Recent meta-analyses have shown that beta diversity through space is jointly driven by species traits, geographical gradients, and ecosystem properties. Spatial variation is, however, only one aspect of beta diversity. The other component is variation in species assemblages through time, that is, temporal turnover. We examined the decrease of assemblage similarity in time in aquatic ecosystems in relation to several ecological, physical, and geographical factors using an extensive data set derived from the literature. The data set was first divided into intra-annual and interannual studies depending on the temporal extent of the studies. Sampling duration was one the most significant variables affecting the degree of temporal turnover, and we found that turnover was faster in studies with shorter temporal extent. Our results further suggested that the rate of temporal turnover increased with increasing ecosystem size, thus contradicting the general species-time-area relationship. Temporal turnover also varied among the ecosystem types: lake assemblages showed faster turnover than stream or marine assemblages in the interannual data set. We found that temporal turnover exhibited large-scale geographical variation, as there was a latitudinal gradient in turnover. Turnover was faster in the tropics in the intra-annual data set, but the pattern was reversed in the interannual data set, where turnover was faster at high latitudes. Finally, we found that the degree of temporal turnover was related to organism characteristics, as larger organisms with active mobility showed slower temporal turnover than smaller organisms. Our results suggest that the degree of species turnover in time is jointly driven by several ecological, physical, and geographical factors in aquatic ecosystems and that the turnover is not uniform across taxonomic groups. Our findings have important consequences for understanding how different biotic assemblages track temporal changes in the environment and how resilient assemblages are toward such changes.

We sampled 100 small lakes in Finland for bacterio-, phyto-, and zooplankton. The lakes were located in five drainage systems, 20 lakes for each system. We tested two main predictions: that the correlation between community similarity and geographical distance (spatial distance decay) is stronger at the across-drainage than at the within-drainage system scale, and that spatial distance decay is strongest for zooplankton and weakest for bacteria. We used a combination of direct ordination, multivariate statistical tests, and distance-based approaches to examine spatial patterns in our data. Our analyses confirmed both of our predictions. Spatial distance decay was scale-dependent; communities were overall weakly spatially structured within the drainage systems, yet distance decay was significant for all planktonic groups across drainage systems. Spatial distance decay was stronger for zooplankton, with higher slopes and shorter halving distances, than for phytoplankton and bacteria. These results provide evidence that distance decay of similarity is related to study scale, environment, and organism characteristics. Planktonic communities may be controlled by both dispersal-driven assembly and local ecological determinism, with the balance between these two forces depending on study scale.

The strengths of environmental drivers and biotic interactions are expected to show large variability across organism groups. We tested two ideas related to the degree of ecological determinism vs. stochasticity using a large data set comprising bacterio-, phyto-, and zooplankton. We expected that (1) there are predictable, size-driven differences in the degree to which planktonic taxa respond to different drivers such as water chemistry, biotic interactions, and climatic variables; and (2) species distribution models show lowest predictive performance for the smallest taxa due to the stochastic distributions of microbes. Generalized linear models (GLMs), generalized additive models (GAMs), and generalized boosted methods (GBMs) were constructed for 84 species to model their occurrence as a function of eight predictors. Predictive performance was measured as the area under the curve (AUC) of the receiver-operating characteristic plot and true skill statistic (TSS) using independent model evaluation data. We found that the model performances were typically remarkably low for all planktonic groups. The proportion of satisfactory models (AUC > 0.7) was lowest for bacteria (11.1% of the models), followed by phyto- (24.2%) and zooplankton (38.1%). The occurrences of taxa within all planktonic groups were related to climatic variables to a certain degree, but bacteria showed the strongest associations with the climatic variables. Moreover, zooplankton occurrences were more related to biotic variables than the occurrences of smaller taxa, while phytoplankton occurrences were more related to water chemistry. We conclude that the occurrences of planktonic taxa are highly unpredictable and that stochasticity in occurrences is negatively related to the organism size perhaps due to efficient dispersal and fast population dynamics among the smallest taxa.

One of the most intriguing environmental gradients connected with variation in diversity is ecosystem productivity. The role of diversity in ecosystems is pivotal, because species richness can be both a cause and a consequence of primary production. However, the mechanisms behind the varying productivity-diversity relationships (PDR) remain poorly understood. Moreover, large-scale studies on PDR across taxa are urgently needed. Here, we examined the relationships between resource supply and phyto-, bacterio-, and zooplankton richness in 100 small boreal lakes. We studied the PDR locally within the drainage systems and regionally across the systems. Second, we studied the relationships between resource availability, species richness, biomass and resource ratio (N∶P) in phytoplankton communities using Structural Equation Modeling (SEM) for testing the multivariate hypothesis of PDR. At the local scale, the PDR showed variable patterns ranging from positive linear and unimodal to negative linear relationships for all planktonic groups. At the regional scale, PDRs were significantly linear and positive for phyto- and zooplankton. Phytoplankton richness and the amount of chlorophyll a showed a positive linear relationship indicating that communities consisting of higher number of species were able to produce higher levels of biomass. According to the SEM, phytoplankton biomass was largely related to resource availability, yet there was a pathway via community richness. Finally, we found that species richness at all trophic levels was correlated with several environmental factors, and was also related to richness at the other trophic levels. This study showed that the PDRs in freshwaters show scale-dependency. We also documented that the PDR complies with the multivariate model showing that plant biomass is not mirroring merely the resource availability, but is also influenced by richness. This highlights the need for conserving diversity in order to maintain ecosystem processes in freshwaters.

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