LAUSR

The varying strengths of relationships between diversity measures—be they taxonomic, functional or phylogenetic—imply that biodiversity dimensionality is variable. Understanding these dimensions is essential to discerning how local communities respond to environmental changes. This study aimed to (i) evaluate the dimensionality of biodiversity in lentic systems, (ii) identify the primary measures that differentiate local communities and (iii) test the hypothesis that biodiversity dimensionality is positively correlated with environmental dimensionality. Using a large dataset encompassing phytoplankton, zooplankton and macroinvertebrate communities from lake ecosystems across the contiguous United States, I calculated Camargo's evenness index based on the eigenvalues from a principal component analysis (PCA) to assess the dimensionality of biodiversity. I also evaluated the degree to which multiple biodiversity dimensions were necessary to describe community patterns. I found that two to three sets of diversity measures were required to adequately capture the biodiversity patterns of plankton and macroinvertebrate communities, respectively. The main measures differentiating local communities were those that included the phylogenetic structure among the taxa. Taxonomic and functional richness also emerged as important variables. The anticipated positive relationship between biodiversity dimensionality and environmental dimensionality was supported for macroinvertebrate communities but not for planktonic groups. This finding suggests that environmental complexity may have distinct impacts depending on the community structure and taxonomic group considered. These study results indirectly suggest that relying on a single measure may cause studies to overlook important responses of biodiversity to environmental gradients. More importantly, in line with previous studies, I found that using only measures based on taxonomic identities falls short in differentiating lentic communities. The feasibility of using measures that require detailed information (e.g., phylogenetic structure) in real‐world contexts (e.g., bioassessment) is an issue that should be carefully evaluated in further studies.