Estimation of the ecosystem carbon budget in South Korea between 1999 and 2008

A carbon flux model, the vegetation integrated simulator for trace gases, was employed to estimate the carbon budgets of vegetation ecosystems in South Korea. The geographic information system was used to prepare the input variables for the model, such as climate, soil, and land-cover data, from reliable national inventories. Model simulation results indicated that the annual average gross primary production, net primary production, and soil respiration (SR) for 10 years were 91.89, 40.16, and 62.91 Tg C year^?1, respectively. The model also estimated a net ecosystem production with a value of 3.51 Tg C year^?1 between 1999 and 2008. Such results indicate that the vegetation ecosystems of South Korea offset 3.3 % of anthropogenic emissions as a net carbon sink. Latitudinal and topographical gradients over the total simulation area were found for all estimates. In addition, the estimates varied between seasons and years, especially in estimates for biomass growth and carbon uptake, because of variations in the weather conditions. Finally, model validation was conducted using measured soil efflux and flux measurement data from the Gwangneung experimental forest (GEF). The estimated SR accounted for 81.6 % of the observed SR at the GEF site (P < 0.005). Further, the model accounted well for the observed phase and amplitude of changes in the summer and autumn seasons.     

Estimation of forest carbon budget from land cover change in South and North Korea between 1981 and 2010

This paper quantified carbon budget in the past 30 years (1981–2010) and identified the impact of land cover change on carbon dynamics using vegetation integrated simulator for trace gases (VISIT) model. North Korea was converted from carbon sink to source with 10.72 ± 5.18 Tg C yr^?1 of net ecosystem production (NEP) in the 1980s, 3.00 ± 7.96 Tg C yr^?1 in the 1990s, and ?0.46 ± 5.13 Tg C yr^?1 in the 2000s. NEP in South Korea was 10.55 ± 1.09 Tg C yr^?1 in the 1980s, 10.47 ± 7.28 Tg C yr^?1 in the 1990s, and 6.32 ± 5.02 Tg C yr^?1 in the 2000s, showing a gradual decline. In North Korea, NEP was decreased by 0.52 Tg yr^?1 in the 1990s due to reduction of forest, and increased by 0.36 Tg yr^?1 in the 2000s due to expansion of cropland. In South Korea, it was decreased by 0.24 Tg yr^?1 in the 1990s as urban and built-up area expanded, and increased by 0.04 Tg yr^?1 in the 2000s with the expansion of forest. These results suggest the importance of forest and land cover management against deforestation for ensuring national carbon balance.     

一种加工型马铃薯品种的农杆菌转化体系研究

大西洋马铃薯是经济价值很高的炸片型加工品种,逆境胁迫下,易产生褐变、空心等问题,影响加工品质。为获取抗逆境胁迫的优质转基因新品种,采用根癌农杆菌介导法,以大西洋马铃薯的茎段为外植体,建立了快速,简便,高效的遗传转化体系。从共培养到转化植株获得只需7-8周,转化频率达80%。结果表明茎段是较好的转化受体,硫代硫酸银可以有效促进不定芽分化并提高再生频率。PCR、Southern杂交分析证明外源基因已经成功整合到马铃薯再生植株的基因组中。该转化体系为大量开发转基因马铃薯植株,进而筛选优质的马铃薯炸片加工型新品种奠定基础。     

Estimation of effective plant area index for South Korean forests using LiDAR system

Light Detection and Ranging (LiDAR) systems can be used to estimate both vertical and horizontal forest structure. Woody components, the leaves of trees and the understory can be described with high precision, using geo-registered 3D-points. Based on this concept, the Effective Plant Area Indices (PAI_e) for areas of Korean Pine (Pinus koraiensis), Japanese Larch (Larix leptolepis) and Oak (Quercus spp.) were estimated by calculating the ratio of intercepted and incident LIDAR laser rays for the canopies of the three forest types. Initially, the canopy gap fraction (G _LiDAR ) was generated by extracting the LiDAR data reflected from the canopy surface, or inner canopy area, using k-means statistics. The LiDAR-derived PAI_e was then estimated by using G _LIDAR with the Beer-Lambert law. A comparison of the LiDAR-derived and field-derived PAI_e revealed the coefficients of determination for Korean Pine, Japanese Larch and Oak to be 0.82, 0.64 and 0.59, respectively. These differences between field-based and LIDAR-based PAI_e for the different forest types were attributed to the amount of leaves and branches in the forest stands. The absence of leaves, in the case of both Larch and Oak, meant that the LiDAR pulses were only reflected from branches. The probability that the LiDAR pulses are reflected from bare branches is low as compared to the reflection from branches with a high leaf density. This is because the size of the branch is smaller than the resolution across and along the 1 meter LIDAR laser track. Therefore, a better predictive accuracy would be expected for the model if the study would be repeated in late spring when the shoots and leaves of the deciduous trees begin to appear.     

干旱胁迫下转基因甘薯块根膨大期水分利用效率和生理代谢特征

以转Cu/Zn-SOD和APX基因及其非转基因甘薯进行盆栽试验,在甘薯块根膨大期进行正常供水(田间最大持水量的80%)、中度缺水(田间最大持水量的60%)和重度缺水(田间最大持水量的40%)3种水分处理,分别测定转基因植株和对照植株在薯块膨大期的第20天和第70天的抗氧化酶系统、可溶性糖含量、光合系统之间的差异,以及在不同水分胁迫处理下产量和水分利用效率之间的差异。以此研究外源基因的超表达是否可以提高甘薯的产量及水分利用效率。结果显示:(1)转基因甘薯(TS)的SOD、APX活性以及可溶性糖含量均高于非转基因对照株(NT),但POD活性低于NT;TS和NT植株的APX活性、可溶性糖含量、净光合速率以及蒸腾速率均随干旱胁迫加重呈递减趋势。(2)干旱胁迫70d时,TS和NT植株光合参数均较胁迫20d时降低,且TS和NT间的净光合速率没有明显差异。(3)TS和NT两株系的块根产量在中度胁迫下最高而在重度胁迫下最低,而TS具有较高的块根产量且在重度胁迫下产量降低幅度较小。(4)TS的气孔导度和蒸腾速率显著低于NT,且TS的水分利用效率较NT更高。研究表明,Cu/Zn-SOD和APX基因可以显著增加干旱胁迫下甘薯块根膨大期的SOD、APX活性和可溶性糖含量,提高其水分利用效率,从而减轻干旱胁迫对产量的影响。     

Spatio-temporal change in forest cover and carbon storage considering actual and potential forest cover in South Korea

This study analyzes change in carbon storage by applying forest growth models and final cutting age to actual and potential forest cover for six major tree species in South Korea. Using National Forest Inventory data, the growth models were developed to estimate mean diameter at breast height, tree height, and number of trees for Pinus densiflora, Pinus koraiensis, Pinus rigida, Larix kaempferi, Castanea crenata and Quercus spp. stands. We assumed that actual forest cover in a forest type map will change into potential forest covers according to the Hydrological and Thermal Analogy Groups model. When actual forest cover reaches the final cutting age, forest volume and carbon storage are estimated by changed forest cover and its growth model. Forest volume between 2010 and 2110 would increase from 126.73 to 157.33 m3 hm-2. Our results also show that forest cover, volume, and carbon storage could abruptly change by 2060. This is attributed to the fact that most forests are presumed to reach final cutting age. To avoid such dramatic change, a regeneration and yield control scheme should be prepared and implemented in a way that ensures balance in forest practice and yield.     

转铜/锌超氧化物歧化酶和抗坏血酸过氧化物酶基因马铃薯的耐氧化和耐盐性研究

高盐等逆境可以加剧植物体内活性氧的产生,进而引起植物细胞死亡。为开发抗逆境作物,以置于氧化诱导型启动子下定位于叶绿体的转铜/锌超氧化物歧化酶（Cu/ZnSOD）和抗坏血酸过氧化物酶基因(APX)马铃薯为材料,研究了其对MV和 NaCl所引起的氧化胁迫的耐受性。结果表明, MV胁迫下,转基因马铃薯叶片膜的相对电导率明显低于对照; NaCl胁迫下,其叶绿素含量高于对照。 在含NaCl 的培养基上,转基因幼苗生根率明显大于对照。另外,NaCl胁迫下转基因马铃薯叶片的SOD和APX酶活性显著高于对照,与其耐盐性的提高相一致。这些研究表明,转入Cu/ZnSOD和APX基因的马铃薯清除活性氧的能力增强,抗逆性得到提高。本实验采用氧化诱导型启动子调控下的SOD和APX两个基因协同作用,使外源基因只有在逆境胁迫时才特异性表达,增强转基因植株的抗逆效果,为培育抗逆经济作物开阔了思路。     

Estimating stem volume and biomass of Pinus koraiensis using LiDAR data

The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R ² = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R ² = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R ² = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm³), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI).