Nitrogen leaching from N limited forest ecosystems: the MERLIN model applied to Gårdsjön, Sweden

International audienceChronic deposition of inorganic nitrogen (N) compounds from the atmosphere to forested ecosystems can alter the status of a forest ecosystem from N-limited towards N-rich, which may cause, among other things, increased leaching of inorganic N below the rooting zone. To assess the time aspects of excess N leaching, a process-oriented dynamic model, MERLIN (Model of Ecosystem Retention and Loss of Inorganic Nitrogen), was tested on an N-manipulated catchment at Gårdsjön, Sweden (NITREX project). Naturally generated mature Norway spruce dominates the catchment with Scots pine in drier areas. Since 1991, ammonium nitrate (NH4NO3) solution at a rate of about 35 kg N ha-1 yr-1 (250 mmol m-2 yr-1) has been sprinkled weekly, to simulate increased atmospheric N deposition. MERLIN describes C and N cycles, where rates of uptake and cycling between pools are governed by the C/N ratios of plant and soil pools. The model is calibrated through a hindcast period and then used to predict future trends. A major source of uncertainty in model calibration and prediction is the paucity of good historical information on the specific site and stand history over the hindcast period 1930 to 1990. The model is constrained poorly in an N-limited system. The final calibration, therefore, made use of the results from the 6-year N addition experiment. No independent data set was available to provide a test for the model calibration. The model suggests that most N deposition goes to the labile (LOM) and refractory (ROM) organic matter pools. Significant leaching is predicted to start as the C/N ratio in LOM is reduced from the 1990 value of 35 to <28. At ambient deposition levels, the system is capable of retaining virtually all incoming N over the next 50 years. Increased decomposition rates, however, could simulate nitrate leaching losses. The rate and capacity of N assimilation as well as the change in carbon dynamics are keys to ecosystem changes. Because the knowledge of these parameters is currently inadequate, the model has a limited ability to predict N leaching from currently N-limited coniferous forest ecosystems in Scandinavia. The model is a useful tool for bookkeeping of N pools and fluxes, and it is an important contribution to further development of qualitative understanding of forest N cycles

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales:review and recommendations

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales—sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.<p>Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales—sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.</p

Evaluating the terrestrial carbon dioxide removal potential of improved forest management and accelerated forest conversion in Norway

As a carbon dioxide removal measure, the Norwegian government is currently considering a policy of large-scale planting of spruce (Picea abies (L) H. Karst) on lands in various states of natural transition to a forest dominated by deciduous broadleaved tree species. Given the aspiration to bring emissions on balance with removals in the latter half of the 21st century in effort to limit the global mean temperature rise to “well below” 2°C, the effectiveness of such a policy is unclear given relatively low spruce growth rates in the region. Further convoluting the picture is the magnitude and relevance of surface albedo changes linked to such projects, which typically counteract the benefits of an enhanced forest CO2 sink in high-latitude regions. Here, we carry out a rigorous empirically based assessment of the terrestrial carbon dioxide removal (tCDR) potential of large-scale spruce planting in Norway, taking into account transient developments in both terrestrial carbon sinks and surface albedo over the 21st century and beyond. We find that surface albedo changes would likely play a negligible role in counteracting tCDR, yet given low forest growth rates in the region, notable tCDR benefits from such projects would not be realized until the second half of the 21st century, with maximum benefits occurring even later around 2150. We estimate Norway's total accumulated tCDR potential at 2100 and 2150 (including surface albedo changes) to be 447 (±240) and 852 (±295) Mt CO2-eq. at mean net present values of US$12 (±3) and US$ 13 (±2) per ton CDR, respectively. For perspective, the accumulated tCDR potential at 2100 represents around 8 years of Norway's total current annual production-based (i.e., territorial) CO2-eq. emissions.publishedVersio