Technical efficiency analysis of the conversion of cropland to forestland program in Jiangxi,Shaanxi, and Sichuan

Conversion of Cropland to Forestland Program (CCFP) has greatly impacted China’s agricultural sector, and more specifically rural farmers. While changes in living standards as a result of the implementation of the CCFP have been analyzed, little research has been conducted regarding the impacts of such policies on farming operations. As agriculture contributes nearly 10% of national GDP, it is important to analyze the implications of policies on a national industry. An input-oriented data envelopment analysis (DEA) model was used to examine the technical efficiency of farming operations following implementation of the CCFP, using survey data from farmers in Jiangxi, Shaanxi, and Sichuan provinces. Additionally, the impact of factors such as urbanization, age and education, and land fragmentation was examined with respect to farming operational efficiency. Scale inefficiency was found to have the greatest effect on overall inefficiency in farming operations in comparison to pure technical inefficiency, which was largely influenced by the presence and degree of land fragmentation of land holdings. Findings can be used to inform national land-use policies facilitating land fragmentation in China and address gaps in existing broader level studies that utilize non-parametric approaches to examine the technical efficiency of Chinese farmers affected by the CCFP.     

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

A Multidisciplinary Decision Support System for Forest Fire Crisis Management

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The systems architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.     

信息融合技术在锅炉故障诊断中的应用

为满足锅炉故障诊断的要求，用信息融合技术，提出了具有数据挖掘功能的锅炉故障诊断系统的一般模型。在对锅炉故障诊断中的信息进行分类的基础上，详细阐述了模型中各功能模块的作用以及它们之间的层次关系，并提出了模型中关键技术的实现方法。实例分析表明，信息融合技术用于锅炉故障诊断对提高诊断的可靠性和准确性有重要作用。     

Discussion of the paper “Cost effective policies for alternative distributions of stochastic water pollution” by Gren, Destouni and Tempone

This discussion addresses some aspects of a recent paper appearing in this journal which investigates cost effective coastal water management based on different assumptions of the probability distributions (normal and log-normal) of pollutant transport. We also suggest an alternative approach to overcome the technical problems of using the theoretical correct distribution for characterising environmental data (log-normal) within a probabilistic programming framework.     

SELECTION OF WASTE DISPOSAL SITES USING GIS1

ABSTRACT: Geographic Information Systems (GIS) technology is used to identify candidate sites for a solid waste disposal facility in the Gölbasi region of Turkey that has suffered from the negative impact of a current but poorly-located open-dump site on the environment. The municipality of Gölbasi has noticed its deleterious effect on the environment, and has thus decided to dismiss this open-dump site and search for new landfill sites. In this study, the procedure followed under a GIS framework rejects the unacceptable sites considering environmental factors exclusively, other than economic and political issues, contained in the form of multiple layers of attribute information to select the candidate sites for landfilling wastes through an overlay analysis performed by GIS software, ARC/INFO V 7.1. For the spatial data requirements of GIS, a number of thematic map layers (ground water, wetlands and swamp areas, surface water, roads, topographic contours, ecological features, settlements, erosion susceptibility zones, and soil type) are prepared in digital form. In this application, GIS is considered as a screening tool in a site selection process to narrow the number of candidate sites, subsequently leading to one or more sites for detailed investigation. Preliminary ranking for a group of potential sites is done on the basis of simple calculations coupled with on-site field studies.     

USING UNCENSORED TRACE-LEVEL MEASUREMENTS TO DETECT TRENDS IN GROUND WATER CONTAMINATION1

ABSTRACT: Environmental decision making involving trace-levels of contaminants can be complicated by censoring, the practice of reporting concentrations either as less than the limit of detection (LOD) or as not detected (ND) when a test result is less than the LOD. Censoring can result in data series that are difficult to meaningfully summarize, graph, and analyze through traditional statistical methods. In spite of the relatively large measurement errors associated with test results below the LOD, simple and meaningful analyses can be carried out that provide valuable information not available if data are censored. For example, an indication of increasing levels of contamination at the fringe of a plume can act as an early warning signal to trigger further study, an increased sampling frequency, or a higher level of remediation at the source. This paper involves the application of nonparametric trend analyses to uncensored trace-level groundwater monitoring data collected between March 1991 and August 1994 on dissolved arsenic and chromium for seven wells at an industrial site in New York.     

ERRORS RELATED TO RANDOM STREAM TEMPERATURE DATA COLLECTION IN UPPER MISSISSIPPI RIVER WATERSHED1

ABSTRACT: Records of hourly water temperatures for two streams in the Upper Mississippi River basin were used to find the error between instantaneous measurements of stream water temperatures and true daily averages. The instantaneous summer water temperature measurements were assumed to be collected during daylight hours, and measurement times were selected randomly. The absolute error at the 95 percent confidence level of randomly collected stream water temperatures was less than 0.9°C for a 1 to 5m deep large river, but as large as 3.6°C for a 0.3 to lm deep small stream. Temperature readings of morning samples were usually below daily average values, and afternoon readings were usually above. Daily mean water temperatures were obtained with less than 0.23°C standard deviation from true daily averages if the daily maximum and minimum water temperatures were averaged. Sample results were obtained for the open water (summer) season only, since diurnal water temperature fluctuations in ice covered streams are usually negligible.     

Geographic information systems within the national health service: the scope for implementation

The paper starts by assessing some of the needs for information management within the health service in Great Britain. Geographic Information Systems are introduced, and some of the functions such as database management, networking and overlying are described. Principally, it is argued that GIS can fill the role as a health information system, resource management system, and has the potential to assist in family practitioner monitoring and epidemiological studies.