Novel functional dissimilarity measures bridging species- and trait-based community analyses

Quantifying dissimilarity between ecological communities is fundamental to functional community ecology. In this study, we develop a conceptual and analytical framework that integrates species-based and trait-based dissimilarity measures. The core of the proposed approach involves two steps: the first computes the products of species abundances and trait values, while the second combines products into aggregated trait abundances (ATAs) for use in both species- and trait-based analyses. Building upon the additive decomposition of the Marczewski-Steinhaus and Bray-Curtis indices into difference and replacement components, we introduce a suite of novel methods that allow for the independent weighting of species abundances and trait values. We first detail the methodology and elucidate its conceptual foundations. Subsequently, we assess its performance using both illustrative toy examples and ecologically realistic simulated datasets. To demonstrate its practical utility, we apply the method to compare macroinvertebrate assemblages from natural and anthropogenically impacted stream sections. Our findings indicate that the proposed framework provides a continuum between traditional species-based and trait-based approaches. Finally, we offer practical guidance for ecologists on selecting the most appropriate dissimilarity measure based on specific research objectives and data characteristics.