• Energy Research

AbstractTo determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L−1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long‐term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient‐rich lakes than nutrient concentrations and surface temperature.

Abstract. Streams draining upland catchments carry large quantities of carbon from terrestrial stocks to downstream freshwater and marine ecosystems. Here it either enters long-term storage in sediments or enters the atmosphere as gaseous carbon through a combination of biotic and abiotic processes. There are, however, increasing concerns over the long-term stability of terrestrial carbon stores in blanket peatland catchments as a result of anthropogenic pressures and climate change. We analysed sub-annual and inter-annual changes in river water colour (a reliable proxy measurement of dissolved organic carbon; DOC) using 6 years of weekly data, from 2011 to 2016. This time-series dataset was gathered from three contiguous river sub-catchments, the Black, the Glenamong and the Srahrevagh, in a blanket peatland catchment system in western Ireland, and it was used to identify the drivers that best explained observed temporal change in river colour. The data were also used to estimate annual DOC loads from each catchment. General additive mixed modelling was used to identify the principle environmental drivers of water colour in the rivers, while wavelet cross-correlation analysis was used to identify common frequencies in correlations. At 130 mg Pt Co L−1, the mean colour levels in the Srahrevagh (the sub-catchment with lowest rainfall and higher forest cover) were almost 50 % higher than those from the Black and Glenamong, at 95 and 84 mg Pt Co L−1 respectively. The decomposition of the colour datasets revealed similar multi-annual, annual and event-based (random component) trends, illustrating that environmental drivers operated synchronously at each of these temporal scales. For both the Black and its nested Srahrevagh catchment, three variables (soil temperature, soil moisture deficit, SMD, and the weekly North Atlantic Oscillation, NAO) combined to explain 54 % and 58 % of the deviance in colour respectively. In the Glenamong, which had steeper topography and a higher percentage of peat intersected by streams, soil temperature, the log of stream discharge and the NAO explained 66 % of the colour concentrations. Cross-wavelet time-series analysis between river colour and each environmental driver revealed a significant high common power relationship at an annual time step. Each relationship however, varied in phase, further highlighting the complexity of the mechanisms driving river colour in the sub-catchments. The estimated mean annual DOC loads for the Black and Glenamong rivers to Lough Feeagh were similar at 15.0 and 14.7 t C km−2 yr−1 respectively. The important role of past and current precipitation and, in particular, temperature emphasises the vulnerability of blanket peatland carbon stores to projected climate change and highlights the interaction of local and regional climate in controlling aquatic carbon export. Our results show that water colour (and hence DOC) concentrations can vary considerably between neighbouring catchments and also that regional-scale climatic drivers control the trends in intra- and inter-annual flux of DOC through the system. The combination of locally determined concentrations and regionally controlled fluxes produces aquatic DOC loads that vary over both the annual cycle and over multiple years.

Changes in climate and human behaviour impact catchment hydrology and the export of nutrients including dissolved organic carbon (DOC), with consequences for drinking water supply. In this study, we projected future river discharge and DOC dynamics under three Shared Socioeconomic Pathways (i.e., different futures of climatic conditions, socio-economic development and adaptation to climate change) and quantified change relative to a baseline for two contrasting catchments: one in Sweden and one in Ireland. For this, we used the Generalised Watershed Loading Functions Model (GWLF) with an integrated DOC module (GWLF-DOC) and drove it with data from an ensemble of global climate models, taking into account variability derived from multiple model parameter sets. We assessed the relative contribution of each of these two factors (climate input data and model parameterisation) to the total uncertainty in predictions. Projections for river discharge differed between the two sites in magnitude, variability and direction of change depending on the future scenario and time period. In contrast, DOC was always projected to show increases in concentration throughout the annual cycle and over time, with the highest levels by the end of the century, for scenarios with greater warming and low mitigation efforts. Future climate data provided the dominant source of uncertainty in all of our projections. However, the DOC model parameters, which respond to temperature and soil moisture conditions, became more influential in scenarios of higher climatic variability. Our approach highlights the benefits of incorporating often ignored parameter uncertainty in climate change impact assessments for both interpreting outputs and communicating results to water managers.

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.