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Deconstructing richness patterns by commonness and rarity reveals bioclimatic and spatial effects in black fly metacommunities

机译:通过共性和稀有性解构丰富性模式揭示了黑蝇元社区的生物气候和空间效应

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摘要

Deconstructing biological communities by grouping species according to their commonness or rarity might improve our understanding about the processes driving variation in biological communities. Such an approach considers differences among organisms and emergent ecological patterns. In this study, we addressed the relative role of spatial and large-scale bioclimatic variables along a commonness and rarity gradient using Simuliidae (Diptera) species richness. A database of species occurrences at 459 locations in Brazil was used to estimate the distribution of 58 simuliid species. Total species richness at each location was estimated first using all occurrences and then by removing one species at a time, following a commonest to rarest gradient (CtR) and vice-versa (RtC). Partial regression analysis was used to test the influence of sets of bioclimatic (E) and spatial (S) variables for Simuliidae species richness across both CtR and RtC gradients. In the CtR gradient, the pure spatial component alone explained between 40% and 60% of the variation in simuliid richness when the total number of species was greater than 35. After removal of the 35th most common species, the model fit decreased sharply reaching nearly zero when only rare species were present. Variation explained by the shared component E+S decreased continuously along the CtR gradient. The relative role of predictor variables on the RtC gradient was similar to CtR gradient. However, removing the rare species first did not change which components best explained species richness. Our gradual deconstructive approach revealed that common species contribute more to species richness variation than rare species, and that the role of predictors in explaining this pattern cannot be untangled by analysing richness of rare and common species in a categorical way.
机译:通过根据物种的共性或稀有性对物种进行分组来解构生物群落可能会增进我们对驱动生物群落变异的过程的理解。这种方法考虑了生物之间的差异和新出现的生态模式。在这项研究中,我们利用Simuliidae(Diptera)物种丰富度,探讨了沿共同性和稀有性梯度的空间和大规模生物气候变量的相对作用。利用巴西459个地点的物种发生数据库,估算了58种类似物种的分布。首先使用所有事件的出现来估计每个位置的总物种丰富度,然后按照从最常见到最稀有的梯度(CtR)以及一次从相反的顺序(RtC)一次去除一个物种来估算。使用部分回归分析来测试生物气候(E)和空间(S)变量集对跨CtR和RtC梯度的Simuliidae物种丰富度的影响。在CtR梯度中,当物种总数大于35时,仅单纯的空间成分可以解释类比丰富度变化的40%至60%。去除第35个最常见的物种后,模型拟合急剧下降,几乎达到仅存在稀有物种时为零。共享分量E + S解释的变化沿CtR梯度连续减小。预测变量在RtC梯度上的相对作用类似于CtR梯度。但是,首先去除稀有物种并没有改变哪种成分最能解释物种丰富度。我们的逐步解构方法显示,普通物种比稀有物种对物种丰富度变化的贡献更大,并且通过分类地分析稀有和常见物种的丰富度,不能弄清预测因子在解释这种模式中的作用。

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