期刊
ROYAL SOCIETY OPEN SCIENCE
卷 10, 期 8, 页码 -出版社
ROYAL SOC
DOI: 10.1098/rsos.230222
关键词
competition field; competitive response; game theory; mean-field game model; multiplayer competition; suppression field
Competition theory suggests that individuals benefit from harming their competitors, but when multiple individuals compete, the effects of competition become complex and may have indirect consequences. Diffuse competition, where interactions occur among multiple competitors rather than just pairwise interactions, is likely the dominant mode of interaction. This type of competition can result in fitness costs, especially when kin-kin interactions are common.
Competition theory is founded on the premise that individuals benefit from harming their competitors, which helps them secure resources and prevent inhibition by neighbours. When multiple individuals compete, however, competition has complex indirect effects that reverberate through competitive neighbourhoods. The consequences of such 'diffuse' competition are poorly understood. For example, competitive effects may dilute as they propagate through a neighbourhood, weakening benefits of neighbour suppression. Another possibility is that competitive effects may rebound on strong competitors, as their inhibitory effects on their neighbours benefit other competitors in the community. Diffuse competition is unintuitive in part because we lack a clear conceptual framework for understanding how individual interactions manifest in communities of multiple competitors. Here, I use mathematical and agent-based models to illustrate that diffuse interactions-as opposed to direct pairwise interactions-are probably the dominant mode of interaction among multiple competitors. Consequently, competitive effects may regularly rebound, incurring fitness costs under certain conditions, especially when kin-kin interactions are common. These models provide a powerful framework for investigating competitive ability and its evolution and produce clear predictions in ecologically realistic scenarios.
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