Influence of climatic drivers and long term N fertilization on the production and leaching of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) in a Norway spruce (Picea abies) forest stand

The influence of long-term nitrogen (N) fertilization and climatic drivers on the production and leaching of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) was studied in a Norway spruce (Picea abies (L.) Karst.) forest stand. DOC and DON soil solution concentrations in the O horizon were roughly an order of magnitude larger than B horizon soil solution concentrations. Soil solution sampled in the O horizon did not seem to respond to N fertilization. In the B horizon, however, slightly elevated concentrations of DOC and DON were occasionally observed in the fertilized plots. There did not seem to be a substantial effect of N fertilization on soil solution concentrations of DOC and DON. A decisive influence of simple climatic drivers on the within-year dynamics of DOC and DON soil solution concentrations could not be determined in this work. The annual mean DOC concentrations were higher 2009 than 1995, which might reflect an influence of the tree stand development on DOC soil solution concentrations

Nitrogen in soil water of coniferous forests

In boreal and temperate forests, long-term elevated nitrogen (N) load may eventually saturate forest ecosystems with N, i.e. total N ecosystem input exceed ecosystem sinks for N, and N losses via soil water transport may then increase and negatively impact environmental quality. This thesis is based upon four studies (reported in papers I-IV), and the overall aims were to assess and analyse effects on soil water N in coniferous forests of two types of anthropogenic disturbance: “chemical disturbance” (long-term experimental N addition and N deposition), and “physical disturbance” (clear-cutting and subsequent soil scarification). Effects of these disturbances were addressed in both field experiments and process-based ecosystem modelling. In the field experiments, soil water N was collected from both organic (O) horizons and mineral soil, at 0.5 m depth, during several growing seasons to assess temporal variation in the N concentration (Paper I). In addition, microbial variables in soil samples of the O-horizon were analysed in the laboratory to assess responses of the soil microbial community to long-term N addition in forest experiments and along a N deposition gradient (Papers II and IV). In the modelling, a process-based ecosystem carbon and N model (CoupModel) was calibrated to measurements obtained during the regeneration phase of a Scots pine (Pinus sylvestris L.) forest in an N fertilization experiment where soil scarification was applied (Paper III). The results showed that long-term N addition to a boreal Norway spruce (Picea abies (L.) Karst) forest can alter the quantity and seasonal dynamics of dissolved organic nitrogen (DON) concentrations in soil water collected from the O-horizon. However, DON concentrations were low in soil water collected from mineral soil under all N treatments and probably only contributed to small net N losses in this forest. Although microbial variables of the O-horizon were affected by N loading they were similar under N loading that resulted in the leaching of small amounts of nitrate (15 kg ha⁻¹ year⁻¹ of NO₃-N). Further, soil scarification increased soil water N leaching from a Scots pine forest, as calculated with the CoupModel, during the regeneration phase, particularly in previously N-fertilized pine stands

The combined impacts of land use change and climate change on soil organic carbon stocks in the Ethiopian highlands

Land Use Change (LUC), especially deforestation in tropical regions, significantly contributes to global anthro-pogenic greenhouse gas (GHG) emissions. Here, we address potential combined impacts of LUC and Climate Change (CC) on Soil Organic Carbon (SOC) stocks in the Ethiopian highlands. The soil model Q was employed to predict SOC stocks for various combinations of LUC and CC scenarios until the year 2100. Four reference sce-narios (cropland, bushland, natural forest, and Eucalyptus plantations under contemporary climatic conditions) were evaluated against reported measurements of SOC stocks. We studied impacts of six common LUC scenarios, including deforestation and planting Eucalyptus, on SOC stocks under contemporary and future climates. To assess the impact of CC, effects of elevated temperature (mean annual temperature + 2.6 degrees C) together with three litterfall scenarios (no change in litterfall, a 5% reduction and 22% increase, designated CC0, CCd, and CCi, respectively) were considered to test potential vegetation responses to increases in temperature and atmospheric CO2 concentrations. Most of the tested combinations of LUC and CC led to losses of SOC stocks. Losses were most severe, both relatively and absolutely, in the deforestation scenarios: up to 30% was lost if natural forest was converted to cropland and temperature increased (under the CC0 scenario). Gains in SOC stocks of 4-19% were modelled when sparse vegetation was converted to more dense vegetation like Eucalyptus plantation with sub-stantially increased litterfall (the CCi scenario). Elevated temperature accelerated decomposition rates, leading to circa 8% losses of SOC stocks.We conclude that effects of LUC and CC on SOC stocks are additive and changes in litterfall caused by LUC determine which has the largest impact. Hence, deforestation is the biggest threat to SOC stocks in the Ethiopian highlands, and stocks in sparse vegetation systems like cropland and bushland are more sensitive to CC0 than LUC. We recommend conservation of natural forests and longer rotation periods for Eucalyptus plantations to preserve SOC stocks.Finally, we suggest that use of the Q model is a viable option for national reporting changes in SOC stocks at Tier 3 within the LULUCF sector to the United Nations Framework Convention on Climate Change (UNFCCC) as it is widely applicable and robust, although it only requires input data on a few generally available variables