Environmental heterogeneity plays a fundamental role in driving species distributions by, for one, fostering niche dimensionality. Within lake ecosystems, species distributions and concordance patterns are driven by both local and regional heterogeneity, though their relative importance across trophic levels has rarely been explored. We developed a statistical framework to compare responses of taxa from different trophic levels to abiotic factors and determine how thisaffected multi-trophic network structures.In particular, we used multi-species concordance modelling (Concordance Analysis and RV coefficient) to determine species associations and correlations within and among three trophic levels (phytoplankton, zooplankton and fish communities sampled across 49 southern Québeclakes, covering eight hydrological regions). We then used Multiple Factor Analysis, Latent Variable Modelling and Local Contributions of sites to Beta Diversity to assess the relative importance of major environmental gradients in structuring species co-responses and species interaction turnover across the landscape. Our analyses confirmed that concordant species within each trophic level varied jointly or segregated into different pelagic food webs in Québec lakes where important acidification and eutrophication took place. Somekeynote species were indicators of different food web compartments and distinguished groups of lakes along multiple environmental niche dimensions. Among the three trophic levels examined, zooplankton depicted the highest proportion of species concordance and appeared to act as a trophic linkage between phytoplankton and fish. Ultimately, the losses or gains in species richness and species interactions were strongly driven by environmental gradients.This study provides for the first time a combined analysis of the effects of environmental heterogeneity on ecological communities belonging to three trophic levels sampled near simultaneously across an 800 km broad lacustrine landscape. The new framework developed in this study has a great potential to better understand the complex response of aquatic ecosystems in a world increasingly affected by multiple, cumulative stressors.
The file provided herein is an RStudio project containing all data files and R script to run the statistical analyses and reproduce figures of the study.