Monitoring toxics by group testing

Monitoring the environment for a large list of organic compounds present at low levels is costly. The primary purpose of such monitoring is to assure that hazardous levels of such compounds are not released into, or present in, the environment. Viewing this as a quality control problem, we suggest that samples from different sources can be composited using group testing procedures prior to analysis. Our purpose is to describe the basic concepts and suggest problems requiring study.     

Establishment of permit limits for mill effluent

Various governmental regulatory agencies are responsible for establishing regulations on the discharge of chlorinated organic compounds from pulp and paper mills. The procedures for setting permit limits are the basic topic of this article. Different methods of determining permit limits are set forth and discussed in a number of references, including documents of the Environmental Protection Agency. This paper discusses in detail the application of one particular methodology—the lognormal model approach. In this paper we utilize a real data set and include the necessary calculations required to set up permit limits. The basic tenets of the permit process are such that if limits are set too low, operators who are in full regulatory compliance will still be frequently cited, and if limits are set too high, operators who are not in compliance will seldom if ever be cited. Thus there is a great need for these effluent limits to be determined with great care, both to protect the environment receiving the wastewater and the industry producing the wastewater.     

Spatial and temporal variation of below-ground N transfer from a leguminous tree to an associated grass in an agroforestry system

Nitrogen (N) transfer from leguminous trees can be a major N source for the associated crop in low-input agroforestry systems. The aim of this study was to identify the main climatic and soil factors controlling N transfer from the leguminous tree Gliricidia sepium (Jacq.) Walp to the associated grass Dichanthium aristatum (Poir.) C.E. Hubb, in a 16-year-old tropical agroforestry system. Nitrogen transfer was estimated using the natural ¹⁵N abundance method. Before tree pruning, total N transfer represented 57% of the N uptake of the grass, including 31% coming from N₂ fixation. The spatial variation induced by the tree was well described by soil organic N content (ON). In this system, ON is an index of soil available N as well as of tree root density. Rainfall (R) and evapotranspiration (ETP) were the main climatic factors controlling N transfer. Multiple regression analysis indicated that R, ETP and ON explained 79% of the temporal and spatial variation of N transfer. Transferred N cannot be estimated after pruning because of the change in the isotopic signature of the soil N source. This was related to N release from root turnover. The results suggest that grass showed a preferential uptake of N coming from the tree, which could be due to a lower energy cost compared to obtaining absorbed N from the clayey soil used in this work.     

Melanin- and carotenoid-dependent signals of great tits (<Emphasis Type="Italic">Parus major</Emphasis>) relate differently to metal pollution

Due to their high phenotypic plasticity, the expression of secondary sexual characteristics is particularly sensitive to stress. Here, we investigated the expression of two conspicuous visual signals in great tits (Parus major) in a metal pollution gradient. In three study sites with marked differences in metal contamination (mainly lead, cadmium, copper and zinc), we compared melanin and carotenoid colouration of great tits. While carotenoid colouration (yellow breast) was negatively related to metal pollution, the size of a melanin trait (breast stripe) was larger in the most polluted sites. Environmental pollutants not only affect the expression of conspicuous signals but may even enhance, directly or indirectly, a signal of male quality such as breast stripe. Our results also support the multiple messages hypothesis predicting that different signals highlight different aspects of geno- and phenotypic condition of the bearer.     

九寨沟县地表水环境容量研究

水体中污染物的排放必须与水体的水环境容量相适应.在综合考虑城市经济发展与水资源利用状况前提下,首先,通过监测资料对九寨沟县辖区内主要污水受纳水体--白水江的地表水环境质量现状进行了评价,同时,结合对白水江流域污染源的现场调查,明确了河道水体的主要污染因子为CODCr和NH3-N,并预测了其在远、近规划期内的排放量;其次,在对河段进行功能分区基础上,采用一维稳态模型下的段首控制法计算了水环境容量.结果表明,2005年白水江CODCr与NH3-N的理论水环境容量分别为39.44 T/d和2.32 T/d,2005年其实际水环境容量分别为26.42 T/d和1.55 T/d.白水江水环境容量在近、远期内均能满足城市发展要求,但鉴于九寨沟县的旅游定位功能,应采取更为严格的控制标准;最后,结合九寨沟城镇生活污染源、农村面源与工业污染源的相应特点,提出了全面提升九寨沟县水环境质量的规划方案,为白水江实施污染总量控制与水环境管理提供了科学依据.     

油气田绿色矿山建设管理要求与实践

针对目前国家对绿色矿山建设的要求和环境保护面临的新形势,结合国内油气勘探与生产业务绿色发展的相关要求,阐述了油气田绿色矿山建设的发展历程、重点内容、建设标准;总结了绿色矿山建设形成的具体成果和经验,这些经验主要包括注重依法合规、提升绿色理念、科技创新、责任落实、多部门协作等,为下一步建设指导方向,进而提升国内油气勘探与生产业务整体绿色发展水平。     

Instream and offstream environmental conditions and stream biotic integrity: Importance of scale and site similarities for learning and prediction

Two different methods to predict biotic integrity were tested and compared in the present paper. The first one tries to predict the fish indices of biotic integrity (IBI) at the state or regional scale based on the most similar observations to a specific target site of interest using the simple to implement k-nearest neighbors (or kNN) method. Two different distance functions were considered to find the k-nearest neighbors: the Euclidean and the Mahalanobis. The second method was applied on the same datasets and consisted of a step-wise multiple regression. The two modeling approaches yielded similar results but kNN proved to be more time-efficient and very fast computationally for the given dataset sizes, which allowed applying a leave-one-out cross validation.In an attempt to reveal the importance of scale in the prediction of IBI, regression models were constructed at the state (or regional) scale and at the more refined cluster of sampling sites scale. Clusters of sites were extracted using Kohonen's self-organizing maps (SOM) followed by k-means clustering of the SOM neurons. Cluster-level regression models, constructed after site patterning, performed better in IBI prediction than global regression models constructed without any previous site patterning. The importance of identifying groups of sites with similar environmental characteristics affecting the IBI was revealed. The combined use of site patterning and regression modeling for IBI prediction also helped identifying important variables acting at the local scale which remain latent at the global scale.     

A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia,China

Two models, artificial neural network (ANN) and multiple linear regression (MLR), were developed to estimate typical grassland aboveground dry biomass in Xilingol River Basin, Inner Mongolia, China. The normalized difference vegetation index (NDVI) and topographic variables (elevation, aspect, and slope) were combined with atmospherically corrected reflectance from the Landsat ETM+ reflective bands as the candidate input variables for building both models. Seven variables (NDVI, aspect, and bands 1, 3, 4, 5 and 7) were selected by the ANN model (implemented in Statistica 6.0 neural network module), while six (elevation, NDVI, and bands 1, 3, 5 and 7) were picked to fit the MLR function after a stepwise analysis was executed between the candidate input variables and the above ground dry biomass. Both models achieved reasonable results with RMSEs ranging from 39.88% to 50.08%. The ANN model provided a more accurate estimation (RMSE_r = 39.88% for the training set, and RMSE_r = 42.36% for the testing set) than MLR (RMSE_r = 49.51% for the training, and RMSE_r = 53.20% for the testing). The final above ground dry biomass maps of the research area were produced based on the ANN and MLR models, generating the estimated mean values of 121 and 147 g/m², respectively.     

Ethics and governance for internet-based conservation science research

Internet-based research is increasingly important for conservation science and has wide-ranging applications and contexts, including culturomics, illegal wildlife trade, and citizen science. However, online research methods pose a range of ethical and legal challenges. Online data may be protected by copyright, database rights, or contract law. Privacy rights may also restrict the use and access of data, as well as ethical requirements from institutions. Online data have real-world meaning, and the ethical treatment of individuals and communities must not be marginalized when conducting internet-based research. As ethics frameworks originally developed for biomedical applications are inadequate for these methods, we propose that research activities involving the analysis of preexisting online data be treated analogous to offline social science methods, in particular, nondeceptive covert observation. By treating internet users and their data with respect and due consideration, conservationists can uphold the public trust needed to effectively address real-world issues.