Gao Yingnan, Abdullah Ahmed, Wu Martin
Department of Biology, University of Virginia, Charlottesville, VA, USA.
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Nat Commun. 2025 Apr 29;16(1):4035. doi: 10.1038/s41467-025-59253-9.
Remarkably, almost every ecological community investigated to date is composed of many rare species and a few abundant species. While the precise nature of this species abundance distribution is believed to reflect fundamental ecological principles underlying community assembly, ecologists have yet to identify a single model that comprehensively explains all species abundance distributions. Recent studies using large datasets have suggested that the logseries distribution best describes animal and plant communities, while the Poisson lognormal distribution is the best model for microbes, thereby challenging the notion of a unifying species abundance distribution model across the tree of life. Here, using a large dataset of ~30,000 globally distributed communities spanning animals, plants and microbes from diverse environments, we show that the powerbend distribution, predicted by a maximum information entropy-based theory of ecology, emerges as a unifying model that accurately captures species abundance distributions of all life forms, habitats and abundance scales. Our findings challenge the notion of pure neutrality, suggesting instead that community assembly is driven by a combination of random fluctuations and deterministic mechanisms shaped by interspecific trait variation.
值得注意的是，迄今为止几乎所有被研究的生态群落都是由许多稀有物种和少数优势物种组成的。虽然人们认为这种物种丰度分布的确切性质反映了群落组装背后的基本生态原理，但生态学家尚未找到一个能全面解释所有物种丰度分布的单一模型。最近使用大型数据集的研究表明，对数级数分布最能描述动植物群落，而泊松对数正态分布是微生物的最佳模型，从而挑战了在整个生命之树上存在统一的物种丰度分布模型这一概念。在这里，我们使用一个包含约30000个全球分布群落的大型数据集，这些群落涵盖了来自不同环境的动物、植物和微生物，我们发现由基于最大信息熵的生态学理论预测的幂弯分布，作为一个统一模型出现，它能准确捕捉所有生命形式、栖息地和丰度尺度下的物种丰度分布。我们的发现挑战了纯粹中性的概念，相反表明群落组装是由随机波动和由种间性状变异塑造的确定性机制共同驱动的。
