The research I will be presenting focuses on identifying signatures of niche assembly in patterns of community structure in cases where transient regimes are important. Existing indices of community assembly processes have met with limited success in demonstrating niche partitioning in real-world communities. Such metrics concentrate on equilibria of a deterministic niche axis model, where coexisting species are expected to disperse evenly along niche axes, in a pattern generally called limiting similarity. One possible reason for the mixed results is that transient states may be more relevant in nature than commonly appreciated. The transient regime in MacArthur and Levins’ 1967 model has been shown in the recent literature to be characterized by clumps of similar species rather than limiting similarity. Additionally, our own recent work shows that these clumps created by transient dynamics are a persistent pattern in a stochastic version of the model with immigration. Further study is needed, however, to connect these theoretical developments with the empirical realm. In particular, we need metrics more fully reflective of patterns of species abundance and trait dispersion under niche assembly.
In this work, we combine patterns of species abundances and trait dispersion observed in simulations of a few different niche models to propose a test more powerful than alternative metrics to detect niche processes when stochasticity and transient regimes are important. The proposed new metric picks up on the periodicity in species abundances along the trait axis, thus capturing the presence of both clumping of species (niches) and structure within the clumps. It is therefore more reflective of the pattern associated with transient dynamics than other metrics created with the equilibria of deterministic niche models in mind, such as the coefficient of variation among nearest-neighbor trait distances.