The Anthropocene presents formidable threats to freshwater ecosystems. Lakes are especially vulnerable and important at the same time. They cover only a small area worldwide but harbour high levels of biodiversity and contribute disproportionately to ecosystem services. Lakes differ with respect to their general type (e.g. land‐locked, drainage, floodplain and large lakes) and position in the landscape (e.g. highland versus lowland lakes), which contribute to the dynamics of these systems. Lakes should be generally viewed as ‘meta‐systems’, whereby biodiversity is strongly affected by species dispersal, and ecosystem dynamics are contributed by the flow of matter and substances among locations in a broader waterscape context. Lake connectivity in the waterscape and position in the landscape determine the degree to which a lake is prone to invasion by non‐native species and accumulation of harmful substances. Highly connected lakes low in the landscape accumulate nutrients and pollutants originating from ecosystems higher in the landscape. The monitoring and restoration of lake biodiversity and ecosystem services should consider the fact that a high degree of dynamism is present at local, regional and global scales. However, local and regional monitoring may be plagued by the unpredictability of ecological phenomena, hindering adaptive management of lakes. Although monitoring data are increasingly becoming available to study responses of lakes to global change, we still lack suitable integration of models for entire waterscapes. Research across disciplinary boundaries is needed to address the challenges that lakes face in the Anthropocene because they may play an increasingly important role in harbouring unique aquatic biota as well as providing ecosystem goods and services in the future.

AimTo discover whether lake and stream diatom communities show different patterns in species richness and in their local (LCBD) and species (SCBD) contributions to beta diversity in relation to macroscale environmental characteristics.LocationFinland.MethodsAs biological data, we used diatom samples collected from Finnish stream (n = 492) and lake (n = 290) sites. As explanatory variable data, we used information on macroscale environmental and historical aspects, such as bedrock, soil and post‐glacial highest shoreline. We also accounted for catchment areas, different levels of isolation and relative centrality of the study sites. We ran multiple linear models and selected best models based on AICc values.ResultsWe found that macroscale factors affecting diatom richness and ecological uniqueness differed clearly between streams and lakes. LCBD and species richness of stream communities were more affected by regional environmental characteristics, whereas LCBD and species richness of lake communities were more often driven by spatial measures. The measures of LCBD and species richness showed a slightly negative relationship in streams, but no such relationship was detected in lakes. Also, we showed that, for both streams and lakes, SCBD was strongly determined by the number of sites occupied by a species and the overall abundance of a species.Main conclusionsOur findings related to the distinction between the determinants of lake and stream species richness or LCBD may be tied to the different hydrological connectivity levels occurring in freshwater lotic and lentic systems. Also, in streams, sites with exceptional ecological uniqueness seem to have a rather low number of species. Our findings may be applied to biological conservation and monitoring planning, emphasizing that not only species‐rich but also unique low‐richness sites may be valuable conservation goals.

Patterns in community composition are scale‐dependent and generally difficult to distinguish. Therefore, quantifying the main assembly processes in various systems and across different datasets has remained challenging. Building on the PER‐SIMPER method, we propose a new metric, the dispersal–niche continuum index (DNCI), which estimates whether dispersal or niche processes dominate community assembly and facilitates the comparisons of processes among datasets. The DNCI was tested for robustness using simulations and applied to observational datasets comprising organismal groups with different trophic level and dispersal potential. Based on the robustness tests, the DNCI discriminated the respective contribution of niche and dispersal processes in pairwise comparisons of site groups with less than 40% and 30% differences in their taxa and site numbers, respectively. In the observational datasets, the DNCI suggested that dispersal rather than niche assembly was the dominant assembly process which, however, varied in intensity among organismal groups and study contexts, including spatial scale and ecosystem types. The proposed DNCI measures the relative strength of community assembly processes in a way that is simple, easily quantifiable and comparable across datasets. We discuss the strengths and weaknesses of the DNCI and provide perspectives for future research.

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