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首页> 外文期刊>Marine biology >Predicting zooplankton response to environmental changes in a temperate estuarine ecosystem
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Predicting zooplankton response to environmental changes in a temperate estuarine ecosystem

机译：预测温带河口生态系统中浮游动物对环境变化的响应

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A novel strategy that allows to predict the responses of zooplanktonic species to environmental conditions in an estuarine temperate ecosystem (Mondego estuary) is presented. It uses 12 indicator species from the zooplanktonic Mondego database (102 species) that are common members of the different habitats, characterized by their specific hydrological conditions. Indicator-species analysis (ISA) was used to define and describe which species were typical of each of the five sampling stations in a 4-year study (2003-2006). First, a canonical correspondence analysis (CCA) was carried out to objectively identify the species-habitat affinity based on the relationship between species, stations and environmental data. Response curves for each of the zooplanktonic species, generated by univariate logistic regression on each of the independent variables temperature and salinity, were generally in agreement with the descriptive statistics concerning the occurrence of those species in this particular estuarine ecosystem. Species-specific models that predict probability of occurrence relative to environmental parameters like salinity, water temperature, turbidity, chlorophyll a, total suspended solids and dissolved oxygen were then developed for the zooplanktonic species. The multiple logistic models used contained between 1 and 3 significant parameters and the percentage correctly predicted was moderate to high, ranging from 62 to 95%. The predictive accuracy of the model was assured by direct comparison of model predictions with the observed occurrence of species obtained in 2006 (validation) and from data collected in the early 2000s in another Portuguese estuary-Ria de Aveiro (Ganal de Mira), a complex mesotidal shallow coastal lagoon. The regression logistic model here defined, correctly suggested that the distribution of zooplankton species was mainly dependent on salinity and water temperature. The logistic regression proved to be a useful approach for predicting the occurrence of species under varying environmental conditions at a local scale. Therefore, this model can be considered of reasonable application (and should be tested in other estuarine systems) due to its ability to predict the occurrence of individual zooplanktonic species associated with habitat changes.
机译：提出了一种新颖的策略，可以预测河口温带生态系统（蒙德戈河口）中浮游动物对环境条件的响应。它使用了来自浮游动物世界数据库的12种指示剂物种（102种），它们是不同生境的共同成员，其特征在于特定的水文条件。在四年的研究中（2003-2006年），使用指标物种分析（ISA）来定义和描述五个采样站中每个采样站的典型物种。首先，进行了典型对应分析（CCA），以根据物种，站点和环境数据之间的关系客观地确定物种-栖息地的亲和力。通过对每个自变量温度和盐度进行单变量logistic回归生成的每个浮游动物物种的响应曲线通常与关于在该特定河口生态系统中这些物种的发生的描述性统计数据一致。然后为浮游动物建立了特定物种模型，该模型可预测相对于环境参数（如盐度，水温，浊度，叶绿素a，总悬浮固体和溶解氧）的发生概率。所使用的多个逻辑模型包含1到3个重要参数，正确预测的百分比为中等到很高，范围从62％到95％。通过将模型预测与2006年获得的物种（验证）和2000年代初在另一个葡萄牙河口Ria de Aveiro（Ganal de Mira）收集的数据进行直接观察比较，可以确保模型的预测准确性。中生的浅沿海泻湖。这里定义的回归逻辑模型正确地表明，浮游动物种类的分布主要取决于盐度和水温。 Logistic回归被证明是预测局部环境中各种环境条件下物种发生的有用方法。因此，由于该模型能够预测与栖息地变化相关的单个浮游动物物种的发生，因此可以认为该模型是合理应用的模型（应在其他河口系统中进行测试）。

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