Abstract/Summary

Elevated nitrogen deposition, caused by traffic, agriculture and industrial emissions, has driven elevated nitrate (NO3-N fluxes) from European forest ecosystems since the late 20th century. Here, an assessment of interactions between former land use, throughfall Total Inorganic Nitrogen (TIN) and NO3-N leaching from forest was first carried out by collating a database from the literature. Leaching of NO3-N was greater in secondary conifer rotations than in conifer-afforested heathland/grassland (p < 0.05). The wide variation in NO3-N leaching fluxes from afforested arable land highlighted the current lack of understanding of the potential for afforestation to improve or threaten water quality. The conversion of conifer plantations to broadleaf forests is increasing across Europe to meet targets to improve forest resilience to pests, disease, and extreme climate events. Due to the changes in soil biochemical processes, the conifer-to-broadleaf conversion was hypothesised to stimulate the breakdown of N-rich organic matter, accumulated during the first rotation, and lead to elevated NO3-N leaching fluxes. However, a chronosequence study observed that throughfall dissolved organic carbon and NO3-N fluxes controlled NO3-N leaching fluxes across the study area, with no significant differences in NO3-N leaching fluxes observed between stands at different stages in the conifer-to-broadleaf conversion process. A coupled biochemical-hydrological model was then tested in its ability to simulate NO3-N leaching fluxes from a mature Pinus sylvestris forest long-term, to then simulate land-use change scenarios. However, the model could not be successfully parameterised. Much of the existing knowledge on NO3-N leaching from forest ecosystems is based on past observed data, which limits evidence-based decision-making for forest nutrient management, particularly under changing forest management, climate change and reductions in N deposition. To support much needed efforts to parameterise detailed biochemical-hydrological models, a framework to improve the parameterisation procedure of such models is proposed.