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强相互作用模型群落中稀有和丰富物种的混乱更替。

Chaotic turnover of rare and abundant species in a strongly interacting model community.

机构信息

Max Planck Institute for Evolutionary Biology, Department of Theoretical Biology, Plön 24306, Germany.

Institut de Biologie de l'ENS, Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université Paris Science & Lettres, Paris 75005, France.

出版信息

Proc Natl Acad Sci U S A. 2024 Mar 12;121(11):e2312822121. doi: 10.1073/pnas.2312822121. Epub 2024 Mar 4.

DOI:10.1073/pnas.2312822121
PMID:38437535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10945849/
Abstract

The composition of ecological communities varies not only between different locations but also in time. Understanding the fundamental processes that drive species toward rarity or abundance is crucial to assessing ecosystem resilience and adaptation to changing environmental conditions. In plankton communities in particular, large temporal fluctuations in species abundances have been associated with chaotic dynamics. On the other hand, microbial diversity is overwhelmingly sustained by a "rare biosphere" of species with very low abundances. We consider here the possibility that interactions within a species-rich community can relate both phenomena. We use a Lotka-Volterra model with weak immigration and strong, disordered, and mostly competitive interactions between hundreds of species to bridge single-species temporal fluctuations and abundance distribution patterns. We highlight a generic chaotic regime where a few species at a time achieve dominance but are continuously overturned by the invasion of formerly rare species. We derive a focal-species model that captures the intermittent boom-and-bust dynamics that every species undergoes. Although species cannot be treated as effectively uncorrelated in their abundances, the community's effect on a focal species can nonetheless be described by a time-correlated noise characterized by a few effective parameters that can be estimated from time series. The model predicts a nonunitary exponent of the power-law abundance decay, which varies weakly with ecological parameters, consistent with observation in marine protist communities. The chaotic turnover regime is thus poised to capture relevant ecological features of species-rich microbial communities.

摘要

生态群落的组成不仅在不同地点之间有所不同,而且随时间变化而变化。了解驱动物种变得稀有或丰富的基本过程对于评估生态系统的弹性和适应不断变化的环境条件至关重要。特别是在浮游生物群落中,物种丰度的大时间波动与混沌动力学有关。另一方面,微生物多样性主要由丰度非常低的“稀有生物界”物种维持。我们在这里考虑一个可能性,即物种丰富群落中的相互作用可以将这两种现象联系起来。我们使用带有弱移民和数百个物种之间强烈、无序和主要竞争相互作用的Lotka-Volterra 模型来弥合单一物种的时间波动和丰度分布模式。我们强调了一个通用的混沌状态,其中少数物种一次达到优势地位,但不断被以前稀有的物种入侵所推翻。我们推导出一个焦点物种模型,该模型捕获了每个物种经历的间歇性繁荣和萧条动态。尽管物种在丰度上不能被视为有效不相关,但群落对焦点物种的影响仍然可以通过几个有效参数来描述,这些参数可以通过时间序列来估计。该模型预测了幂律丰度衰减的非单位指数,该指数随生态参数的变化而微弱变化,与海洋原生动物群落的观测结果一致。因此,混沌转换状态有望捕获富含物种的微生物群落的相关生态特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/b725101e2bd9/pnas.2312822121fig07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/5b3b218d6713/pnas.2312822121fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/b4c0a1482d6c/pnas.2312822121fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/74684e0d568c/pnas.2312822121fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/55d0ac5abd96/pnas.2312822121fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/f06693c0acf9/pnas.2312822121fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/5c2d48aa46ed/pnas.2312822121fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/b725101e2bd9/pnas.2312822121fig07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/5b3b218d6713/pnas.2312822121fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/b4c0a1482d6c/pnas.2312822121fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/74684e0d568c/pnas.2312822121fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/55d0ac5abd96/pnas.2312822121fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/f06693c0acf9/pnas.2312822121fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/5c2d48aa46ed/pnas.2312822121fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b066/10945849/b725101e2bd9/pnas.2312822121fig07.jpg

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