Climate change may alter the services ecosystems provide by changing ecosystem functioning. As ecosystems can also resist environmental perturbations, it is crucial to consider the different processes that influence resilience. “Climate proofing” can identify potential climate-related threats to ongoing delivery of ecosystem services. Dr. Katri Rankinen and colleagues have published a new study modelling the potential for increased nitrate(NO3−) concentrations in drinking water due to climate change. They analyzed catchment-scale changes in ecosystem services connected to water purification in southern Finland by combining climate change scenarios with process-based forest growth (PREBAS) and eco-hydrological (PERSiST and INCA) models. By using the aforementioned model chain, they improved traditional model calibration by including timing of forest phenology and duration of the snow-covered period from networks of cameras and satellite data. They upscaled the combined modelling results with scenarios of population growth to produce vulnerability maps. Their results show that boreal ecosystems seemed to be strongly buffered against increased NO3– leaching by a combination of increases in evapotranspiration and vegetation NO3– uptake. Societal vulnerability varied greatly between scenarios and municipalities. The most vulnerable areas were agricultural regions on permeable soil types.
Dr. Jan Deutscher and colleagues present a new study modelling streamflow decline in the Central European uplands. This study is timely as in recent decades the effects of global climate change have caused a continuous drying out of temperate landscapes. In Czech forests, this drying out has been manifested as a visible decrease in streamflow. Dr. Deutscher and colleagues address questions related to the severity of the streamflow decrease and attempt to identify its main causes. They base their analysis on daily streamflow, temperature, and precipitation data measured during five years (1/11/2014 to 31/10/2019) in a spruce-dominated temperate upland catchment located in the Czech Republic. Streamflow values were modeled in with PERSiST using precipitation and temperature values obtained from the observational E-OBS gridded dataset and calibrated against in situ measured discharge. Their modeling results show a greater than 65% decline in streamflow during the five-year study period at the Křtiny experimental catchment. This trend is most likely caused by increasing temperature. They found a strong relationship between increasing temperature and decreasing discharge during the growing seasons, which can be simplified to an increasing trend in the mean daily temperature of 0.1o C per season, effectively causing a decreasing trend in the discharge of −10% per season regardless of the increasing precipitation during the period.