峰丛和洼地喀斯特地形定量对比(英文)

This study presented a quantitative comparison of cockpit and doline karst by examining the numbers and characteristics of typical types of landform entities that are developed in Guilin(Guangxi, China), La Alianza(PR, USA), Avalton(KY, USA), and Oolitic(IN, USA). Five types of landform entities were defined: isolated hill(IH), clustered hills(CHs), isolated sinkhole(IS), clustered sinkholes(CSs), and clustered hills with sinkholes(CHSs). An algorithm was developed to automatically identify these types of landform entities by examining the contour lines on topographic maps of two cockpit karst areas(Guilin and La Alianza) and two doline karst areas(Oolitic and Avalton). Within each specific study area, the CHSs is the least developed type yet with a larger size and higher relief. The IH and IS entities are smaller in size, lower in relief, and outnumber their clustered counterparts. The total numbers of these types of entities are quite different in cockpit and doline karst areas. Doline karst is characterized by more negative(IS and CSs) than positive(IH and IHs) landforms and vice versa for cockpit karst. For example, the Guilin study area has 1192 positive landform entities in total, which occupy 9.81% of the total study area. It has only 622 negative landform entities occupying only 3.91% of the total study area. By contrast, the doline karst in Oolitic has 130 negative while only 10 positive landform entities. The positive and negative landforms in Oolitic occupy 12.68% and 2.61% of the total study area, respectively. Furthermore, average relief and slope of the landform entities are much higher and steeper in the cockpit karst than the doline karst areas. For instance, the average slope of CHs in Alvaton is 3.90 degrees while it is 19.78 degrees in La Alianza. The average relief of CSs is 4.07 m and 34.29 m in Oolitic and Guilin respectively. Such a difference within a specific area or between the cockpit and doline karst may reveal different controls on the development of karst landscape.     

黔桂喀斯特山区植被变化及其地形效应

为科学认识喀斯特山区植被变化及其地形效应,基于MODIS NDVI数据,采用统计学方法,系统分析2000-2016年喀斯特山区植被变化的时空特征及其与海拔、地形起伏度、坡度、坡向的关系。研究表明,黔桂喀斯特山区植被绿度中部高,西北及东南较低,年均NDVI随海拔和地形起伏度的增加呈单峰曲线变化,峰值位于400~600 m,NDVI随坡度和坡向的变化不明显;2000-2016年大部分地区NDVI呈增长趋势,其中超过20%的地区呈显著增长（P<0.05）,年均增长率约0.0018。西部和东南部绿化趋势最为显著,仅在东北和中东部,NDVI呈下降趋势;NDVI呈增长趋势的比例随海拔的增加而增加,说明该喀斯特山区近年来植被恢复向着良性化方向发展,高海拔植被恢复速率更快,低海拔缓坡处的植被生态建设需要进一步加强。     

重庆市岩溶泉发育特征与流量控制机制分析

为给岩溶山区的经济发展和居民的生产生活提供水资源保障,论文以重庆市为例,通过查明重庆岩溶泉及其流量的发育规律和控制机制,利用1∶200000区域水文地质图和水文地质普查报告,运用水文地质勘查、统计分析和ArcGIS的空间分析等手段,在分析岩溶发育特征的基础上,分析地形地貌、地层岩性、地质构造和地表水系等因素对岩溶泉发育、分布及其流量的影响。结果表明：地势起伏度范围在0~200 m时最有利于岩溶泉的发育,随着地势起伏度的增加,岩溶泉平均流量开始逐渐减少;碳酸盐岩与碎屑岩岩组岩溶泉发育密度最大,其次为灰岩与白云岩互层岩组、灰岩岩组、白云岩岩组;构造复合部位、背斜缓翼、向斜轴部、断裂构造等地质构造部位均有利于岩溶泉发育;以岩溶水水动力特征及其与当地侵蚀基准面的相互关系为依据,将重庆市的岩溶大泉划分为以下3种类型：河床型、河岸型、河源型,而岩溶大泉分布数量由多到少分别为河岸型>河源型>河床型。     

基于Strahler面积—高程分析的云南石林县域喀斯特地貌演化的量化研究

基于异质性喀斯特地貌结构与喀斯特保护地整体保护利用的关系,将水平蚀低垂直加深的喀斯特地貌发育机制落实于地理信息系统支持的Strahler面积—高程分析,形成整体、海拔段和内部洼地的面积—高程曲线与积分值指标组,以量化石林县域喀斯特地貌演化。结果表明不同地貌发育特征的不同地形面具有不同的Strahler值,其差异和规律性有一定的指示价值。石林县四级海拔梯级地貌处于壮年晚期,为断裂切割与巴江侵蚀基准面差异性控制下的孤丘夷平面分解,属同期异构的回春型地貌区。> 2100 m海拔段为孤丘夷平构造侵蚀溶原中山,洼地不发育。1900~2100 m海拔段为孤丘夷平面转向孤丘溶原洼地、峰丛洼地,暗河不发育。1700~1900 m海拔段为溶丘洼地斜坡,由蚀余状石林—剑状石林—覆盖石林—烘烤石林组成的石林垂直层状结构与溶丘—洼地—暗河—泉群—河谷盆地组成的水平梯级地貌结构,它是水平与垂直地貌过程的融合产物。石林发育区既为水源形成区,也为水土流失区。这是石林保护地整体保护利用的地貌动力依据。     

温室气体排放评价指标及其定量分析

Anthropogenic greenhouse gases （GHG） emission and related global warming issues have been the focus of international communities for some time. The international communities have reached a consensus to reduce anthropogenic GHG emissions and restrain global warming. The quantitative assessment of anthropogenic GHG emissions is the scientific basis to find out the status of global GHG emission, identify the commitments of each country, and arrange the international efforts of GHG emission reduction. Currently the main assessment indicators for GHG emission include national indicator, per capita indicator, per GDP indicator, and international trade indicator etc. The introduction to the above indi- cators is put forward and their merits and demerits are analyzed. Based on the GHG emission data from the World Resource Institute （WRI）, the US Energy Information Administration （EIA）, and the Carbon Dioxide Information Analysis Center （CDIAC）, the results of each indictor are calculated for the world, for the eight G8 industrialized countries （USA, UK, Canada, Japan, Germany, France, Italy and Russia）, and the five major developing countries including China, Brazil, India, South Africa and Mexico. The paper points out that all these indicators have some limitations. The Indicator of Industrialized Accumulative Emission per Capita （IAEC） is put forward as the equitable indicator to evaluate the industrialized historical accumulative emission per capita of every country. IAEC indicator can reflect the economic achievement of GHG emission enjoyed by the current generations in every country and their commitments. The analysis of IAEC indicates that the historical accumulative emission per capita in indus- trialized countries such as UK and USA were typically higher than those of the world average and the developing countries. Emission indicator per capita per GDP, consumptive emission indicator and survival emission indicator are also put forward and discussed in the paper.     

A quantitative comparison and analysis on the assessment indicators of greenhouse gases emission

Anthropogenic greenhouse gases (GHG) emission and related global warming issues have been the focus of international communities for some time. The international communities have reached a consensus to reduce anthropogenic GHG emissions and restrain global warming. The quantitative assessment of anthropogenic GHG emissions is the scientific basis to find out the status of global GHG emission, identify the commitments of each country, and arrange the international efforts of GHG emission reduction. Currently the main assessment indicators for GHG emission include national indicator, per capita indicator, per GDP indicator, and international trade indicator etc. The introduction to the above indicators is put forward and their merits and demerits are analyzed. Based on the GHG emission data from the World Resource Institute (WRI), the US Energy Information Administration (EIA), and the Carbon Dioxide Information Analysis Center (CDIAC), the results of each indictor are calculated for the world, for the eight G8 industrialized countries (USA, UK, Canada, Japan, Germany, France, Italy and Russia), and the five major developing countries including China, Brazil, India, South Africa and Mexico. The paper points out that all these indicators have some limitations. The Indicator of Industrialized Accumulative Emission per Capita (IAEC) is put forward as the equitable indicator to evaluate the industrialized historical accumulative emission per capita of every country. IAEC indicator can reflect the economic achievement of GHG emission enjoyed by the current generations in every country and their commitments. The analysis of IAEC indicates that the historical accumulative emission per capita in industrialized countries such as UK and USA were typically higher than those of the world average and the developing countries. Emission indicator per capita per GDP, consumptive emission indicator and survival emission indicator are also put forward and discussed in the paper.     

植被恢复不同阶段下喀斯特土壤微生物群落结构及活性的变化——以云南石林景区为例

为了探讨植被恢复对喀斯特土壤生化特性的影响,对云南石林景区植被恢复演替下土壤养分、微生物群落结构及活性进行了比较研究。结果表明,相对于裸露地,植被恢复显著地提高了土壤养分、微生物量碳、微生物活性、微生物商、细菌种丰富度及基因多样性;相对于对照原始林,植被恢复演替下土壤总有机碳、总氮、微生物量碳、基础呼吸和诱导呼吸的恢复程度分别为32%～83%、36%～70%、54%～89%、58%～82%和35%～51%;对照林与植被恢复演替下土壤细菌群落结构之间的相似性遵循如下趋势:裸露地(稀)草地灌丛。总体上,自然恢复方式(草地和灌丛)提高土壤质量效果优于人工恢复方式(柏树林);从裸露地到稀草地恢复过程中,土壤质量提高尤为迅速,为退化喀斯特土壤生态系统进一步恢复改善了条件。     

Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging

Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R² for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected.