土地利用方式下土壤有机碳特征及影响因素——以后寨河喀斯特小流域为例

为研究喀斯特小流域土壤有机碳空间分布与土地利用之间的关系,基于网格法在后寨河流域挖掘了2 755个土壤剖面,并采集了22 057个土壤样品。分析了后寨河流域不同土地利用方式下土壤有机碳密度特征。结果表明：后寨河流域土壤有机碳密度主要受人为干扰、土壤厚度与岩石裸露率的制约。不同利用方式土壤有机碳密度（0~100 cm）总体上呈现以下规律：水田>旱地>经果林地>园地>草地>弃耕地>坡耕地>乔灌木林地>乔木林地>荒地>灌木林地>灌草地。后寨河流域100 cm土壤有机碳平均碳密度为8.70 kg/m²,低于中国土壤有机碳平均密度10.83 kg/m²,总有机碳储量为5.39×10⁸ kg。科学合理地进行土地利用方式调整与管理,可以增大喀斯特小流域土壤有机碳储量。     

专家笔谈：资源环境热点问题

重大的资源开发利用工程建设设想或实施往往容易引起社会各界的广泛关注。如何正确认识和科学评价各种资源环境热点问题是大家讨论的重点。文章认为任何重大资源开发工程必须遵循自然规律、生态规律、资源规律和经济规律,必须结合国家战略需求和地缘政治关系,开展前期深入的系统性综合调查,进行生态安全与资源工程安全评价和交叉学科论证,并对其科学价值、社会价值和经济价值等做出正确的判断。建议：未来的资源环境工程建设要谨防“大跃进”,要科学认识自然资源系统规律,守护好美丽的地球家园;要切实履行资源科学家的社会责任,提倡基于科学研究和科学态度的学术争鸣,科学问题最好还是由科学家去讨论;一些争议大的科研课题慎用公益性研发经费来支持。     

典型铅锌矿化区不同土地利用类型土壤重金属污染特征与评价

选取云南者海典型铅锌矿区周边冶炼区（A）、粮食主产区（B）、保护区（C）三个区域土壤为研究对象,分析三个区域内林地（LD）和耕地（GD）土壤pH、总碳（TC）、总氮（TN）、总磷（TP）和5种重金属（Hg、Cd、Pb、Zn、Cu）含量,利用典范对应分析（CCA）研究不同土地利用类型下它们之间的关系,基于系统熵值与重金属生物毒性改进灰色聚类评价法对研究区重金属污染程度进行评价。结果表明,A、B、C三区土壤的5种重金属均超过云南省土壤背景值,且含量A区 > B区 > C区,所有土壤样品Hg、Cd、Pb、Zn、Cu平均含量分别为7.24、1.53、1 794、2 892、210 mg/kg;LD土壤重金属含量普遍高于GD。研究区土壤pH总体呈弱酸性,但A区土壤受矿业活动影响呈弱碱性。TC、TN含量和C/N值均表现出LD大于GD,但TP含量表现为GD显著大于LD （P<0.05）。CCA分析表明LD和GD土壤pH与Cd和Cu呈负相关,与Zn和Pb呈正相关,且pH对重金属含量的影响最大;TC、TP与重金属Cd和Cu在LD土壤中呈正相关,在GD土壤中呈负相关。改进灰色聚类评价结果表明重金属污染程度均表现为LD大于GD;A区污染最严重且均呈重度污染,B区次之,C区污染程度最轻。经比较本文改进的灰色聚类评价法在准确性和灵敏度方面优于传统方法。     

Land Degradation Monitoring in Namibia: A First Approximation

This paper presents development of a first approximation of a Namibian, national level, land degradation monitoring system. The process involved a large number of stakeholders and led to the definition of four primary indicators that were regarded as related to land degradation in Namibia: population pressure, livestock pressure, seasonal rainfall and erosion hazards. These indicators were calculated annually for the period 1971–1997. Annual land degradation risk maps were produced for the same period by combining the indicators. A time series analysis of results generated by indicators was undertaken at two sites. The analysis revealed a general trend towards an increased land degradation risk over the period 1971–1997. A decrease in annual rainfall and an increase in livestock numbers caused this negative trend at one site, while decreased annual rainfall and increased human population were the causes at a second site. Evaluation of resulting maps through direct field observations and long-term monitoring at selected study sites with different conditions relevant for the indicators defined, is an essential next step.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

The Impact of Landsat Satellite Monitoring on Conservation Biology

Landsat 7s recent malfunctioning will result in significant gaps in long-term satellite monitoring of Earth, affecting not only the research of the Earth science community but also conservation users of these data. To determine whether or how important Landsat monitoring is for conservation and natural resource management, we reviewed the Landsat programs history with special emphasis on the development of user groups. We also conducted a bibliographic search to determine the extent to which conservation research has been based on Landsat data. Conservation biologists were not an early user group of Landsat data because a) biologists lacked technical capacity – computers and software – to analyze these data; b) Landsats 1980s commercialization rendered images too costly for biologists budgets; and c) the broad-scale disciplines of conservation biology and landscape ecology did not develop until the mid-to-late 1980s. All these conditions had changed by the 1990s and Landsat imagery became an important tool for conservation biology. Satellite monitoring and Landsat continuity are mandated by the Land Remote Sensing Act of 1992. This legislation leaves open commercial options. However, past experiments with commercial operations were neither viable nor economical, and severely reduced the quality of monitoring, archiving and data access for academia and the public. Future satellite monitoring programs are essential for conservation and natural resource management, must provide continuity with Landsat, and should be government operated.     

Land User Participation in Developing a Computerised Decision Support System for Combating Desertification

Combating desertification in natural rangelands has recently become a priority in large parts of southern Africa. Rangeland managers, farmers, scientists, conservationists and land users have been applying a variety of restoration technologies to address this problem. Bush encroachment, as part of the desertification process, involves the natural replacement of the herbaceous plant cover by undesirable problem woody species. The active and passive restoration technologies that are applied, are mainly based on indigenous knowledge and include the chemical, mechanical or manual reclamation of unproductive rangelands, as well as the combating of woody and alien species encroachment. Indigenous practices and knowledge play a major role in the effectiveness and success rate of these technologies. This project faces the challenge of bringing together both local and scientific knowledge in a single user-friendly, computerised Decision Support System (DSS) which is directly accessible by land users to support them in the process of decision making, concerning the combating of desertification. Case studies from central and northern Namibia were used to combine qualitative and quantitative data to develop this Decision Support System. The DSS currently consists of two databases and an expert system, which evaluates the results of land users’ management practices, and provides easily accessible information and advice for participants in the system, based on the incorporated data. The DSS is also linked to national and international web sites and databases to offer a wider range of information on technologies concerning agricultural and conservation practices.