Abstract
Abstract It is common practice for ecologists to examine species niches in the study of community composition. The response curve of a species in the fundamental niche is usually assumed to be quadratic. The centre of a quadratic curve represents a species' optimal environmental conditions, and the width its ability to tolerate deviations from the optimum. Most multivariate methods assume species respond linearly to niche axes, or with a quadratic curve that is of equal width for all species. However, it is widely understood that some species have the ability to better tolerate deviations from their optimal environment (generalists) compared to other (specialist) species. Rare species often tolerate a smaller range of environments than more common species, corresponding to a narrow niche. We propose a new method, for ordination and fitting Joint Species Distribution Models, based on Generalized Linear Mixed‐effects Models, which relaxes the assumptions of equal tolerances. By explicitly estimating species maxima, and species optima and tolerances per ecological gradient, we can better explore how species relate to each other.
Highlights
One of the key topics addressed by community ecology is the exploration of community composition
Latent variables can be understood as combinations of missing predictors, so that Generalized Linear Latent Variable Models (GLLVMs) allow us to parsimoniously model species distributions
We considered a GLLVM with quadratic response model and d = 2 latent variables, which was constructed as follows
Summary
One of the key topics addressed by community ecology is the exploration of community composition. Species communities are surveyed at locations along environmental gradients. The ecological niche is reflected in the observed distribution of a species. A species exhibits its maximum abundance, or has the highest probability of occurrence, at the optimum of the niche. The limits of a species distribution correspond to the limits of the niche, controlled by a species' tolerance to a range of environmental conditions. Different species vary in their ability to tolerate deviations from the optimum, reflecting differences in niche width, and indicating different places on the specialist–generalist spectrum
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