Kazuya Nishina

Spatial variations in nitrous oxide and nitric oxide emission potential on a slope of Japanese cedar (Cryptomeria japonica) forest.

Abstract To quantify the spatial variation and spatial structure of nitrous oxide (N2O) and nitric oxide (NO) emission from forest soils, we measured N2O and NO emission rates from surface soil cores taken at 1 m intervals on a cross-line transect (65 m × 20 m) on a slope of Japanese cedar (Cryptomeria japonica) forest in a temperate region of central Japan and analyzed the spatial dependency of N oxide gas emissions using geostatistics. We divided N2O emission into N2O from denitrification and N2O from nitrification using the acetylene inhibition method. According to the geostatistical analysis, N2O emission rates on the slope had large spatial variation and weak spatial dependency. This weak spatial dependency was caused by the inordinately high N2O emissions on the slope, which were derived mainly from denitrification. In contrast, NO emission rate on the slope had large spatial variation, but strong spatial dependency and a distinct spatial distribution related to slope position, that is, high in the middle of the slope and low in the shoulder and the foot of the slope. The CN ratio and water-filled pore space were the dominant factors controlling NO emission rate on a slope. Our results suggest that spatial information about topographic factors helps to improve the estimation of both N2O emission and NO emission from forest soils.

Relationship between N2O and NO emission potentials and soil properties in Japanese forest soils

Abstract To determine the relationship between nitrous oxide (N2O) and nitric oxide (NO) emission rates and soil properties in forest soils, N2O and NO emission rates in soils were measured in incubation experiments under standardized temperature and water conditions (water content at a water-holding capacity of 60%) using soils packed into a cylindrical core, and variations in the soil properties were also determined. The N2O emission rates from nitrification and from denitrification were determined separately using a nitrification inhibitor (10 Pa acetylene). Soil samples were taken from 25 forest stands in a central temperate area of Japan. The N2O and NO emission rates were highly variable, even under the standardized temperature and water-holding capacity (60%) conditions. According to a partial least squared regression model analysis, the C:N ratio and pH strongly affected the N2O emission rate, whereas NO- 3, water-soluble Al and the C:N ratio strongly affected the NO emission rate. The C:N ratio negatively affected the emission rate of both N oxide gases, suggesting that N mineralization is an important factor in the rates of N oxide gas emission. The acetylene inhibition experiment showed that N2O emission from denitrification was positively affected by pH, water-filled pore space and filling density, and negatively affected by the C:N ratio, total carbon and total nitrogen.

Calibration of forest 137Cs cycling model ”FoRothCs” via approximate Bayesian computation based on 6-year observations from plantation forests in Fukushima

Predicting the environmental fate of 137Cs in forest ecosystems along with the concentrations of 137Cs in tree parts are important for the managements of radioactively contaminated forests. In this study, we calibrate the Forest RothC and Cs model (FoRothCs), a forest ecosystem 137Cs dynamics model, using observational data obtained over six years from four forest sites with different levels of 137Cs contamination from Fukushima Prefecture. To this end, we applied an approximate Bayesian computation (ABC) technique based on the observed 137Cs concentrations (Bq kg-1) of five compartments (leaf, branch, stem, litter, and soil) in a Japanese cedar plantation. The environmental decay (increment) constants of the five compartments were used as the summary statistics (i.e., the metric for model performance) to infer the five parameters related to 137Cs transfer processes in FoRothCs. The ABC technique successfully reconciled the model outputs with the observed trends in 137Cs concentrations at all sites during the study period. Furthermore, the estimated parameters are in agreement with the literature values (e.g., the root uptake rates of 137Cs). Our study demonstrates that model calibration with ABC based on the trends in 137Cs concentrations of multi compartments is useful for reducing the prediction uncertainty of 137Cs dynamics in forest ecosystems.