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.     

Leader–member exchange,organizational identification,and knowledge hiding: The moderating role of relative leader–member exchange

In this article, we sought to identify a new interpersonal antecedent of knowledge hiding, namely, leader–member exchange (LMX). Drawing on the group engagement model (an extension of social identity theory within the group/organization context), we built a theoretical model linking LMX and knowledge hiding. This model focuses on the mediating role of organizational identification and the moderating role of relative LMX in influencing the mediation. Using two time‐lagged studies (Study 1: n = 317; Study 2: n = 248) conducted in China, we examined our research model. Study 1 provided support for the proposed hypotheses for evasive hiding and playing dumb but not for rationalized hiding. Study 2 replicated and extended our findings. Results revealed that (a) LMX was negatively related to evasive hiding and playing dumb but not to rationalized hiding; (b) organizational identification mediated the influence of LMX on evasive hiding and playing dumb but not on rationalized hiding; and (c) relative LMX not only moderated the relationship between LMX and organizational identification but also reinforced the indirect effect of LMX on evasive hiding and playing dumb but not on rationalized hiding (via organizational identification). The implications, limitations, and future research directions are also discussed.     

安全疏散中ICT技术应用研究脉络与热点分析

为了研究ICT技术在安全疏散领域的应用现状、演进和热点,以Web of Science核心数据库中有关ICT技术对安全疏散应用研究的科技文献为研究对象,运用CiteSpace软件对文献研究主题和时空分布、研究演进和科研网络以及研究热点和前沿态势进行分析。研究结果表明:ICT技术对安全疏散应用研究可以划分为低潮期、发展期和爆发期3个阶段,形成了3大科研网络版块;随着ICT技术的发展,刊发相关研究的期刊从综合类向专业类拓展,并从火灾科学、交通科学和心理科学等多学科进行了交叉研究;在不同的发展时期,研究侧重点不尽相同,当前以无线传感网络、建筑疏散和导航系统等领域为研究热点,基于研究成果,提出相关研究热点和前沿等建议。     

Evaluation of Local Ecological Knowledge as a Method for Collecting Extensive Data on Animal Abundance

Abstract:  The use of local ecological knowledge (LEK) has been advocated for biodiversity monitoring and management. To date, however, it has been underused in studying wild populations of animals and, particularly, in obtaining quantitative abundance estimates. We evaluated LEK as a tool for collecting extensive data on local animal abundance and population trends. We interviewed shepherds in southeastern Spain, asking them to estimate the local abundance of the terrestrial tortoise Testudo graeca . We quantified reliability of abundance estimates derived from interviews by comparing them with those obtained from standard field-sampling protocols (distance sampling). We also explored the complementarity of these 2 approaches. LEK provided high-quality and low-cost information about both distribution and abundance of T. graeca . Interviews with shepherds yielded abundance estimates in a much wider range than linear transects, which only detected the species in the upper two-thirds of its abundance range. Abundance estimates from both methodologies showed a close relationship. Analysis of confidence intervals indicated local knowledge could be used to estimate mean local abundances and to detect mean population trends. A cost analysis determined that the information derived from LEK was 100 times cheaper than that obtained through linear-transect surveys. Our results should further the use of LEK as a standard tool for sampling the quantitative abundance of a great variety of taxa, particularly when population densities are low and traditional sampling methods are expensive or difficult to implement.     

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.     

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard‐to‐detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts’ assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural‐appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best‐performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola.     

Rubber cultivation and sustainable development in Xishuangbanna,China

SUMMARY

Xishuangbanna in southwest China is a tropical and subtropical region with extraordinary traditional cultures and attractive landscapes. Rubber cultivation is a key production source undergoing rapid growth. It contributes substantially to improvement of the local economic situation and partially replaces traditional slash-and-burn agriculture in the uplands, but it also results in biodiversity loss and environmental degradation and disturbs the peaceful life of the indigenous people. We discuss the traditional ecological knowledge (TEK) preserved in daily practices and the present types of rubber plantations and suggest the application of TEK, in particular, the indigenous land-use experience to rubber cultivation, in order to promote sustainability in local economic development and ecological well-being.