Wetland Biotypology by Multivariate Methods: What Happens When Species Abundance Is Weighted by Species Preference Index?

Abstract

Wetland conservation planning relies on the in situ distribution of both habitats and species and also on species preferences for these habitats. To study such distributions, ecologists frequently use multivariate methods, mainly correspondence analysis (CA) and hierarchical clustering, which are based on the raw or transformed abundances of species in habitats. These methods often suffer from the high dominance of abundant generalist species and obscure the role of species with low abundance, including some indicator taxa, which leads to an uncertain ecological interpretation of the results. In this study, we suggest mitigating this bias by weighting raw abundances by the degree of preference (DP) of the species. As this index varies between 0 and 1, the weighting operation reduces the influence of generalist taxa (with low DP) in favor of selective taxa (with high DP) and redistributes species contributions in the factorial axes. In parallel, K-medoids allows for the clustering of both species and habitats in ecologically coherent groups, whose composition shifts with data weighting. These changes were tested on a real dataset of 109 waterbird species counted in 166 wetland habitats, which was submitted to CA in combination with a hybrid K-medoids clustering method. In addition to its ecological foundation, in the sense that it improves the ecological relevance of wetland and assemblage typologies, this approach is intermediate between the use of raw abundance and presence–absence and avoids subjective data codification, offering a robust tool for conservation evaluation and decision-making.