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群落水平上物种的相关分布可以与尺度无关,并且与多度的均匀性有关。

Community-level species' correlated distribution can be scale-independent and related to the evenness of abundance.

机构信息

CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.

Institute of Statistics & Department of Applied Mathematics, National Chung Hsing University, 250 Kuo Kuang Road, Taichung, 40227, Taiwan.

出版信息

Ecology. 2018 Dec;99(12):2787-2800. doi: 10.1002/ecy.2544. Epub 2018 Nov 16.

Abstract

The spatial distribution of species is not random; instead, individuals tend to gather, resulting in a non-random pattern. Previous studies used the independent negative binomial distribution (NBD) to model the distributional aggregation of a single species, in which the independence of the distribution of individuals of a species in different quadrats had been assumed. This way of analyzing aggregation will result in the scale-dependent estimation of the aggregation or shape parameter. However, because non-random (and therefore non-independent) distribution of individuals of a species in a finite area can be caused by either correlated or clumped distribution of individuals of a species between neighboring sites, an alternative model would assume that the distribution of individuals of a species over different sampling areas is multinomial. Here, we showed that, by assuming that regional species abundance followed a NBD while using a multinomial distribution to assign individuals of species in different non-overlapped sampling quadrats that are from a partition of the entire region (quantifying positive correlation or synchrony), the estimation of the shape parameter in this probabilistic model, which is the negative multinomial distribution (NMD), was scale-invariant (i.e., the estimated shape parameter is identical across different partitions of the study region). Accordingly, the estimation of the shape parameter was related to regional species distribution alone. This implied that, the shape parameter at the community level, using the NMD model, reflected the evenness of interspecific abundance. As a comparison, if the distribution of individuals of a single species followed independent NBDs as studied previously, the shape parameter would measure the evenness of intraspecific abundance (quantifying single-species' distributional aggregation). Moreover, our study highlighted the necessity for adjusting the model for the effects of unsampled species when studying community-level distributional patterns. Collectively, as long as a target area is partitioned into non-overlapping quadrats (no matter how their sizes vary), the proposed NMD model in this study, along with the independent NBDs model, can be jointly formulated as a framework to reconcile the scale-dependent debate on the shape parameter, unifying the relationship between inter- or intraspecific abundance and distributional patterns.

摘要

物种的空间分布并非随机,而是倾向于聚集,从而呈现出非随机的模式。先前的研究使用独立负二项分布(NBD)来对单一物种的分布聚集进行建模,其中假定在不同样方中个体的分布是独立的。这种聚集的分析方法会导致聚集或形状参数的尺度依赖性估计。然而,由于在有限区域内的物种个体的非随机(因此非独立)分布可能是由相邻站点之间的物种个体的相关或聚集分布引起的,因此替代模型会假定物种个体在不同采样区域的分布是多项分布。在这里,我们表明,通过假设区域物种丰度遵循 NBD,同时使用多项分布来分配来自整个区域分区的不同不重叠采样样方中的物种个体(量化正相关或同步性),这种概率模型中的形状参数的估计是尺度不变的(即,在研究区域的不同分区中估计的形状参数是相同的)。因此,形状参数的估计仅与区域物种分布有关。这意味着,使用 NMD 模型,群落水平的形状参数反映了种间丰度的均匀度。相比之下,如果如先前研究中那样,单个物种的个体分布遵循独立的 NBD,那么形状参数将衡量种内丰度的均匀度(量化单一种群的分布聚集)。此外,我们的研究强调了在研究群落水平分布模式时,需要调整模型以适应未采样物种的影响。总之,只要目标区域被划分为不重叠的样方(无论其大小如何变化),本研究中提出的 NMD 模型以及独立的 NBD 模型都可以共同制定一个框架,以协调关于形状参数的尺度依赖性争议,统一种间或种内丰度与分布模式之间的关系。

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