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.     

A causal analysis of time-varying speed camera safety effects based on the propensity score method

Introduction: Speed limit enforcement cameras provide an effective approach to reduce vehicle speeds and the number of road accidents. However, it is still unclear whether the safety effects of speed cameras show durability over long periods of time. This paper analyses how the effects of speed cameras on road accidents change over time. A total number of 771 camera sites and 4787 potential control sites are observed for a period of 18 years (1999–2016) across England. Method: Covariates such as road class, crash history, speed limit, and annual average daily traffic (AADT) are included in the data set. A difference in difference (DID) based propensity score matching (PSM) method is employed to select proper control sites and estimate the treatment effects. The safety effects of speed cameras are then evaluated from a long-term perspective. The post-treatment period is divided into four equal-length periods: early, medium 1 and 2, and late. Results and Conclusions: The results show that speed cameras have significantly reduced the number of road accidents near the camera sites. However, the effects vary across different time periods. The safety effects of speed cameras experienced a sharp decrease during the medium periods after an initial period of highly reduced accidents (medium 1: −53.1%, medium 2: −40.7%) and recovered slightly during the late period. In addition, to evaluate the criteria for selecting camera sites in the UK, we further investigated whether speed cameras at high risk sites have better safety performance. The results show that while safety effects at high risk camera sites also decreased during the medium periods, the reduction was smaller (medium 1: −20.8%, medium 2: −2.1%). Practical Applications: Appropriate road traffic regulations and management, as well as proper camera sites selection criterion, are important to maintain the effectiveness of speed cameras.     

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。     

DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL IN TAIWAN1

ABSTRACT: Ground water is a vital water resource in the Choushui River alluvial fan in Taiwan. A significantly increased demand for water, resulting from rapid economic development, has led to large scale ground water extraction. Overdraft of ground water has considerably lowered the ground water level, and caused seawater intrusion, land subsidence, and other environmental damage. Sound ground water management thus is essential. This study presents a decision support system (DSS) for managing ground water resources in the Choushui River alluvial fan. This DSS integrates geographic information, ground water simulation, and expert systems. The geographic information system effectively analyzes and displays the spatially varied data and interfaces with the ground water simulation system to compute the dynamic behavior of ground water flow and solute transport in the aquifer. Meanwhile, a ground water model, MODFLOW‐96, is used to determine the permissible yield in the Choushui River alluvial fan. Additionally, an expert system of DSS employs the determined aquifer permissible yield to assist local government agencies in issuing water rights permits and managing ground water resources in the Choushui River alluvial fan.     

Automated Classification of an Environmental Sensitivity Index

Environmental Sensitivity Indices (ESI) composed of many field-data are essential for monitoring and control systems. At the beginning of the last decade an ESI of the German Wadden Sea was developed for use by the relevant authorities. This ESI was derived by experts semi-manually analysing the extensive field data-set. An algorithm is presented here which emulates human expert-decisions on the classification of sensitivity classes. This will permit the necessary regular updates of ESI-determination when new field data become available using automated classifications procedures. After tuning the algorithm parameters it generates decisions identical to those of human experts in about 97% of all locations tested. In addition, the algorithm presented also enables erroneous or extremely seldom field data to be identified.     

Detecting Differences in Crown Transparency Assessments Between Countries using the Image Analysis System Croco

Estimates of crown transparency calculated using the semi-automatic image analysis system CROCO were compared withthe visual estimates of survey teams from 12 European countries.For each of five European species (Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.), Scotspine (Pinus sylvestris L.), beech (Fagus sylvatica L.), oak (Quercus robur L.)) 15 trees were assessed. In 64\% of the comparisons, CROCO estimates and the survey teams' scores differed significantly, while differences between countries were significant in 58 % of all comparisons. We calculated Spearman's rank correlation and the standard deviation of the differences between CROCO and each country and between pairs of countries. We then computed the medians for CROCO and each country. CROCO and only a few countries hadfor all species a higher median correlation and lower median standard deviation than the median for the comparison between countries. In addition no country had a consistently higher correlation or lower standard deviation than CROCO. We concludethat CROCO can provide more consistent and less variable estimates of crown transparency than visual assessments and that it can serve as a reference to detect differences in visualtransparency assessments between countries over time.