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Beyond neutrality: adding habitat filtering to neutral models
Ecological Processes ( IF 4.8 ) Pub Date : 2020-05-29 , DOI: 10.1186/s13717-020-00228-7
Wasana Abeysinghe , Ruwan Punchi-Manage

Understanding the processes that structure species is one of the primary focuses in community ecology. Hubbell’s neutral model shows stochastic processes alone can describe the two macro-ecological patterns, species richness and species-area relationship, of the community. Although Hubbell’s neutral model can explain the macro-ecological patterns of the species at large scales, it paid less attention to construct the spatial structure of the community. Previous studies suggest that such spatial structures are mostly due to habitat filtering processes work at the intermediate spatial scales. Therefore, Hubbell’s neutral model does not explain the full picture of the community structuring due to its fully stochastic nature. In this study, we proposed a two-schema model that has the habitat filtering component and the stochastic component to construct the species assemblages seen in the community level. The proposed model uses one additional parameter (i.e. number of individuals in habitat) in addition to Hubbell’s three-parameter neutral model (i.e. fundamental bio-diversity number (θ), dispersal limitation (m) and speciation (v)). The proposed model works at two spatial scales: habitat filtering at the intermediate scales and stochastic processes at the large and very small spatial scales. The model coupled the local community dynamics with the meta-community dynamics. The local community has a fixed area with carrying capacity that is proportional to the local community size. The number of habitats in the proposed model can vary. Individuals are placed into habitats with probabilities according to the habitat suitability. Species richness and species composition in each habitat were calculated. The model is fitted for different θ values, m values, and a different number of habitats. We assume that habitat filtering plays an important role together with stochastic processes to structure species in forests. Therefore, the proposed model with only four parameters can explain a large proportion of the species structuring of the communities. We found that more species can be maintained in a heterogeneous environment than a uniform environment. Therefore, habitat conservation is highly important for maintaining species diversity in forest communities.

中文翻译:

超越中立性:在中立模型中添加栖息地过滤功能

了解构成物种的过程是社区生态学的主要重点之一。Hubbell的中性模型表明,随机过程本身可以描述社区的两种宏观生态模式,即物种丰富度和物种-面积关系。尽管Hubbell的中性模型可以大规模地解释物种的宏观生态模式,但它对构建社区空间结构的关注却很少。先前的研究表明,这种空间结构主要是由于栖息地过滤过程在中间空间尺度上起作用。因此,Hubbell的中性模型由于具有完全的随机性而不能解释社区结构的全部情况。在这个研究中,我们提出了一种具有栖息地过滤组件和随机组件的两模式模型,以构建在社区水平上看到的物种集合。除了Hubbell的三参数中立模型(即基本生物多样性数(θ),扩散限制(m)和物种形成(v))之外,该模型还使用了一个额外的参数(即栖息地中的个体数量)。所提出的模型在两个空间尺度上起作用:中等尺度上的栖息地过滤和大和非常小的空间尺度上的随机过程。该模型将本地社区动态与元社区动态结合在一起。当地社区的固定区域承载能力与当地社区规模成正比。提议的模型中的栖息地数量可以变化。根据栖息地的适宜性,将个体置于具有概率的栖息地中。计算了每个栖息地的物种丰富度和物种组成。该模型适用于不同的θ值,m值和不同数量的栖息地。我们假设栖息地过滤和随机过程在构造森林物种中起着重要作用。因此,所提出的仅具有四个参数的模型可以解释社区中物种构成的很大一部分。我们发现,在异质环境中可以维持的物种比统一环境还多。因此,栖息地保护对于维持森林群落物种多样性至关重要。该模型适用于不同的θ值,m值和不同数量的栖息地。我们假设栖息地过滤和随机过程在构造森林物种中起着重要作用。因此,所提出的仅具有四个参数的模型可以解释社区中物种构成的很大一部分。我们发现,在异质环境中可以维持的物种比统一环境还多。因此,栖息地保护对于维持森林群落物种多样性至关重要。该模型适用于不同的θ值,m值和不同数量的栖息地。我们假设栖息地过滤和随机过程在构造森林物种中起着重要作用。因此,所提出的仅具有四个参数的模型可以解释社区中物种构成的很大一部分。我们发现,在异质环境中可以维持的物种比统一环境还多。因此,栖息地保护对于维持森林群落物种多样性至关重要。所提出的仅具有四个参数的模型可以解释群落的大部分物种结构。我们发现,在异质环境中可以维持的物种比统一环境还多。因此,栖息地保护对于维持森林社区的物种多样性至关重要。所提出的仅具有四个参数的模型可以解释群落的大部分物种结构。我们发现,在异质环境中可以维持的物种比统一环境还多。因此,栖息地保护对于维持森林群落物种多样性至关重要。
更新日期:2020-05-29
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