Efficient search procedures for extreme pollutant values

Extreme pollutant values are of great interest in water quality monitoring because of their frequent toxicological significance. The principal barrier to the detection of these values, however, is the cost of extensive and comprehensive monitoring. This paper demonstrates an efficient method to determine the maximum sample measurement from a finite set of sequential samples without explicitly testing them all. It is assumed that the process of sample measurement is distinct from collection and has higher costs. It is further assumed that the measurements have high positive autocorrelation.A methodology is presented based on a common industrial testing procedure referred to as composite sampling—the physical pooling or compositing of a set of sequential samples before measurement. A method known as primary first order compositing (PFOC) was found to be superior to the traditional technique of random sampling, particularly if small composite sizes are utilized.The authors are, respectively, operations research analyst, Vancouver, B. C.; Associate Professor and Chairman, Policy Analysis Division, Faculty of Commerce and Business Administration, University of British Columbia; and Associate Professor, Management Science Division, Faculty of Commerce, U.B.C.     

Estimating means and variances: The comparative efficiency of composite and grab samples

This paper compares the efficiencies of two sampling techniques for estimating a population mean and variance. One procedure, called grab sampling, consists of collecting and analyzing one sample per period. The second procedure, called composite sampling, collectsn samples per period which are then pooled and analyzed as a single sample. We review the well known fact that composite sampling provides a superior estimate of the mean. However, it is somewhat surprising that composite sampling does not always generate a more efficient estimate of the variance. For populations with platykurtic distributions, grab sampling gives a more efficient estimate of the variance, whereas composite sampling is better for leptokurtic distributions. These conditions on kurtosis can be related to peakedness and skewness. For example, a necessary condition for composite sampling to provide a more efficient estimate of the variance is that the population density function evaluated at the mean (i.e.f()) be greater than . If , then a grab sample is more efficient. In spite of this result, however, composite sampling does provide a smaller estimate of standard error than does grab sampling in the context of estimating population means.     

用BaCl2滴定法快速测定硫酸盐的研究

用铬酸钡光度法、EDTA滴定法、间接原予吸收法、离子色谱法等方法测定SO4^2-检测上限都很低（12—200mg／L），且只适用于清洁水，若水样混浊则会引起较大的误差。有的地下水，SO4^2-浓度高迭44000mg／L，用BaCl2滴定法测定SO4^2-：测试水样，以溴酚蓝做酸碱指示剂，加1：50盐酸，调为pH=3．5，加入30ml异丙醇，以钍试荆做终点指示荆，滴加0．01mol／L BaCl2，砖红色为终点，根据BaCl2用量计算SO4^2-浓度。本方法快捷、准确、测定范围大，上限可迭2000mg／L，克服了光度法测定浑浊水样引起误差大的缺点。     

用BaCl2滴定法快速测定硫酸盐的研究

用铬酸钡光度法、EDTA滴定法、间接原子吸收法、离子色谱法等方法测定SO42-检测上限都很低(12-200mg/L),且只适用于清洁水,若水样混浊则全引起较大的误差.有的地下水,SO42-浓度高达44000mg/L,用BaCl2滴定法测定SO42-:测试水样,以溴酚蓝做酸碱指示剂,加1∶50盐酸,调为pH=3.5,加入30ml异丙醇,以钍试剂做终点指示剂,滴加0.01mol/L BaCl2,砖红色为终点,根据BaCl2用量计算SO42-浓度.本方法快捷、准确、测定范围大,上限可达2000mg/L,克服了光度法测定浑浊水样引起误差大的缺点.     

Implications of Land Use Changes on Carbon Dynamics and Sequestration—Evaluation from Forestry Datasets, India

Forests and soils are a major sink of carbon, and land use changes can affect the magnitude of above ground and below ground carbon stores and the net flux of carbon between the land and the atmosphere. Studies on methods for examining the future consequences of changes in patterns of land use change and carbon flux gains importance, as they provide different options for CO₂ mitigation strategies. In this study, a simulation approach combining Markov chain processes and carbon pools for forests and soils has been implemented to study the carbon flows over a period of time. Markov chains have been computed by converting the land use change and forestry data of India from 1997 to 1999 into a matrix of conditional probabilities reflecting the changes from one class at time t to another class time t+1. Results from Markov modeling suggested Indian forests as a potential sink for 0.94 Gt carbon, with an increase in dense forest area of about 75.93 Mha and decrease of about 3.4 Mha and 5.0 Mha in open and scrub forests, if similar land use changes that occurred during 1997–1999 would continue. The limiting probabilities suggested 34.27 percent as dense forest, 6.90 as open forest, 0.4 percent mangrove forest, 0.1 percent scrub and 58 percent as non-forest area. Although Indian forests are found to be a potential carbon sink, analysis of results from transition probabilities for different years till 2050 suggests that, the forests will continue to be a source of about 20.59 MtC to the atmosphere. The implications of these results in the context of increasing anthropogenic pressure on open and scrub forests and their contribution to carbon source from land use change and forestry sector are discussed. Some of the mitigation aspects to reduce greenhouse gas emissions from land use change and forestry sector in India are also reviewed in the study.     

Trait‐based prediction of extinction risk of small‐bodied freshwater fishes

Small body size is generally correlated with r‐selected life‐history traits, including early maturation, short‐generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small‐bodied freshwater fishes from 4 temperate river basins: Murray‐Darling, Australia; Danube, Europe; Mississippi‐Missouri, North America; and the Rio Grande, North America. Twenty‐three ecological and life‐history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed‐effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size—among small‐bodied species—was the most influential trait correlated with threatened species listings. The k‐folds cross‐validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small‐bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11,000 unclassified freshwater fishes, especially those under threat from proposed dam construction in the world's most biodiverse river basins.     

Monitoring Environmental Impact in the Upper Sonoran Lifestyle: A New Tool for Rapid Ecological Assessment

Characterized by expensive housing, high socioeconomic status, and topographic relief, Upper Sonoran Lifestyle communities are found primarily along the Wildland-Urban Interface (WUI) in the Phoenix, Arizona metro area. Communities like these sprawl into the wildlands in the United States Southwest, creating a distinct urban fringe. This article, through locational comparison, introduces and evaluates a new field assessment tool for monitoring anthropogenic impact on soil–vegetation interactions along the well-maintained multi-use recreational trails in Upper Sonoran Lifestyle region. Comparing data from randomly selected transects along other multi-use trails with data from a control site revealed three key indicators of anthropogenic disturbances on soil–vegetation interactions: soil disturbance, vegetation disturbance, and vegetation density. Soil and vegetation disturbance displayed an average distance decay exponent factor of −0.60, while vegetation density displayed a reverse decay average of 0.60. Other important indicators of disturbance included vegetation type, biological soil crusts, and soil bulk density. The predictive ability of this new field tool enhances its applicability, offering a powerful rapid ecological assessment method for monitoring long-term anthropogenic impact in the Upper Sonoran Lifestyle, and other sprawling cities along the WUI.     

Coalition of injustice? Bodies,business, and the biosphere in struggles against unwanted land uses

Scholars of environmental injustice have pushed to see beyond the spatial distribution of environmental harms in studies of unwanted land uses. Building upon this work, this article examines how the complex geographies of environmental injustice play out in a coalition to prevent the construction of a coal-fired power plant in Surry County, Virginia. While spatially dispersed coalitions of negatively affected actors can strengthen efforts to prevent the construction of an unwanted land use, they can also perpetuate the environmental injustices surrounding it. To make this argument, particular attention is paid to the diverse reasons and ways differentially situated actors oppose an unwanted land use. It is demonstrated how the disparate concerns and differential tactics deployed by actors in coalitions against unwanted land uses are often embedded in and potentially contribute to longer histories of social injustice.