Predicting niche overlap with model-based ordination

The ecological niche is a fundamental concept in ecology that can be used in order better understand species relationships. The overlap in species niches provides a measure of the likelihood for species to co-occur. Most approaches that quantify niche overlap have been based on distance and similarity indices, for pairwise combinations of species. In this paper, we suggest that niche overlap can be calculated from the predictions of a model. Using a statistical model to predict niche overlap provides various benefits, includes the possibility to adjust the model to properties of the data. We demonstrate this using an example dataset of an ecological community of Foraminifera species, to which we fit a generalized linear latent variable model (GLLVM). GLLVMs are a flexible class of models that allow to estimate the distribution of species using both measured environmental predictors and residual covariation between species. We demonstrate how to calculate niche overlap from GLLVMs for any combination of species, and separately for different environments. Predicting niche overlap from a model further expands the toolset available to ecologists for the exploration of species co-occurrence patterns.