Koerich, G. | Search bioRxiv

bioRxiv2026

Reduced-Rank Generalised Dissimilarity Modelling (RRGDM): Model-Based Ordination of Dissimilarity Data

(1) Dissimilarity indices offer an effective way to represent multivariate variability in community composition and to quantify beta diversity and its drivers. However, models that regress dissimilarities against environmental predictors face the challenge of linking site-level predictors to a pairwise response. (2) This mismatch is typically circumvented by regressing dissimilarities against distances in predictor values. But this approach does not reflect how environmental variables act on individual samples, complicates the inclusion of standard modelling features such as random effects, and conflates environmental effects on average composition with effects on compositional dispersion. (3) We propose Reduced-Rank Generalised Dissimilarity Modelling (RRGDM), a framework for model-based ordination that resolves the pair-to-site mismatch by reframing dissimilarity modelling as an ordination problem. RRGDM represents dissimilarities as the outcome of sample positions in a shared, low-dimensional latent space that captures community composition. These positions are in turn modelled as a linear function of predictors and error terms, with an associated dispersion sub-model. (4) Through a simulation study and two empirical examples, we show that RRGDM recovers known environmental effects and represents them as ecologically interpretable outputs. RRGDM enables inference on the relative importance of environmental gradients driving beta diversity and disentangles effects on composition versus dispersion. Although motivated by beta diversity, the approach is applicable to other pairwise dissimilarity data.

ecology↗

bioRxiv2026

Population and community responses to the fast, slow, and seasonal components of environmental variation

Theory suggests that different components of environmental fluctuations, from daily and seasonal cycles to multidecadal trends, can have distinct and even opposing effects on species abundances and community dynamics, depending on their specific adaptations. But empirical research that deconstructs the influence of these different cycles on communities is lacking. Here, we used long-term biological monitoring data together with flow records of rivers across New Zealand to (i) investigate the role of fast, slow, and seasonal river-flow fluctuations in structuring macroinvertebrate communities; and (ii) to assess whether life-history and mobility traits mediate the response. Using joint species distribution models, we found striking differences in taxon and community responses to the different components of river flow variation. Responses to slow fluctuations were generally stronger and better predicted by traits, while responses to seasonal fluctuations were highly heterogeneous. Fast increases in flow, typical of flooding events, had pervasive negative effects on species abundances, but the severity of impact partly depended on mobility traits. Our results suggest that different ecological mechanisms underpin the response to distinct environmental fluctuations, highlighting the value of jointly considering multiple temporal scales of variation and species functional traits to understand and predict how communities reorganise under fluctuating environmental regimes.

ecology↗