Challenges in linking trait patterns to niche differentiation

Abstract

Among approaches to establish the importance of niche differentiation for species coexistence, the use of functional traits is attractive for its potential to suggest specific coexistence mechanisms. Recent studies have looked for trait patterns reflective of niche differentiation, building on a line of research with a deep but somewhat neglected history. We review the field from its foundation in limiting similarity theory in the 1960s to its resurgence in 2000s, and find the theory of trait patterning still in a stage of development. Elements still to be accounted for include environmental fluctuations, multidimensional niche space, transient dynamics, immigration, intraspecific variation, evolution and spatial scales. Recent empirical methods are better than early approaches, but still focus on patterning arising in simplistic models, and should rigorously link niche space with trait space, use informative null models, and adopt new metrics of pattern as theory develops. Because tests based on overly simplistic expectations of trait pattern are of little value, we argue that progress in the field requires theory development, which should entail exploring patterns across a set of conceptual and system‐specific models of competition along trait axes.

Disentangling the processes driving plant assemblages in mountain grasslands across spatial scales and environmental gradients

“…Therefore, the convergence of traits at the community level may also be driven by the exclusion of weaker competitors by the stronger ones (Bengtsson, Fagerstrom, & Rydin, ; Chesson, ; Kunstler et al, ; Mayfield & Levine, ). However, when plant competition is at work, the coexistence of species can be empowered by mechanisms that counteract competitive exclusion (Barot & Gignoux, ; Chesson, ; Wilson, ): Opposite to the trait convergence caused by habitat filtering, trait divergence results from the fact that species must differentiate to compete for different resources (corresponding to different α ‐niche attributes; Stubbs & Wilson, ; Wilson & Stubbs, ), usually resulting in a range of distinct traits in the community (D'Andrea & Ostling, ; Johansson & Keddy, ; MacArthur & Levins, ; Wilson, ). Such trait divergence is therefore expected to limit the trait similarity of coexisting species through α ‐niche differentiation (Götzenberger et al, ; Wilson, ).…”

Biodiversity maintenance may be lower under partial niche differentiation than under neutrality

“…S4–S6, S8), and indeed has received attention in the recent literature on niche dynamics (Holt , Scheffer and van Nes , Fort et al. , , Pigolotti and Cencini , D'Andrea and Ostling ). We verified in our simulations that if immigration is turned off, the clusters eventually disappear, and one species remains per each cluster.…”

Sensitivity of functional diversity metrics to sampling intensity

“…the number of species), Shannon species diversity, a metric increasing with both more species and a higher evenness in abundances, Pielou's evenness, a metric measuring the evenness in species’ abundances (Magurran ), Functional Richness, quantifying the multidimensional trait space species occupy, Functional ‐, quantifying the average distance of the species from the centroid in trait space, Functional Evenness, a metric quantifying how even individuals from a community are distributed over trait space (Villéger, Mason & Mouillot ), functional dispersion (Laliberté & Legendre ) and Rao's quadratic entropy (Rao ; Botta‐Dukát ), two metrics quantifying (albeit with subtle differences) the average deviation of individuals from a trait mean, Trait Range, the highest minus lowest trait value (Stubbs & Wilson ) and Mean, minimal and standard deviation of nearest neighbour distances (NND) (Stubbs & Wilson ). The NND metrics can be quantified using multiple traits, but in this study we based it on a single trait, as this reflects the most common practice in other studies (D'Andrea & Ostling ). For the key characteristics of these diversity metrics, see Table .…”