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Empirical realised niche models for British coastal plant species

机译:英国沿海植物物种的经验实现利基模型

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摘要

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels.
机译:沿海环境拥有适应各种盐度条件的植物分类单元。盐度以及其他非生物变量以可预测的方式限制了沿海植物的分布,而适应大多数盐分条件的分类单元却相对较少。但是,几乎没有尝试量化这些关系以创建沿海植物的利基模型。盐度和其他非生物变量对沿海植物的影响的量化对于预测沿海生态系统对外部驱动程序(例如海平面上升)的响应至关重要。我们基于八个非生物变量为英国的132个沿海植物分类群构建了利基模型。在沿海生境中很少有植被组成和非生物变量的成对测量,因此使用Ellenberg指标的群落平均值定义了四个变量,即根据典型物种的发生地点的典型碱度,肥力,水分利用度和盐度分配的分数。其余变量是树冠高度,年降水量以及最高和最低温度。在超过80%的模型中,盐度和湿度指标得分是重要的术语,这表明大多数沿海物种的分布至少部分地由这些变量决定。当使用该模型针对独立数据集预测物种发生时,有64%的模型对物种发生的预测为中度到良好。这表明大多数模型已成功捕获了利基市场的关键决定因素。该模型可潜在地用于预测响应海平面上升而对生境和物种依赖性生态系统服务的变化。

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