Hovstad, K. A. | Search bioRxiv

bioRxiv2021

Model-based ordination with constrained latent variables

O_LIIn community ecology, unconstrained ordination can be used to indirectly explore drivers of community composition, while constrained ordination can be used to directly relate predictors to an ecological community. However, existing constrained ordination methods do not explicitly account for community composition that cannot be explained by the predictors, so that they have the potential to misrepresent community composition if not all predictors are available in the data. C_LIO_LIWe propose and develop a set of new methods for ordination and Joint Species Distribution Modelling (JSDM) as part of the Generalized Linear Latent Variable Model (GLLVM) framework, that incorporate predictors directly into an ordination. This includes a new ordination method that we refer to as concurrent ordination, as it simultaneously constructs unconstrained and constrained latent variables. Both unmeasured residual covariation and predictors are incorporated into the ordination by simultaneously imposing reduced rank structures on the residual covariance matrix and on fixed-effects. C_LIO_LIWe evaluate the method with a simulation study, and show that the proposed developments outperform Canonical Correspondence Analysis (CCA) for Poisson and Bernoulli responses, and perform similar to Redundancy Analysis (RDA) for normally distributed responses, the two most popular methods for constrained ordination in community ecology. Two examples with real data further demonstrate the benefits of concurrent ordination, and the need to account for residual covariation in the analysis of multivariate data. C_LIO_LIThis article contextualizes the role of constrained ordination in the GLLVM and JSDM frameworks, while developing a new ordination method that incorporates the best of unconstrained and constrained ordination, and which overcomes some of the deficiencies of existing classical ordination methods. C_LI

ecology↗

bioRxiv2020

Model-based ordination for species with unequal niche widths

O_LIIt 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 center of a quadratic curve represents a species optimal environmental conditions, and the width its ability to tolerate deviations from the optimum. C_LIO_LIMost multivariate methods assume species respond linearly to the environment of the niche, or with a quadratic curve that is of equal width and height for all species. However, it is widely understood that some species are generalists who tolerate deviations from their optimal environment better than others. Rare species often tolerate a smaller range of environments than more common species, corresponding to a narrow niche. C_LIO_LIWe 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 and equal maxima. C_LIO_LIBy explicitly estimating species optima, tolerances, and maxima, per ecological gradient, we can better predict change in species communities, and understand how species relate to each other. C_LI

ecology↗