Categories
INCA-N New Papers PERSiST

Nitrate leaching under climate change

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.

Categories
New Papers PERSiST

Declining streamflow in central European forests

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.

Categories
INCA-C New Papers PERSiST

Spatially explicit, landscape-scale modelling of GHG sources and sinks

Maria Holmberg and colleagues present an approach to collate spatially explicit estimated fluxes of GHGs (carbon dioxide, methane and nitrous oxide) for the main land use sectors in the landscape, and show how these fluxes can be aggregated to calculate net emissions of an entire region. They used INCA-C and PERSiST to estimate the flux of organic carbon from terrestrial ecosystems to lakes and rivers.

They developed and tested the approach in a large river basin in Finland, providing information from intensively studied eLTER research sites. To evaluate the full GHG balance, they included fluxes from natural ecosystems (lakes, rivers, and undrained mires) together with anthropogenic fluxes from agriculture and forestry. They quantified fluxes using an anthropogenic emissions model (FRES), a forest growth and carbon balance model (PREBAS), and literature values for emissions from lakes, rivers, undrained mires, peat extraction sites and cropland. Spatial data sources included CORINE land use data, soil map, lake and river shorelines, national forest inventory data, and statistical data on anthropogenic activities. Emission uncertainties were evaluated with Monte Carlo simulations. They summed the vertical fluxes of spatially explicit net emissions, disregarding the impact of lateral fluxes from terrestrial to aquatic ecosystems on the vertical fluxes.

Their model results showed that artificial surfaces were the most emission intensive land-cover class while lakes and rivers were about as emission intensive as arable land. Forests were the dominant land cover in the region (66%). The forest C sink decreased total emissions for the region by 72%. The region’s net emissions amounted to 4.37 ± 1.43 Tg CO2-eq yr-1, corresponding to a net emission intensity 0.16 Gg CO2-eq km-2 yr-1, and estimated per capita net emissions of 5.6 Mg CO2-eq yr-1. Using INCA-C and PERSiST, the amount of organic C leaching from mires, cropland, and forests to the watercourses was estimated to correspond to about 10% of the CO2 and CH4 emissions from land to air.

Although the landscape approach developed by Dr. Holmberg and colleagues opens opportunities to examine the sensitivities of important GHG fluxes to changes in land use and climate, management actions, and mitigation of anthropogenic emissions, there is still a need to extend the work to a fully integrated regional GHG budget, accounting for all lateral fluxes of C- and N-containing compounds.