Physics Department, Bar-Ilan University, Ramat-Gan, Israel.
Department of Plant Pathology and Microbiology, The Hebrew University of Jerusalem, Rehovot, Israel.
Nat Ecol Evol. 2022 Jun;6(6):693-700. doi: 10.1038/s41559-022-01745-8. Epub 2022 Apr 28.
May's stability theory, which holds that large ecosystems can be stable up to a critical level of complexity, a product of the number of resident species and the intensity of their interactions, has been a central paradigm in theoretical ecology. So far, however, empirically demonstrating this theory in real ecological systems has been a long-standing challenge with inconsistent results. Especially, it is unknown whether this theory is pertinent in the rich and complex communities of natural microbiomes, mainly due to the challenge of reliably reconstructing such large ecological interaction networks. Here we introduce a computational framework for estimating an ecosystem's complexity without relying on a priori knowledge of its underlying interaction network. By applying this method to human-associated microbial communities from different body sites and sponge-associated microbial communities from different geographical locations, we found that in both cases the communities display a pronounced trade-off between the number of species and their effective connectance. These results suggest that natural microbiomes are shaped by stability constraints, which limit their complexity.
梅的稳定性理论认为，大型生态系统在达到一定复杂度水平时可以保持稳定，这是驻留物种数量及其相互作用强度的产物，这一理论一直是理论生态学的核心范例。然而，到目前为止，在真实生态系统中实证验证这一理论一直是一个长期存在的挑战，其结果并不一致。特别是，由于可靠地重建如此庞大的生态相互作用网络的挑战，该理论是否适用于自然微生物组丰富而复杂的群落尚不清楚。在这里，我们引入了一种无需依赖其底层相互作用网络先验知识即可估计生态系统复杂性的计算框架。通过将该方法应用于来自不同身体部位的人类相关微生物群落和来自不同地理位置的海绵相关微生物群落，我们发现，在这两种情况下，群落的物种数量和有效连接度之间都存在明显的权衡。这些结果表明，自然微生物组受到稳定性约束的影响，这限制了它们的复杂性。
