农村环境质量区划的多元分析

本文提出了适合于农村环境质量区划的分区方法，即首先以主成分分析法分析农村环境质量问题，然后以多种聚类分析法取得一个初始分区系统，最后用判别分析法判别该初始分区系统中各区域单元的类型归属是否正确，对一些类型归属不恰当的作适当调整，最终得到农村环境质量分区系统。文章最后讨论了类型划分问题。     

江苏省重要生态功能保护区的分类及建立方法

阐述了重要生态功能保护区的概念,根据江苏省的自然环境特征,论述了江苏省重要生态功能保护区的建立方法及其分类,并提出了重要生态功能保护区的保护和管理措施.     

微生物燃料电池在污水处理中的研究进展

微生物燃料电池（microbial fuel cell，MFC）利用微生物催化剂将其代谢能直接转化为电能，具有原料广泛、反应条件温和、清洁高效等优点。简述了MFC的工作原理及分类，总结了用于污水处理的MFC的性能及其影响因素。探讨了MFC在实际应用中的瓶颈，并展望其在污水处理中的应用前景。     

Evaluation of US EPA Environmental Monitoring and Assessment Program's (EMAP)-Wetlands sampling design and classification

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) will monitor the nation's resources by evaluating the status and trends of selected indicators of condition using a probability-based sampling design. The EMAP-Wetlands program will monitor the condition of the nation's wetlands. The EMAP classification system is an aggregation of the many subclasses of the US Fish and Wildlife Service's National Wetlands Inventory (NWI) classification system. This aggregation results in fewer wetland classes with more wetlands per class than the NWI system. Aggregation of the NWI classification was based primarily on dominant vegetation cover, flooding regimes, dominant water source, and adjacency to rivers and lakes. We evaluated the EMAP classification system and sampling design using NWI digital wetlands data for portions of Illinois, Washington, North Dakota, and South Dakata. Relative numbers of wetlands, total areas, average areas, and common versus rare classes were compared between the EMAP and NWI classification systems. As expected, the EMAP classification provided fewer wetland polygons, each with larger areas, without altering total wetland area. Summary statistics comparing sample estimates to true population parameters (represented by the NWI data) demonstrated the effectiveness of the EMAP sampling design with the exception of rare EMAP classes in the selected regions. Although simple random sampling is inadequate for both large and small wetlands, the EMAP sampling design is readily adapted to provide better estimates for these categories. Aggregating the NWI classification to the EMAP classification provides fewer wetland classes, with more wetlands per class, for EMAP's annual reports and statistical summaries. The research in this report has been funded by the United States Environmental Protection Agency (EPA) under contracts 68-C8-0006 to ManTech Environmental Technology, Inc. and 68-03-3532 to The Bionetics Corporation. Mention of trade names does not constitute endorsement or recommendation for use.     

A Procedure for Making Optimal Selection of Input Variables for Multivariate Environmental Classifications

Abstract:  Multivariate classifications of environmental factors are used as frameworks for conservation management. Although classification performance is likely to be sensitive to choice of input variables, these choices have been subjective in most previous studies. We used the Mantel test on a limited set of sites for which biological data were available to iteratively seek a definition of environmental space (i.e., intersite distances calculated with a set of appropriately transformed and weighted environmental variables) that had maximal correlation with the same sites described in a biological space. The procedure was used to select input variables for a classification of New Zealand's rivers that discriminates variation in fish communities for biodiversity management. The classification performed (i.e., discriminated biological variation) better than classifications with subjectively chosen variables. The inherently linear measures of environmental distance that underlie multivariate environmental classifications mean that they will perform best if they are defined based on variables for which there is a linear variation in the biological community throughout the entire range of the variable. Classification performance will therefore be improved when variables that have nonlinear relationships with biological variation are transformed to make their relationship with biological turnover more linear and when the contributions of environmental factors that have particularly strong relationships with biological variation are increased by weighting. Our results indicate that attention to the manner in which environmental space is defined improves the efficacy of multivariate classification and other techniques in which the environment is used as a surrogate for biological variation.     

Assessing the Threat Status of Ecological Communities

Abstract: Conservationists are increasingly interested in determining the threat status of ecological communities as a key part of their planning efforts. Such assessments are difficult because of conceptual challenges and a lack of generally accepted criteria. We reviewed 12 protocols for assessing the threat status of communities and identified conceptual and operational issues associated with developing a rigorous, transparent, and universal set of criteria for assessing communities, analogous to the International Union for Conservation of Nature (IUCN) Red List standards for species. We examined how each protocol defines a community and its extinction and how each applies 3 overarching criteria: decline in geographic distribution, restricted geographic distribution, and changes to ecological function. The protocols vary widely in threshold values used to assess declines and distribution size and the time frames used to assess declines, leading to inconsistent assessments of threat status. Few of the protocols specify a scale for measuring distribution size, although assessment outcomes are highly sensitive to scale. Protocols that apply different thresholds for species versus communities tend to require greater declines and more restricted distributions for communities than species to be listed in equivalent threat categories. Eleven of the protocols include a reduction in ecological function as a criterion, but almost all assess it qualitatively rather than quantitatively. We argue that criteria should be explicit and repeatable in their concepts, parameters, and scale, applicable to a broad range of communities, and address synergies between types of threats. Such criteria should focus on distribution size, declines in distribution, and changes to key ecological functions, with the latter based on workable proxies for assessing the severity, scope, and immediacy of degradation. Threat categories should be delimited by thresholds that are assessed at standard scales and are logically consistent with the viability of component species and important ecological functions.     

卫星云图样本集的FCM优化调整与云类判别

基于云类样本的红外-可见光二维灰度空间投影,采用模糊聚类方法调整优化云类样本特征区域,消除采样误差。针对常规模糊C均值聚类(FCM)方法在处理上述问题时表现出的局限性,提出用样本特征均值替代FCM中随机初始中心的改进办法,既避免了常规FCM方法对初始中心敏感的缺陷,又可纠正其聚类结果对云类样本特征结构的歪曲。改进后的聚类结果既消除了采样误差,又保持了云类样本的基本特征属性,基于该判据的分类结果可较为准确地分辨出陆地、水体、低云、中云、卷云和积雨云,分割判别效果符合客观实际。     

基于水资源消耗和CODCr排放双调控的我国工业分类研究

从水资源消耗和COD_Cr排放双调控出发,利用2005年各工业部门有关统计数据,基于万元产值水资源消耗和COD_Cr排放强度,将40个工业部门划分为低水资源消耗-低污染工业、高水资源消耗-低污染工业和高水资源消耗-高污染工业3类.基于该分类方案,利用2001—2005年统计数据,对3类工业水资源消耗和COD_Cr排放进行统计分析,结果表明:占工业生产总值30%的高水资源消耗-高污染工业,排放了接近85%的COD_Cr有机物;占工业生产总值40%的高水资源消耗-低污染工业,水资源消耗接近75%;而占工业生产总值30%的低水资源消耗-低污染工业,水资源消耗不到2%,COD_Cr的排放量也低于4%.基于该工业分类方案,建立起工业生产与水资源消耗量和COD_Cr排放量之间的双向联系.      

构建有机化合物斑马鱼雌激素干扰效应的二元分类模型

计算毒理学方法已成为辅助内分泌干扰物(EDCs)管理的决策支持工具。因此,发展内分泌干扰效应指标的(定量)结构活性关系((Q) SAR)等预测模型对于实现EDCs环境管理具有重要的意义。在雌激素受体(Q) SAR模型研究方面,目前主要针对人、牛、大鼠和小鼠等物种的雌激素受体干扰效应进行了研究,而对鱼等水生生物雌激素受体干扰效应等指标的(Q)SAR模型研究还较少。本研究采用基于欧几里德距离的K最近邻(k NN)分类算法,构建了斑马鱼雌激素受体干扰效应的二元分类模型。结果表明,2个最优模型训练集和验证集的预测准确度(Q)、敏感性(Sn)和特异性(Sp)参数均大于0.93,说明模型具有较好的预测能力。因此,能够用所建模型填补模型应用域内其他化合物缺失的斑马鱼雌激素受体干扰效应定性数据。     

1种基于视频的油田危险区域入侵检测智能综合识别技术研究

为解决油田日常生产作业中缺乏危险作业区域的等级划分与自动识别方式以及缺乏人员踏入危险区域的识别方法.提出1种基于视频智能综合识别技术的全天油田危险区域入侵检测算法,该算法首先结合油田危险因素对油田危险区域进行危险等级的划分与危险区域的识别;然后,针对光照条件良好的白天场景,在训练数据集中融合油田作业区视频数据和公开行人...