Design,management, and key accomplishments of a coordinated environmental research program on acidic deposition

The present and potential adverse effects of the atmospheric input of acidic and acidifying substances on the environment have been of significant public and scientific concern for the past several decades. This article describes the background, design, implementation, and major accomplishments of a 6-yr integrated multidisciplinary environmental research program designed to address the issue of the regional scale consequences of acidic deposition on the environment and human health in Alberta. The research program was called the Acid Deposition Research Program (ADRP) and was a cooperative undertaking between industry, the Energy Resources Conservation Board, and the government of Alberta, Canada. The research effort was designed and guided by two external science advisory boards, biophysical and human health, to maintain objectivity and continuity from beginning to end. Public input was sought, encouraged, and ensured by a public advisory board. The major conclusions of the ADRP are presented as well as observations on the needs of future integrated multidisciplinary research programs.     

A PROGRAM TO CALCULATE CHANNEL SCOUR AND FILL1

ABSTRACT: A computer program written in BASIC calculates net changes in stream channel cross-sections. Calculations are based on dividing the channel cross-section into discrete regions of scour and fill. Internal boundaries of these regions (along the x-axis of the cross-section) are determined by the location of vertical depth measurements taken at two distinct times. The right and left boundaries of the cross-section can be specified so that scour or fill can be calculated for any portion of the profile desired.     

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。     

B2B再循环物流网络优化模型研究

行业特性和技术约束致使一些制造企业产生大量的副产品和边角废料,对环境造成巨大压力.而可持续发展要求则促使制造企业寻求一种与自然生态环境和谐共处、资源良性循环的物流模式,构建再循环物流系统.因此,为了有效解决经济发展与环境的矛盾,促进产业间或产业内工业企业进行循环经济实践,设计具有生态柔性的B2B网络下再循环物流系统的结构模型.运用环境影响分析模型,分析再循环物流系统各个业务单元的环境影响因子.基于结构模型,运用混合整数规划方法,构建再循环物流系统多目标优化模型.该模型同时考虑了再循环系统的物流成本和外部环境影响;适合于多物料、单周期、有产能限制的再循环网络设施选址-分配问题.通过算例验证了模型的有效性.      

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.      

对“三北”防护林体系工程的思考与展望

“三北”防护林体系工程是一项宏伟的工程,她不仅是中国生态环境建设的伟大创举,也是全球生态环境建设的重要组成部分。始于1978年的这项生态工程,23年来累计造林保存面积2203.72×104hm₂,“三北”地区的森林覆盖率已从工程开始实施时的5.05%提高到目前的9%,一些重点地区的区域性防护林体系已初具规模,生态效益、经济效益、社会效益都有了不同程度的提高。这一工程体系突破了传统的单一模式,实行带、片、网相结合,人工造林、飞播造林、封山封沙育林相结合,造(林)、封(育)、管(护)相结合,丰富了防护林体系建设的科学内涵。21世纪前50年是“三北”防护林体系建设的攻坚期,也是决战期,必须重视科技成果的推广运用,加快工程建设步伐,并采取切实措施巩固建设成果。     

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...