Carbon dioxide and methane emission from subsurface peatlands and its controlling factors北大核心CSCD

Peatland is an efficient carbon dioxide (CO2) sink on the continent and plays an important role in global carbon cycle. Climate change and human activities, two of the notable global environmental issues, have accelerated the degradation of peatlands during recent years. Global warming will increase the rate of aerobic decomposition in the surface of peatlands. Carbon stored in the subsurface of peatlands will be metabolized if the climatic conditions become favorable for decomposition. This study reviewed the carbon circle of subsurface peatland in natural environment and in environments disturbed by human activity or climate change. Furthermore, the major factors (environmental and human factors) that affect the carbon cycle were also discussed. According to a previous study, subsurface peatland will rapidly participate in the carbon cycle when the peatland is degraded. Water level, vegetation, and temperature were the main natural factors affecting the carbon cycle, whereas drainage, farming, and grazing were the main anthropogenic factors. Further studies should focus on different soil layer carbon dynamics, inorganic carbon content, and conservation and restoration of peatlands. The study methods should be a combination of macro with micro scale and focus on developing deep peat research techniques. Most of the previous studies focused on greenhouse gas emission and their response factors in short-term experiments. Thus, the mechanism and process of subsurface carbon are not clear and needs further study. © 2018 Science Press. All rights reserved.     

流化床垃圾焚烧炉工艺改进的探讨

对流化床垃圾焚烧炉的工艺改进进行了分析 ,在焚烧炉内更有利于脱除酸性气体 ,当垃圾热值达 4 5 0 0kJ/kg时 ,部分吹入氧气可使燃烧温度达 1 30 0℃以上。用空心球代替流动砂可以取消流动砂的循环环节     

Considering climate change and regional differences: An efficiency assessment of coal mine use and land restoration

China is the country with the largest coal mining production and consumption in the world, but due to a large amount of coal burning, air pollution and climate change are exasperating related problems. The previous literature mainly has discussed coal mine production and environmental pollution, but failed to take into account external factors such as climate change and seldom discussed the relationship between coal mine land use and land restoration. Therefore, this study uses the meta-Epsilon-Based Measure two-stage Data Envelopment Analysis under the exogenous model and incorporates coal mine land use and land restoration use into the model to explore the relationship between the two under climate change. The research results are as follows. (1) If the external climate factors are not considered, then the phenomenon of overestimation or underestimation of the technology gap arises. (2) The efficiency value of the coal mining stage in most provinces is generally higher than the land restoration efficiency value.     

河南省人类活动净磷输入的时空变化与影响参数

为探究河南省人类活动净磷输入状况,基于河南省18个省辖市(县辖市)行政单元统计数据,利用人类活动净磷输入量(NAPI)模型,核算河南省1990、1995、2000、2005、2010、2015和2019年人类活动净磷输入量.结果表明:在时间尺度上,1990～2015年河南省NAPI整体呈升高趋势,2015～2019年略...     

中国技术灾害的时序变化与区域差异

近年来,由于生产的全球化、工业水平的迅速提高、技术系统的复杂化和规模化,以及社会结构急剧变化,我国技术灾害的发生频次增多,强度加剧,经济损失趋于上升.技术灾害继自然灾害之后,已逐渐发展为威胁我国人民生命安全和生存环境的主要灾种.基于技术灾害数据库,从致灾因子多度、风险频数、相对损失强度和综合风险指数等4个方面对中国技术灾害的时序变化和区域差异进行了分析与探讨,以期加深对中国技术灾害的系统认识,并为中国技术灾害的风险管理提供依据.     

东南丘陵土地利用变化及驱动力研究--以衡阳市为例

在GIS,Excel, SPSS11.0的支持下,以土地详查数据为依据,对衡阳市1994~2001年的土地利用变化过程进行了全面分析,揭示了衡阳市近七年来土地利用变化的时空特点,并分析了其主要原因。研究表明：(1)衡阳市1994~2001年耕地、未利用地面积总体减少,其他用地均有不同程度增加,土地利用类型变动的总体方向是：农用地和未利用地向建设用地转化,耕地向园地、水域转化,未利用地向林地转化。(2) 衡阳市土地利用变化存在较大的时间和空间差异。时间上1997年前土地利用变化显著,1997年后变化较小;空间上以祁东县和衡阳市区变化较大,衡南县、南岳区变化较小。(3)人口因素、政策因素、经济因素是衡阳市土地利用变化的主要影响因素。1997年前后土地利用变化情况的差异主要由政策因素造就,地形地貌因素及经济因素则主导了区内空间差异的形成。     

DRYING UP OF THE YELLOW RIVER:A RESPONSE TO GLOBAL CLIMATIC CHANGE

Ｉｎｒｅｃｅｎｔｙｅａｒｓ,ａｔｔｅｎｔｉｏｎｈａｓｂｅｅｎｐａｉｄｔｏｇｌｏｂａｌｃｌｉｍａｔｉｃｃｈａｎｇｅ,ａｎｄｃｅｒｔａｉｎｒｅｓｅａｒｃｈｒｅｓｕｌｔｓｈａｖｅｂｅｅｎｍａｄｅｉｎｖａｒｉｏｕｓｒｅｌａｔｅｄｆｉｅｌｄｓ.Ｔｈｅｃｈａｎｇｅｉｎ ｇｌｏｂａｌｃｌｉｍａｔｅｉｓｍａｉｎｌｙｒｅｐｒｅｓｅｎｔｅｄｂｙｔｈｅｗａｒｍｉｎｇｕｐｏｆｇｌｏｂａｌａｉｒｔｅｍｐｅｒａｔｕｒｅ ,ｆｒｅｑｕｅｎｔｏｃｃｕｒｒｅｎｃｅｏｆＥＮＳＯａｎｄａｂｎｏｒｍａｌｉｔｙｉｎａｔｍｏｓｐｈｅｒｉｃｃｉｒ…     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.     

干旱区城市化对生态系统碳库的影响——以乌鲁木齐市为例

城市化是影响区域生态系统碳循环的主要原因,也是评估生态系统碳循环的最大不确定因素。论文利用1990与2010年Landsat TM数据,基于V-I-S城市土地覆被模型和决策树分类法,获得乌鲁木齐土地变化时空格局;结合野外实测数据和文献检索得到研究区不同土地覆被类型的土壤与植被碳密度,估算了城市土地变化对生态系统碳库的影响。结果表明：1）1990—2010年间,乌鲁木齐城市不透水地表（impervious surface areas, ISA）以中部南部内部填充与北部扩张的形式约增加62%,主要占用农田（27%）与荒漠（62%）。2）乌鲁木齐市生态系统碳库主体（95%）分布在土壤中,城市土地覆被变化导致约25%的碳库损失,由农田、裸土/残存荒漠以及城市绿地转变为ISA解释了68%的土壤有机碳和63%的植被碳损失量,其空间分布与ISA的扩张相一致。城市植被及其土壤具有较高的碳密度,合理的城市规划可以抵消部分因土地变化而损失的生态系统碳。