Application of GIS technology in chemical emergency response

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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。     

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。     

环境专家系统

本文介绍了国内外环境专家系统的发展状况。环境专家系统成功的应用表明环境专家系统是解决环境问题的一个有力工具，环境专家系统将越来越广泛地应用于环境科学中，环境专家系统与决策支持系统相结合以及将神经网络技术应用于环境专家系统中，是环境专家系统的发展方向，文中还介绍了我们正在研究的大气污染总量控制规划专家系统。     

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.     

Predicting categories of drugs used by suspected drug-impaired drivers using the Drug Evaluation and Classification Program tests

Objective: The purpose of this study was to statistically determine which combination(s) of drug-related signs and symptoms from the Drug Evaluation and Classification (DEC) protocol best predict the drug category used by the suspected drug-impaired driver.

Methods: Data from 1,512 completed DEC evaluations of suspected impaired drivers subsequently found to have ingested central nervous system (CNS) depressants, CNS stimulants, narcotic analgesics, and cannabis were analyzed using a multinomial logistic regression procedure. A set of evaluations completed on drug-free subjects was also included. The relative importance of clinical, behavioral, and observational measures in predicting drug categories responsible for impairment was also examined.

Results: Thirteen drug-related indicators were found to significantly contribute to the prediction of drug category, including being under the care of a doctor or dentist, condition of the eyes, condition of the eyelids, mean pulse rate, assessment of horizontal gaze nystagmus (HGN), convergence, performance on the One Leg Stand (OLS) Test, eyelid tremors, pupil size in darkness, reaction to light, presence of visible injection sites, systolic blood pressure, and muscle tone. Indicators related to the appearance and physiological response of the eye contributed the most to the prediction of drug category, followed closely by clinical indicators and performance on the psychophysical tests.

Conclusions: The findings from this study suggest that drug recognition experts (DREs) should be careful to review a set of key signs and symptoms when determining the category of drug used by suspected drug-impaired drivers. Drug use indicators related to the appearance and physiological response of the eye were found to contribute the most to the prediction of the drug category responsible for the impairment. These results could help form the basis of a core set of indicators that DREs could initially consult to form their opinion of drug influence. This in turn may enhance the validity, effectiveness, and efficiency of drug detection and identification by DREs and lead to a more effective and efficient DEC program, improved enforcement of drug-impaired driving, and greater acceptance of the DEC program by the courts.     

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.     

基于模糊专家系统的垃圾焚烧底灰重金属污染风险评价

垃圾焚烧处理技术可以实现城市生活垃圾减量化,但底灰中重金属的存在与迁移转化会形成持续的潜在风险。针对重金属Cu、Cr、Pb和Cr对环境的潜在风险进行分析,将模糊专家系统引入潜在生态风险指数法中。首先将重金属的富集系数作为输入,然后应用知识库和推理机制来实现重金属对环境危害快速、不确定信息的准确推理,最后对城市生活垃圾焚烧底灰中重金属对环境的潜在风险进行评价。实验结果验证,该方法能够更快速、准确地做出适当的决定,为底灰的安全处置和再利用提供理论基础。