JSEM: A Framework for Identifying and Evaluating Indicators

There are two issues in indicator development that have not been adequately addressed: (1) how to select an optimal combination of potentially redundant indicators that together best represent an endpoint, given cost constraints; (2) how to identify and evaluate indicators when the endpoint is unmeasured. This paper presents an approach to identifying and evaluating combinations of indicators when the mathematical relationships between the indicators and an endpoint may not be quantified, a limitation common to many ecological assessments. The approach uses the framework of Structural Equation Modeling (SEM), which combines path analysis withmeasurement models, to formalize available informationabout potential indicators and to evaluate their potential adequacy for representing an endpoint. Unlike traditional applications of SEM which require data on all variables, our approach – judgement-based SEM (JSEM) – can utilize expert judgement regarding the strengths and shapes of indicator-endpoint relationships. JSEM is applied in two stages. First, a conceptual model that relates variables in a network of direct and indirect linkages is developed, and is used to identify indicators relevant to an endpoint. Second, an index of indicator strength – i.e., the strength of the relationship between the endpoint and a set of indicators – is calculated from estimates of correlation between the modeled variables, and is used to compare alternative sets of indicators. The second stage is most appropriate for large, long-term assessments. Although JSEM is not a statistical technique, basing JSEM on SEM provides a structure for validating the conceptual model and for refining the index of indicator strength as data become available. Our main objective is to contribute to a rigorous and consistent selection of indicators even when knowledgeabout the ability of indicators to represent an endpoint is limited to expert judgement.     

Monitoring of Biodiversity Indicators in Boreal Forests: a Need for Improved Focus

The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity following forest management. Part of this problem can be attributed to the lack of focused questions for monitoring including absence of null models and predicted effects, a certain level of disconnect between research and management, and recognition that monitoring can be designed as a research question. Considerable research from the past decade has not been adequately synthesized to answer important questions, such as which species or forest attributes might be the best indicators of change. A disproportionate research emphasis has been placed on community ecology, and mostly on a few groups of organisms including arthropods, amphibians, migratory songbirds, and small mammals, while other species, including soil organisms, lichens, bats, raptors, some carnivores, and larger mammals remain less well-known. In most studies of community ecology, the question of what is the importance, if any, of the regularly observed subtle changes in community structures, and causes of observed changes is usually not answered. Hence, our ability to deal with questions of persistence is limited, and demographic research on regionally--defined key species (such as species linked to processes, species whose persistence may be affected, species with large home ranges, species already selected as indicators, and rare and threatened species) is urgently needed. Monitoring programs need to be designed to enable managers to respond to unexpected changes caused by forest management. To do this, management agencies need to articulate null models for monitoring that predict effects, focus fine--scale monitoring on key species (defined by local and regional research) in key habitats (rare, declining, important) across landscapes, and have a protocol in place to adapt management strategies to changes observed. Finally, agencies must have some way to determine and define when a significant change has occurred and to predict the persistence of species; this too should flow from a well--designed null model.     

不同污染指示菌对河流的细菌学评价

以细菌学理论为依据，以湖南沅江常德江段水体为实例，说明了用《地表水环境质量标准》（GHZB 1－1999）中粪大肠菌群指标（FC）和《地面水环境质量标准》（GB 3838－88）中总大肠菌群指标（TC）分别评价河流水体的细菌学质量所存在的差异。     

生态系统健康评价的研究进展

回顾了生态系统健康的概念,阐述了水生态系统健康评价的三种指标体系:指示物种指标体系、结构功能指标体系、V-O-R指标体系.其中,结构功能指标体系从选取指标和指标分类两方面进行了方法归纳,分析了生态系统健康的几种评价方法,以及讨论了生态系统健康研究中存在的问题和发展趋势.     

辽宁省干线公路网络通达性研究

以辽宁省干线公路网络和14个地市、21个主要县市为研究对象,以最短距离原则为基础,选取距离、时间和通达性系数来衡量城市通达性水平的高低;以行车速度为指标,得到不同速度下通达性水平的空间格局;在100km/h的行车速度下,计算一个城市在1h、2h、3h、5h内连接的城市数目,并对通达性水平的特点和空间格局进行分析。结果显示,35个城市的通达性水平呈现出＂同心圈＂结构,＂核心—外围＂模式明显。以沈阳和鞍山为核心,由核心向外围通达性水平逐步降低,且随着行车速度的提高,通达性水平呈现出明显的上升趋势。由于通达水平的提高,在未来的几年里辽宁省将逐渐形成5个交通圈,同时实现＂一个工作日,全省通达＂的目标。     

福州市环境可持续性评价

本文选取2000-2007年福州市城区环境数据,采用压力-状态-响应指标体系,对福州市近8年的环境动态进行可持续性评价。压力因子包括人口、经济和能耗,状态因子包括大气环境、声环境和水环境,响应因子包括污染控制、环境建设和环境管理。结果表明,福州市环境可持续发展能力2000年较差,2001-2002年一般,2003-2007年较好。     

燃料乙醇行业环境污染控制评价指标体系的构建

在分析我国燃料乙醇行业基本信息的基础上,根据其原料特性、生产规模、生产技术、污染控制措施、环境管理等方面的特点,筛选出合适的指标,构建多层次燃料乙醇行业环境污染控制评价指标体系。运用层次分析法确定指标权重分值,建立燃料乙醇行业环境污染控制评价模型,并选取国内燃料乙醇典型企业进行调研,结合行业现状对该指标体系做出合理性和可行性分析。     

区域低碳交通评价模型研究

在中国机动车快速增长的前提下,低碳交通运输是实现节能减排、发展低碳经济的重要组成部分。借鉴戴利的消费和福利绩效公式,基于导向性、数据可获性与可比性等基本原则,构建区域低碳交通评价指标体系,该体系包括低碳交通能效指标和低碳交通运营指标。基于灰关联分析法和模糊数学方法,建立区域低碳交通模糊评价模型。最后,对江苏2010年的低碳交通发展水平进行评价,结果表明,该年江苏低碳交通发展水平为"良",今后发展的重点在于大力发展城市轨道交通、积极开展低碳公路建设、开展碳税制度和优化公交体系等。     

Heavy Metal Distribution in Valley Sediments in Wadi Al-Karak Catchment Area, South Jordan

Valley sediments samples collected from the major and minor valleys of Al-Karak catchment area (southern Jordan) were leached with hot dilute HCl and analysed for their heavy metals content. The results of leachable metal concentrations indicated the absence of anomalous values for metal occurrences. However, appreciable contamination of the sediments with Cu, Zn, Pb, Cd and Cr was observed. Using an index of pollution the extent of contamination was better delineated. The geographical distribution of the samples showed higher Cu, Zn, Pb, Cd and Cr concentrations mainly around heavily inhabited areas indicating an anthropogenic source of contamination. Lithological influence indicated from the anomalies of Fe and Mn was found to be very low.     

滩涂湿地污灌系统生态监测指标体系的研究与构建

对在滩涂湿地建立的生态工业园区进行调查研究,用生态方法和化学成分分析方法对各物种和生物体进行研究,初步构建了滩涂湿地污灌系统生态监测指标体系,期望能够对造纸废水的处理、滩涂湿地的开发利用以及滩涂湿地生态系统起到较好的保护和改善作用,为生态工业园区建设提供较好的安全保障.