We assessed the relative roles of local environmental conditions and dispersal on community structure in a landscape of lakes for the major trophic groups. We use taxonomic presence-absence and abundance data for bacteria, phytoplankton, zooplankton, and fish from 18 lakes in southern Quebec, Canada. The question of interest was whether communities composed of organisms with more limited dispersal abilities, because of size and life history (zooplankton and fish) would show a different effect of lake distribution than communities composed of good dispersers (bacteria and phytoplankton). We examine the variation in structure attributable to local environmental (i.e., lake chemical and physical variables) vs. dispersal predictors (i.e., overland and watercourse distances between lakes) using variation partitioning techniques. Overall, we show that less motile species (crustacean zooplankton and fish) are better predicted by spatial factors than by local environmental ones. Furthermore, we show that for zooplankton abundances, both overland and watercourse dispersal pathways are equally strong, though they may select for different components of the community, while for fish, only watercourses are relevant dispersal pathways. These results suggest that crustacean zooplankton and fish are more constrained by dispersal and therefore more likely to operate as a metacommunity than are bacteria and phytoplankton within this studied landscape.

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

The classical view states that microbial biogeography is not affected by dispersal barriers or historical events, but only influenced by the local contemporary habitat conditions (species sorting). This has been challenged during recent years by studies suggesting that also regional factors such as mass effect, dispersal limitation and neutral assembly are important for the composition of local bacterial communities. Here we summarize results from biogeography studies in different environments, i.e. in marine, freshwater and soil as well in human hosts. Species sorting appears to be the most important mechanism. However, this result might be biased since this is the mechanism that is easiest to measure, detect and interpret. Hence, the importance of regional factors may have been underestimated. Moreover, our survey indicates that different assembly mechanisms might be important for different parts of the total community, differing, for example, between generalists and specialists, and between taxa of different dispersal ability and motility. We conclude that there is a clear need for experimental studies, first, to clearly separate regional and local factors in order to study their relative importance, and second, to test whether there are differences in assembly mechanisms depending on different taxonomic or functional groups.

Ecological stability is the central framework to understand an ecosystem's ability to absorb or recover from environmental change. Recent modelling and conceptual work suggests that stability is a multidimensional construct comprising different response aspects. Using two freshwater mesocosm experiments as case studies, we show how the response to single perturbations can be decomposed in different stability aspects (resistance, resilience, recovery, temporal stability) for both ecosystem functions and community composition. We find that extended community recovery is tightly connected to a nearly complete recovery of the function (biomass production), whereas systems with incomplete recovery of the species composition ranged widely in their biomass compared to controls. Moreover, recovery was most complete when either resistance or resilience was high, the latter associated with low temporal stability around the recovery trend. In summary, no single aspect of stability was sufficient to reflect the overall stability of the system.

The response of microbial communities to long-term environmental change is poorly understood. Here, we study bacterioplankton communities in a unique system of coastal Antarctic lakes that were exposed to progressive long-term environmental change, using 454 pyrosequencing of the 16S rDNA gene (V3–V4 regions). At the time of formation, most of the studied lakes harbored marine-coastal microbial communities, as they were connected to the sea. During the past 20 000 years, most lakes isolated from the sea, and subsequently they experienced a gradual, but strong, salinity change that eventually developed into a gradient ranging from freshwater (salinity 0) to hypersaline (salinity 100). Our results indicated that present bacterioplankton community composition was strongly correlated with salinity and weakly correlated with geographical distance between lakes. A few abundant taxa were shared between some lakes and coastal marine communities. Nevertheless, lakes contained a large number of taxa that were not detected in the adjacent sea. Abundant and rare taxa within saline communities presented similar biogeography, suggesting that these groups have comparable environmental sensitivity. Habitat specialists and generalists were detected among abundant and rare taxa, with specialists being relatively more abundant at the extremes of the salinity gradient. Altogether, progressive long-term salinity change appears to have promoted the diversification of bacterioplankton communities by modifying the composition of ancestral communities and by allowing the establishment of new taxa.