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首页> 外文期刊>Journal of Vegetation Science >Measuring and interpreting trait-based selection versus meta-community effects during local community assembly.
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Measuring and interpreting trait-based selection versus meta-community effects during local community assembly.

机译:在当地社区集会期间测量和解释基于特征的选择与元社区的影响。

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Questions: (1) How can one quantify the relative importance of meta-community processes related to immigration, local trait-based habitat filtering, and demographic stochasticity using the Community Assembly by Trait Selection (CATS) model in a general context? (2) How can this generalization be used to detect different strengths and directions in trait selection at the meta-community and local community levels? Methods: I describe a decomposition of the deviance between observed and predicted relative abundances based on a maximum entropy model including a meta-community prior (CATS) and generalize a previous decomposition of relative abundance using this model; corrections to avoid negative explained proportions of deviance are presented. Simulations of community assembly are used to explore its properties and elucidate its interpretation. In particular, this method quantifies the proportion of the total deviance between observed and predicted relative abundances attributed to: (1) pure trait-based local selection, (2) dispersal mass effect from the meta-community, (3) joint contributions of (1) and (2) that cannot be separated; and (4) residual deviance due to demographic stochasticity. Results and Conclusions: The previous decomposition, while giving correct values in that particular data set, requires modification in order to avoid nonsensical negative values. When the modifications described in this paper are made, the decomposition provides correct values. Furthermore, positive or negative values of the joint composition inform us of the importance and direction of correlations between local trait-based selection and processes occurring in the larger meta-community.
机译:问题:(1)在一般情况下,如何使用按特质选择的社区集结(CATS)模型来量化与移民,基于局部特征的生境过滤和人口统计随机性相关的元社区过程的相对重要性? (2)如何在元社区和地方社区层面上使用这种概括来检测性状选择的不同优势和方向?方法:我基于最大熵模型(包括元社区先验(CATS))描述了观测到的相对丰度和预测的相对丰度之间的偏差分解,并使用该模型归纳了相对丰度的先前分解;为避免负面解释的偏差比例提出了一些更正。社区集会的模拟被用来探索其性质并阐明其解释。尤其是,此方法量化了观测到的和预测的相对丰度之间总偏差的比例,这些偏差归因于:(1)基于纯特征的局部选择;(2)来自元社区的弥散质量效应;(3)( 1)和(2)不可分开; (4)人口随机性造成的剩余偏差。结果和结论:先前的分解虽然在该特定数据集中提供了正确的值,但需要进行修改,以避免产生无意义的负值。进行本文所述的修改后,分解可提供正确的值。此外,关节组成的正值或负值使我们了解了基于局部特征的选择与大型社区中发生的过程之间的相关性的重要性和方向。

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