Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance

The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17–28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13–14% (0.04 ≤ P ≤ 0.06), and decreased human and deer by 6–7%. Negative misclassification into livestock was significant (0.04 ≤ P ≤ 0.06). Low antibiotic resistance showed the greatest effect in this category.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

5—(4—磺酸基苯偶氮)8—(2,4—二硝基苯氨基)喹啉测定食品中铜的研究应用

在弱碱性介质中 ,5— (4—磺酸基苯偶氮 ) 8— (2 ,4—二硝基苯氨基 )喹啉 (SPDNPAQ)与铜反应生成 2∶ 1紫红色络合物 ,体系 λmax=56 0 nm,ε=1.2 3× 10 5L· mol-1· cm-1。铜含量在 0～ 0 .4 mg/ L内符合比耳定律 ,方法用于一些生物样品和水样中铜的测定。     

地表水COD浓度灰色预测的GPPM（1）模型

根据地表水中ＣＯＤ浓度的时序数据,建立了ＧＰＰＭ（１）预测模型,结果表明ＧＰＰＭ（１）模型的预测精度优于常规灰色ＧＭ（１,１）模型,它为环境系统的拟合,预测和决策提供了新的方法途径。     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

The concentrations, distribution and sources of PAHs in agricultural soils and vegetables from Shunde, Guangdong, China

The concentrations, distribution and sources of 16 polycyclic aromatic hydrocarbons (PAHs) were determined in 30 agricultural soil and 16 vegetable samples collected from subtropical Shunde area, an important manufacturing center in China. The total PAHs ranged from 33.7 to 350 μg/kg in soils, and 82 to 1,258 μg/kg in vegetables. The most abundant individual PAHs are phenanthrene, fluoranthene, chrysene, pyrene and benzo(b)fluoranthene for soil samples, and anthracene, naphthalene, phenanthrene, pyrene and chrysene for vegetable samples. Average vegetable–soil ratios of total PAHs were 2.20 for leafy vegetables and 1.27 for fruity vegetables. Total PAHs in vegetable samples are not significantly correlated to those in corresponding soil samples. Principal component analyses were conducted to distinguish samples on basis of their distribution in each town, soil type and vegetable specie. Relatively abundant soil PAHs were found in town Jun’an, Beijiao, Chencun, Lecong and Ronggui, while abundant vegetable PAHs were observed in town Jun’an, Lecong, Xingtan, Daliang and Chenchun. The highest level of total PAHs were found in vegetable soil, followed by pond sediment and “stacked soil” on pond banks. The PAHs contents in leafy vegetables are higher than those in fruity vegetables. Some PAH compound ratios suggest the PAHs derived from incomplete combustion of petroleum, coal and refuse from power generation and ceramic manufacturing, and paint spraying on furniture, as well as sewage irrigation from textile industries. Soil PAHs contents have significant logarithmic correlation with total organic carbon, which demonstrates the importance of soil organic matter as sorbent to prevent losses of PAHs.     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

植物大气污染响应高光谱监测实例研究

选择某钢铁企业绿化树种桂花当年生叶片作为供试样本,测试叶片光谱反射率之后分别测试叶液pH值、叶片含硫量、叶绿素含量、叶片含水量,研究生长在S02 污染环境下桂花叶片光谱的变化以及相应的部分生理生化指标的变化.研究表明,污染较严重生产区采集的叶片光谱反射率和红边斜率均较生活区低.叶片含硫量随大气SO2 浓度的增减而相应地变化,叶片叶绿素含量、叶液pH值、叶片含水量的变化规律与叶片含硫量和大气SO2浓度的变化规律相反.     

北京市昌平区大气环境PM10中多环芳烃的含量及变化趋势

通过采集了2004～2006年北京市昌平区四个季节中大气PM10样品,采用超声抽提方法,使用GC/MS分析了该区PAHs含量和组成.结果显示,三年中四个季度的18种PAHs总量范围分别为21.64～656.39ng/m3、31.94～164.33ng/m3和7.294～209.3ng/m3,其中致癌性极强的苯并[a]芘含量范围为2.69～36.95 ng/m3、1.44～6.6ng/m3和0.256～8.625ng/m1,其变化趋势与PAHs总量有较好的相关性.PAHs的浓度是冬季＞秋季＞夏季＞春季,这与夏季时雨水冲刷和阳光照射强度大导致PAHs光解,冬季时燃煤排放大等影响因素有关.文章还使用多种方法判断昌平区大气PM10中的PAHs主要来源于燃煤和汽车尾气,其它污染源贡献较小.     

渭河干流(宝鸡段)表层沉积物Cu、Zn、Pb污染特征与评价

对渭河干流（宝鸡段）表层沉积物中重金属Cu、Zn、Pb含量进行了调查,用潜在生态危害系数法对其污染水平进行了评价,并与松花江（吉林市段）、淮河（江苏段）、长江（下游）、苏州河、珠江（广州段）5条河流表层沉积物中Cu、Zn、Pb的含量做了对比研究。结果表明,3种重金属元素平均含量均超出相应的土壤背景值,出现了一定程度上的富集;生态危害系数均〈40,属轻微生态危害。重金属含量水平在国内诸河中处于中间位置。