Integration of species traits in direct gradient analysis generates insights into how communities are assembled and may respond to environmental changes. We investigated phytoplankton trait-environment relationships for over 300 taxa during the open-water season across 75 north-temperate lakes and reservoirs in Alberta, Canada. An innovative, data-driven approach was applied using iterative model selection for RLQ optimization to reveal key monthly associations. Fourth-corner analysis then tested the significance of relationships using spatially and phylogenetically constrained null models derived by Moran spectral randomization. Both local- and regional-scale drivers of succession were found with evidence of deterministic filtering by traits increasing in mid-summer. Trait associations to land-use and water quality highlighted potential anthropogenic cross-scale interactions, such as logging and pasture development affecting phytoplankton via allochthonous nutrient inputs. Biogeographic factors (e.g., elevation and habitat size) and associated temperature and chemical gradients (e.g., pH and bicarbonate) were also linked to multiple morphological, physiological, and behavioral traits, including potential toxin production. Several correlated traits emphasized importance of trait syndromes corresponding to distinct taxonomic groups (e.g., cyanobacteria and green algae). However, rather than clustering species with shared ecological preferences or roles, our study builds on past trait-based approaches to phytoplankton by testing for explicit trait associations with a range of environmental factors. Thus, we provide a novel, quantitative means of revealing environmental constraints on communities and translating their compositional changes under climate and other human influences into functional impacts on freshwater ecosystems.
