Species coexistence as an emergent effect of interacting mechanisms.

IF 1.2 4区 生物学 Q4 ECOLOGY Theoretical Population Biology Pub Date : 2025-01-14 DOI:10.1016/j.tpb.2024.12.005
Thomas Seidelmann, Sanaz Mostaghim
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引用次数: 0

Abstract

Although extensively studied, the maintenance of biodiversity remains a highly debated and investigated topic of contemporary research in ecology. Several studies have quantified the contributions of various coexistence mechanisms to biodiversity. However, often stochastic individual-level interactions are abstracted away, or mechanisms are studied in isolation. The intertwined nature and reciprocal influences between mechanisms, as they arise from individual-level interactions, are therefore rarely considered. We propose a novel mechanistic simulation model grounded in neutral theory to capture and quantify emergent effects arising from such mechanism interactions. Three coexistence mechanisms are supported: storage effect, intransitivity, and resource partitioning. We show that basic neutral dynamics and related models of isolated mechanisms can be replicated. Beyond that, we observe difficult to predict, yet significant emergent effects for mechanism combinations. In some cases, coexistence times could be extended more than tenfold compared to the individual mechanisms performances. Our findings suggest that studies of individual coexistence mechanisms might be insufficient and indeed misleading for quantifying their overall impact on biodiversity. The particular combination of mechanisms and their interactions appear to be of vital importance.

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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
期刊最新文献
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