A community of metacommunities: exploring patterns in species distributions across large geographical areas

Abstract

Ecological communities show extremely complex patterns of variation in space, and quantifying the relative importance of spatial and environmental factors underpinning patterns of species distributions is one of the main goals of community ecology. Although we have accumulated good knowledge about the processes driving species distributions within metacommunities, we have few insights about whether (and how) environmental and spatial features can actually generate consistent species distributional patterns across multiple metacommunities. In this paper we applied the elements of metacommunity structure (EMS) framework to identify and classify metacommunities according to multiple but discrete patterns of species distributions. Given that each pattern has unique underlying structuring mechanisms, exploring and comparing such patterns across multiple metacommunities spanning large geographical areas provides a way to test the existence of general principles underlying species distributions within metacommunities. In this study, we applied the EMS framework into a data set containing about 9000 lakes distributed across 85 fish metacommunities across Ontario, Canada, and estimated the relative importance of local and spatial factors in explaining their distributional patterns. Nested and Clementsian gradients were the patterns that fitted most metacommunities; nested metacommunities were distributed throughout the province, while Clementsian gradient metacommunities were concentrated in the southeastern region. Sixty-five percent of nested metacommunities were located in low-energy watersheds (i.e., colder climate and shorter growing season), whereas metacommunities representing Clementsian gradients were present in high-energy watersheds (i.e., relatively warmer climate and longer growing season). Taken together, our results reveal that the environmental and spatial properties in which metacommunities are embedded are at least partially responsible for their species distributional patterns.