土地承载力研究范式的变迁、分化及其综论

基于Kuhn范式理论,将现有土地承载力研究成果显化、梳理为4种主要研究范式,即基于限制因子的研究范式、基于多因素综合的研究范式、基于参照区的研究范式、基于生态足迹的研究范式。以范式应用的时代背景、空间尺度为着眼点,对各类范式进行综合比较,结果显示：基于限制因子的土地承载力研究范式起源最早、发展最为成熟,基于多因素综合、基于参照区、基于生态足迹的3种研究范式,均是以前者为基础,按照不同的方向分化而成;范式分化的原因在于时空条件的变化所引致的亟需解释、解决的现实问题的变化。范式本身并无优劣之分,但有其独特的适应性：基于限制因子、基于生态足迹的两种研究范式适用于全球及国家等大尺度土地承载力问题,且发展较为成熟,其成果具有较强的理论和实践指导意义;基于多因素综合及基于参照区的两种研究范式适用于市县等中小尺度,但其研究较为薄弱,所得的承载力分值、承载力相对值对区域土地管理实践的指导价值有限。当前,市县等中小尺度土地承载力研究亟需加强,其指导实践的有效性与可操作性亟待大幅度提高。     

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。     

深圳市综合水质指数研究及其在水资源资产评估上的应用

自然资源资产评估技术是开展自然资源资产负债表实践和实行环境责任离任审计的重要技术支撑。水资源作为一项重要自然资源,如何有效评估水资源资产是不可回避的问题。论文以深圳市为研究区域,一是采用综合污染指数法和主成分分析法,以总氮、氨氮、总磷、化学需氧量、生化需氧量、固体悬浮物为指标参数构建了深圳市综合水质指数以评价水资源综合水质。二是以该综合水质评估模型为基础,通过采用治污成本法分析综合水质与治污成本间的关系,从而构建深圳市景观水和饮用水资源的价值量评估模型。论文还以深圳市大鹏新区为试点开展了水资源价值量评估,评估结果显示,2015年大鹏新区景观水和饮用水资源的价值量分别为3.60亿、0.35亿元。     

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.