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非对称社区的抽样理论。

A sampling theory for asymmetric communities.

机构信息

Department of Biology, University of Maryland, College Park, MD 20742, USA.

出版信息

J Theor Biol. 2011 Mar 21;273(1):1-14. doi: 10.1016/j.jtbi.2010.12.021. Epub 2010 Dec 21.

DOI:10.1016/j.jtbi.2010.12.021
PMID:21182847
Abstract

We introduce the first analytical model of asymmetric community dynamics to yield Hubbell's neutral theory in the limit of functional equivalence among all species. Our focus centers on an asymmetric extension of Hubbell's local community dynamics, while an analogous extension of Hubbell's metacommunity dynamics is deferred to an appendix. We find that mass-effects may facilitate coexistence in asymmetric local communities and generate unimodal species abundance distributions indistinguishable from those of symmetric communities. Multiple modes, however, only arise from asymmetric processes and provide a strong indication of non-neutral dynamics. Although the exact stationary distributions of fully asymmetric communities must be calculated numerically, we derive approximate sampling distributions for the general case and for nearly neutral communities where symmetry is broken by a single species distinct from all others in ecological fitness and dispersal ability. In the latter case, our approximate distributions are fully normalized, and novel asymptotic expansions of the required hypergeometric functions are provided to make evaluations tractable for large communities. Employing these results in a bayesian analysis may provide a novel statistical test to assess the consistency of species abundance data with the neutral hypothesis.

摘要

我们介绍了第一个不对称社区动态的分析模型,该模型在所有物种之间具有功能等效性的极限下产生了 Hubbell 的中性理论。我们的关注点集中在 Hubbell 的局部社区动态的不对称扩展上,而 Hubbell 的后生境动态的类似扩展则被推迟到附录中。我们发现,质量效应可能有助于不对称局部社区中的共存,并产生与对称社区无法区分的单峰物种丰度分布。然而,多个模式仅源自不对称过程,并强烈表明存在非中性动态。尽管完全不对称社区的精确稳定分布必须通过数值计算得出,但我们为一般情况和近似中性社区(其中通过单个物种打破对称性,该物种在生态适应性和扩散能力方面与所有其他物种都不同)推导出了近似抽样分布。在后一种情况下,我们的近似分布是完全归一化的,并且提供了所需超几何函数的新颖渐近展开式,以便为大型社区的评估提供可处理性。在贝叶斯分析中使用这些结果可能为评估物种丰度数据与中性假设的一致性提供一种新的统计检验方法。

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