• Journal of Korean Society of Forest Science
• /
• v.103 no.4
• /
• pp.593-598
• /
• 2014

In this study, we developed the carbon emission factors for 4 major species of warm-temperate region in Korea, and tried to provide their carbon emissions and removals estimates using these carbon emission factors. We selected Castanopsis cuspidata, Camellia japonica, Quercus acuta and Quercus glauca as target species and derived their carbon emission factors. The basic wood density that serve as one of the carbon emission factors were 0.583 for Castanopsis cuspidata, 0.657 for Camellia japonica, 0.833 for Quercus acuta and 0.763 for Quercus glauca and their uncertainties ranged from 5.3 to 17.9%. Biomass expansion factors were calculated as well: 1.386 for Castanopsis cuspidata, 2.621 for Camellia japonica, 1.701 for Quercus acuta and 2.123 for Quercus glauca and associated uncertainties varied from 14.7 to 30.5%. Lastly root-shoot ratios for each species were also determined: 0.454 for Castanopsis cuspidata, 0.356 for Camellia japonica, 0.191 for Quercus acuta and 0.299 for Quercus glauca with the uncertainties lying within a range from 19.8 to 35.7%. These three carbon emission factors including basic wood density had the uncertainties of less than 40% recommended by FAO. Therefore the application of country-specific emission factors seemed to provide quite accurate estimates of carbon emissions and removals. The estimation of the carbon stored in the 4 species were also conducted which amounted to $186.10tCO_2/ha$ for Castanopsis cuspidata, $280.63tCO_2/ha$ for Camellia japonica, $344.04tCO_2/ha$ for Quercus acuta and $278.91tCO_2/ha$ for Quercus glauca and their annual carbon removals were $6.65tCO_2/ha/yr$, $6.25tCO_2/ha/yr$, $11.70tCO_2/ha/yr$ and $12.29tCO_2/ha/yr$, respectively. This systematic assessment of forest resources can be a reliable source of information for managing evergreen broadleaved forest in warm temperate regions and thus serve as useful data for effective decision-making to address vegetation zone shifts due to climate change.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.308-308
• /
• 2017

The low and unstable yield of soybean has been a major problem in Japan. Excess soil moisture conditions are one of the major factors to restrict soybean productivity. More than 80 % of soybean crops are cultivated in converted paddy fields which often have poor drainage. In central and eastern regions of Japan, the early vegetative growth of soybean tends to be restricted by the flooding damage because the early growth period is overlapped with the rainy season. Field observation shows that induced excess water stress in early vegetative stage reduces dry matter production by decreasing intercepted radiation by leaf and radiation use efficiency (RUE) (Bajgain et al., 2015). Therefore, it is necessary to evaluate the responses of soybean growth for excess water conditions to assess these effects on soybean productions. In this study, we aim to modify the soybean crop model (Sinclair et al., 2003) by adding the components of the restriction of leaf area development and RUE for adaptable to excess water conditions. This model was consist of five components, phenological model, leaf area development model, dry matter production model, plant nitrogen model and soil water balance model. The model structures and parameters were estimated from the data obtained from the field experiment in Tsukuba. The excess water effects on the leaf area development were modeled with consideration of decrease of blanch emergence and individual leaf expansion as a function of temperature and ground water level from pot experiments. The nitrogen fixation and nitrogen absorption from soil were assumed to be inhibited by excess water stress and the RUE was assumed to be decreasing according to the decline of leaf nitrogen concentration. The results of the modified model were better agreement with the field observations of the induced excess water stress in paddy field. By coupling the crop model and the ground water level model, it may be possible to assess the impact of excess water conditions for soybean production quantitatively.