物种的定义是监测和保护计划的前提。但是，鉴于海洋的软底环境的时空动态和明显的同​​质性，如何定义栖息地是一项挑战。鉴于通常在底栖生物群落中出现的偶然物种数量众多，指示物种的选择也很复杂。这项研究的目的是基于成熟的分析方法，拟定一个框架，以识别软底生境并选择指标物种以支持监测和保护计划。提议的框架包括四个步骤：1）对社区数据执行冗余分析（RDA），以识别社区结构对环境梯度的响应； 2）在RDA双图上进行核仁密度分析以确定栖息地； 3）使用指标值分析（IndVal）选择每个栖息地的指标种类； 4）运行多项式分位数回归分析，以找到每种指标种类的最佳分布。这样的框架允许基于环境和生物数据集的关联来确定栖息地，而不是仅仅依靠非生物替代物。作为案例研究，我们使用了人为压力下巴西东南部生物多样性沿海生态系统的宏观和小型动物数据。在海湾中确定了三个主要的栖息地，并且相似的环境变量影响了宏观和半植物的组合。然而，大型动物对沉积物组成的变化更为敏感，而小型动物对总有机物含量和水深的变化反应强烈。大型和中型动物指标类群对每个生境显示出很高的特异性和保真度值，支持它们在监测和保护计划中的使用。每个栖息地的时空组织和每种指示剂物种的最佳分布提供了基准知识，可用于监测研究区域的环境变化并帮助保护该区域。

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