Congruence, but no cascade-Pelagic biodiversity across three trophic levels in Nordic lakes

Declining calcium concentration drives shifts toward smaller and less nutritious zooplankton in northern lakes

Zooplankton community composition of northern lakes is changing due to the interactive effects of climate change and recovery from acidification, yet limited data are available to assess these changes combined. Here, we built a database using archives of temperature, water chemistry and zooplankton data from 60 Scandinavian lakes that represent broad spatial and temporal gradients in key parameters: temperature, calcium (Ca), total phosphorus (TP), total organic carbon (TOC), and pH. Using machine learning techniques, we found that Ca was the most important determinant of the relative abundance of all zooplankton groups studied, while pH was second, and TOC third in importance. Further, we found that Ca is declining in almost all lakes, and we detected a critical Ca threshold in lake water of 1.3 mg L-1 , below which the relative abundance of zooplankton shifts toward dominance of Holopedium gibberum and small cladocerans at the expense of Daphnia and copepods. Our findings suggest that low Ca concentrations may shape zooplankton communities, and that current trajectories of Ca decline could promote widespread changes in pelagic food webs as zooplankton are important trophic links from phytoplankton to fish and different zooplankton species play different roles in this context.

Decadal biodiversity trends in rivers reveal recent community rearrangements

While it is recognized that biodiversity currently declines at a global scale, we still have an incomplete understanding of local biodiversity trends under global change. To address this deficiency, we examined the recent decadal trends in water quality and biodiversity (taxonomic and functional) of key river organisms (diatoms, macroinvertebrates and fish) in France. We implemented regression, RLQ and fourth-corner analyses. Our results showed that nutrient loads tended to decrease, diatom richness tended to decline and macoinvertebrate richness tended to increase. The recovery of sensitive taxa in all three groups suggested a successful outcome of water quality management in France over the past decades. Our study further revealed consistent rearrangements within river communities, with a decrease in the ratio of planktonic to benthic diatoms, and corresponding functional changes in macroinvertebrate and fish trait composition, indicative of a trophic cascade in response to changes in environmental conditions.

Multiple thresholds and trajectories of microbial biodiversity predicted across browning gradients by neural networks and decision tree learning

Ecological association studies often assume monotonicity such as between biodiversity and environmental properties although there is growing evidence that nonmonotonic relations dominate in nature. Here, we apply machine-learning algorithms to reveal the nonmonotonic association between microbial diversity and an anthropogenic-induced large-scale change, the browning of freshwaters, along a longitudinal gradient covering 70 boreal lakes in Scandinavia. Measures of bacterial richness and evenness (alpha-diversity) showed nonmonotonic trends in relation to environmental gradients, peaking at intermediate levels of browning. Depending on the statistical methods, variables indicative for browning could explain 5% of the variance in bacterial community composition (beta-diversity) when applying standard methods assuming monotonic relations and up to 45% with machine-learning methods taking non-monotonicity into account. This non-monotonicity observed at the community level was explained by the complex interchangeable nature of individual taxa responses as shown by a high degree of nonmonotonic responses of individual bacterial sequence variants to browning. Furthermore, the nonmonotonic models provide the position of thresholds and predict alternative bacterial diversity trajectories in boreal freshwater as a result of ongoing climate and land-use changes, which in turn will affect entire ecosystem metabolism and likely greenhouse gas production.