The shape of terrestrial abundance distributions

The shape of terrestrial abundance distributions
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DOI:
10.1126/sciadv.1500082
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发表时间:
2015-09-01
期刊:
影响因子:
13.6
通讯作者:
Alroy, John
Alroy, John
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Alroy, John

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生态学家普遍认为,大多数群落的丰度分布相当平坦,但主要由少数物种主导。其原因是物种丰度被认为遵循某些预测这种模式的理论分布。然而,以前的研究要么集中在一些理论分布,要么集中在一些经验分布。我展示了 1055 个树木、蝙蝠、小型陆地哺乳动物、鸟类、蜥蜴、青蛙、蚂蚁、粪甲虫、蝴蝶和臭虫样本的丰度模式。根据最大似然相关的 Kullback-Leibler 散度统计,现有的五种理论分布对最常见物种和平均物种的频率做出了不准确的预测,并且大多数与整体模式的拟合效果很差。相反,数据支持此处称为“双几何”的低主导分布。根据其两个控制参数的值,它可能类似于几何级数分布或对数正态级数分布。然而,与任何其他模型不同,它假设丰富度是有限的,并且物种在二维生态位景观中对资源的竞争不平等,这意味着生态位宽度是可变的,并且性状分布既不是沿单一维度排列也不是随机关联的。生态位空间是多维的这一假设有助于解释众多物种如何在相互作用强烈的情况下共存。
Ecologists widely accept that the distribution of abundances in most communities is fairly flat but heavily dominated by a few species. The reason for this is that species abundances are thought to follow certain theoretical distributions that predict such a pattern. However, previous studies have focused on either a fewtheoretical distributions or a few empirical distributions. I illustrate abundance patterns in 1055 samples of trees, bats, small terrestrial mammals, birds, lizards, frogs, ants, dung beetles, butterflies, and odonates. Five existing theoretical distributions make inaccurate predictions about the frequencies of the most common species and of the average species, and most of them fit the overall patterns poorly, according to the maximum likelihood-related Kullback-Leibler divergence statistic. Instead, the data support a low-dominance distribution here called the " double geometric." Depending on the value of its two governing parameters, it may resemble either the geometric series distribution or the lognormal series distribution. However, unlike any other model, it assumes both that richness is finite and that species compete unequally for resources in a two-dimensional niche landscape, which implies that niche breadths are variable and that trait distributions are neither arrayed along a single dimension nor randomly associated. The hypothesis that niche space is multidimensional helps to explain how numerous species can coexist despite interacting strongly.