Translucent windows: How uncertainty in competitive interactions impacts detection of community pattern

TL;DR

This paper investigates how uncertainty and incomplete knowledge of species traits affect the detection of community clustering patterns driven by competition, emphasizing the importance of trait-niche linkage for accurate inference.

Contribution

It demonstrates that community clustering patterns are robust to unobserved niche axes but require traits to be good proxies for niches to be detectable.

Findings

Clustering patterns persist despite unknown niche axes.

Detection depends on traits being close proxies for niches.

Patterns can inform about competition if traits are well linked to niches.

Abstract

Trait variation and similarity among coexisting species can provide a window into the mechanisms that maintain their coexistence. Recent theoretical explorations suggest that competitive interactions will lead to groups, or clusters, of species with similar traits. However, theoretical predictions typically assume complete knowledge of the map between competition and measured traits. These assumptions limit the plausible application of these patterns for inferring competitive interactions in nature. Here we relax these restrictions and find that the clustering pattern is robust to contributions of unknown or unobserved niche axes. However, it may not be visible unless measured traits are close proxies for niche strategies. We conclude that patterns along single niche axes may reveal properties of interspecific competition in nature, but detecting these patterns requires natural history expertise firmly tying traits to niches.