GIS支持下的水文生态效应评价混合型专家系统设计初探

文章从人工神经网络(ANN)、专家系统(ES)各自的优势和不足出发，结合地理信息系统(GIS)技术的特点，介绍了水文生态效应评价的混合型专家系统(HEMES)的基本结构模式和各模块的功能。然后抓住ANN、ES、GIS的共同作用因子一专家知识，从数据库结构、C 类方面探讨了三者集成的问题，并根据集成的思想探讨了相关功能设计。指出HEMES是一种更准确、易操作的评价技术，可作为相关管理、决策者的辅助工具。     

环境专家系统研究进展

对环境专家系统(EES)在环境科学领域的应用进展及其研究的必要性进行了分析。结合近几年来国内外大量的实践案例和相关研究文献。对环境专家系统的发展历史、开发语言，空间分析能力，应用功能等方面的研究状况进行了全面回顾，并针对当前环境专家系统研究及应用的主要领域一环境影响评价专家系统(EIA—ES)进行了系统总结。     

专家系统及其在农业与自然资源管理中的应用

阐述了专家系统的概念及其与传统程序、其它计算机辅助决策的区别，综述了专家系统在农业与自然资源管理中的应用现状及其日益重要的作用，探讨了农业专家系统的发展趋向。     

Empirical Bayes calculations of concordance between endpoints in environmental toxicity experiments

Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum, concordance can reach well above 90%.     

外来有害生物风险评估技术

概述了有害生物风险分析的概念、必要性、生物学基础和一般程序 ;论述了生态气候图、农业气候相似距库、生态气候评价的分析模型、地理信息系统、专家系统、基于定性分析与定量估算相结合的数学模型等有害生物风险分析技术的原理和特点 ;认为应用网络技术 ,建立基于分布式计算的全球入侵物种风险评价数据体系 ,可有效提高风险评价的速度和准确性。     

Statistics: an essential technology in environmental research and management

Statistical methods as developed and used in decision making and scientific research are of recent origin. The logical foundations of statistics are still under discussion and some care is needed in applying the existing methodology and interpreting results. Some pitfalls in statistical data analysis are discussed and the importance of cross examination of data (or exploratory data analysis) before using specific statistical techniques are emphasized. Comments are made on the treatment of outliers, choice of stochastic models, use of multivariate techniques and the choice of software (expert systems) in statistical analysis. The need for developing new methodology with particular relevance to environmental research and policy is stressed.Dr Rao is Eberly Professor of Statistics and Director of the Penn State Center for Multivariate Analysis. He has received PhD and ScD degrees from Cambridge University, and has been awarded numerous honorary doctorates from universities around the world. He is a Fellow of Royal Society, UK; Fellow of Indian National Science Academy; Foreign Honorary Member of American Academy of Arts and Science; Life Fellow of King's College, Cambridge; and Founder Fellow of the Third World Academy of Sciences. He is Honorary Fellow and President of International Statistical Institute, Biometric Society and elected Fellow of the Institute of Mathematical Statistics. He has made outstanding contributions to virtually all important topics of theoretical and applied statistics, and many results bear his name. He has been Editor of Sankhya and theJournal of Multivariate Analysis, and serves on international advisory boards of several professional journals, includingEnvironmetrics and theJournal of Environmental Statistics. This paper is based on the keynote address to the Seventh Annual Conference on Statistics of the United States Environmental Protection Agency.     

Balancing Forest‐Regeneration Probabilities and Maintenance Costs in Dry Grasslands of High Conservation Priority

Abstract: Abandonment of agricultural land has resulted in forest regeneration in species‐rich dry grasslands across European mountain regions and threatens conservation efforts in this vegetation type. To support national conservation strategies, we used a site‐selection algorithm (MARXAN) to find optimum sets of floristic regions (reporting units) that contain grasslands of high conservation priority. We sought optimum sets that would accommodate 136 important dry‐grassland species and that would minimize forest regeneration and costs of management needed to forestall predicted forest regeneration. We did not consider other conservation elements of dry grasslands, such as animal species richness, cultural heritage, and changes due to climate change. Optimal sets that included 95–100% of the dry grassland species encompassed an average of 56–59 floristic regions (standard deviation, SD 5). This is about 15% of approximately 400 floristic regions that contain dry‐grassland sites and translates to 4800–5300 ha of dry grassland out of a total of approximately 23,000 ha for the entire study area. Projected costs to manage the grasslands in these optimum sets ranged from CHF (Swiss francs) 5.2 to 6.0 million/year. This is only 15–20% of the current total estimated cost of approximately CHF30–45 million/year required if all dry grasslands were to be protected. The grasslands of the optimal sets may be viewed as core sites in a national conservation strategy.     

Testing Hypotheses of Bird Extinctions at Rio Palenque,Ecuador, with Informal Species Lists

Abstract: Informally gathered species lists are a potential source of data for conservation biology, but most remain unused because of questions of reliability and statistical issues. We applied two alternative analytical methods (contingency tests and occupancy modeling) to a 35‐year data set (1973–2007) to test hypotheses about local bird extinction. We compiled data from bird lists collected by expert amateurs and professional scientists in a 2‐km² fragment of lowland tropical forest in coastal Ecuador. We tested the effects of the following on local extinction: trophic level, sociality, foraging specialization, light tolerance, geographical range area, and biogeographic source. First we assessed extinction on the basis of the number of years in which a species was not detected on the site and used contingency tests with each factor to compare the frequency of expected and observed extinction events among different species categories. Then we defined four multiyear periods that reflected different stages of deforestation and isolation of the study site and used occupancy modeling to test extinction hypotheses singly and in combination. Both types of analyses supported the biogeographic source hypothesis and the species‐range hypothesis as causes of extinction; however, occupancy modeling indicated the model incorporating all factors except foraging specialization best fit the data.     

Application of GIS technology in chemical emergency response

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基于人误系统复合状态(MSHES)的人误防范理论研究

评析国内外以第一代人因可靠性分析(静态)、第二代人因可靠性分析(动态)为主体形成的人误防范理论和方法;针对目前不能量化人的生理、认知、心理等相关非结构性和非确定性参数和数据的"瓶颈",建立基于人-机-环系统业务流程的人误系统复合状态(Multiplex State ofHumanErrors System,MSHES)结构模型;探求运用粗糙集数据挖掘,对资深专业人员的经验规则信息、人因事故或事件分析的信息,挖掘人因层次结构中的根因与人误层次结构中的差错之间的关联关系,构建基于规则的人误防范专家系统结构模型;探究人的风险性评估和人误防范理论。