Matrix models for quantifying competitive intransitivity.

Assessing the relative importance of intransitive competition networks in nature has been difficult because it requires a large number of pairwise competition experiments linked to observed field abundances of interacting species. Here we introduce metrics and statistical tests for evaluating the contribution of intransitivity to community structure using two kinds of data: competition matrices derived from the outcomes of pairwise experimental studies (C matrices) and species abundance matrices. We use C matrices to develop patch transition matrices (P) that predict community structure in a simple Markov chain model. We propose a randomization test to evaluate the degree of intransitivity from these P matrices in combination with empirical or simulated C matrices. Benchmark tests revealed that the methods could correctly detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. These tests represent the first tools for estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to both spatio-temporal data sampled in homogeneous environments or across environmental gradients, and to experimental measures of pairwise interactions. To illustrate the methods, we analyzed empirical data matrices on the colonization of slug carrion by necrophagous flies and their parasitoids.