混合菌对石油的降解

从含油污水中分离得到4株能高效降解石油的微生物菌株(X2、X3、X4、X5),经鉴定,4株菌分别属于黄单胞菌属(Xanthomonas sp.)、动胶菌属(Zoogloea sp.)、芽孢杆菌属(Bacillus sp.)和邻单胞菌属(Plesiomonas sp.).通过观察4株菌在原油培养基中的生长变化过程,确定了其中的优势菌;并对4株菌进行复配实验以确定各株菌混合后的石油降解效果;用正交实验法确定达到最佳石油降解效果各菌的投加量;通过对残油的Gc-MS测定分析,确定各菌在降解石油时所起的作用.结果表明,混合菌株中菌X4为优势菌,且有高的降解效果(达68,60％),其它3株降解率不高的菌混合投加也能达到较高的降解效果(达63.17％),菌X4是混合菌株维持高降解率的关键;达到最佳降解效果的各菌投加量分别为0.1％、0.1％、0.5％、2.0％;菌X2和菌X3降解C12-C16直链烃和少量支链烃,菌X4和菌X5对C12-C22直链烃有好的降解效果.图2表4参10     

Evaluating unintended consequences of intentional species introductions and eradications for improved conservation management

Increasingly intensive strategies to maintain biodiversity and ecosystem function are being deployed in response to global anthropogenic threats, including intentionally introducing and eradicating species via assisted migration, rewilding, biological control, invasive species eradications, and gene drives. These actions are highly contentious because of their potential for unintended consequences. We conducted a global literature review of these conservation actions to quantify how often unintended outcomes occur and to elucidate their underlying causes. To evaluate conservation outcomes, we developed a community assessment framework for systematically mapping the range of possible interaction types for 111 case studies. Applying this tool, we quantified the number of interaction types considered in each study and documented the nature and strength of intended and unintended outcomes. Intended outcomes were reported in 51% of cases, a combination of intended outcomes and unintended outcomes in 26%, and strictly unintended outcomes in 10%. Hence, unintended outcomes were reported in 36% of all cases evaluated. In evaluating overall conservations outcomes (weighing intended vs. unintended effects), some unintended effects were fairly innocuous relative to the conservation objective, whereas others resulted in serious unintended consequences in recipient communities. Studies that assessed a greater number of community interactions with the target species reported unintended outcomes more often, suggesting that unintended consequences may be underreported due to insufficient vetting. Most reported unintended outcomes arose from direct effects (68%) or simple density-mediated or indirect effects (25%) linked to the target species. Only a few documented cases arose from more complex interaction pathways (7%). Therefore, most unintended outcomes involved simple interactions that could be predicted and mitigated through more formal vetting. Our community assessment framework provides a tool for screening future conservation actions by mapping the recipient community interaction web to identify and mitigate unintended outcomes from intentional species introductions and eradications for conservation.     

双酚A对青岛大扁藻的干扰效应

为了探讨双酚A(bisphenol A,BPA)对海洋微藻的生态毒性效应,实验选择了以青岛大扁藻(Platymonas helgolanidica)作为受试物种,设置6个实验浓度(即0、2、4、6、8、10 mg·L-1)对微藻进行了96 h暴露处理,测定了不同浓度暴露下对青岛大扁藻的生长以及抗氧化系统酶活性等指标。研究结果表明,BPA对青岛大扁藻的96h-EC50为9.32 mg·L-1,属高毒类污染物。青岛大扁藻经过BPA暴露处理后,细胞密度下降,细胞色素含量降低,并且呈现明显的剂量-效应关系;细胞抗氧化系统中超氧化物歧化酶(SOD)、抗坏血酸过氧化物酶(APX)、单脱氢抗坏血酸还原酶(MDHAR)、脱氢抗坏血酸还原酶(DHAR)、谷胱甘肽还原酶(GR)活性均受到干扰。     

Impact of bias in predicted height on tree volume estimation: A case-study of intrinsic nonlinearity

Bias originating from intrinsic nonlinearity in nonlinear models is caused by excess curvature in the solution locus of parameter estimates derived from least squares procedures. Bias due to intrinsic nonlinearity varies according to sample size as well as model specification. This paper analyses consequences of fractionising data into smaller sub-samples. Based on measurements of stem diameter and total tree height from the first Danish national forest inventory, it is demonstrated how data splitting at random may cause the intrinsic nonlinear curvature to exceed the critical F-value. Application of a Taylor-series expansion shows that, for all practical purposes, the bias in predictions of individual tree volume (based on stem diameter and tree height) is negligible. To minimize residual variance, intrinsic curvature and, in turn, prediction bias, it is recommended that data be stratified according to site conditions, stand characteristics or other relevant criteria. Finally, the preferred model should exhibit close-to-linear behaviour.     

Temperature and Concentration Effects in Biomonitoring of Organic Air Pollutants

Up to now only very few studies in biomonitoring of organic air pollutants have been published taking into account the strong influence mean temperatures have on the accumulation process into plants during the course of the exposition. Temperature governed sorption as well as the plants vitality pose a major source of uncertainty making inter-study comparisons difficult. Different surface-to-volume ratios of plant foliage lead to strongly varying concentration effects in different plant species. Moreover a plants content of waxes and lipids must be considered in order to relate xenobiotic concentrations to the compounds being most efficient in the bioaccumulation process. Some of these factors are evaluated in regard to the use of plants as biomonitors for organic air pollutants. Another aim is to deduce the mean ambient gas phase concentrations from PAH concentrations determined in the biomonitor plants using vegetation-air partitioning coefficients which have been corrected for temperature dependent sorption as well as the plants lipid content. Restrictions of such approaches and methods of biomonitoring in general are discussed.     

大气中有机胺类物质反应机理和消除过程研究

综述大气中有机胺可能的来源、健康危害及其在大气中的均相和非均相化学转化机制,阐述有机胺的反应产物对二次有机气溶胶及其对大气气溶胶的物理和化学性质的改变,此类改变增强大气气溶胶间接气候效应(如成云结核能力等)。大气中的有机胺主要通过与大气氧化剂的反应和非均相反应过程的溶解或置换进入颗粒相,而后随着湿沉降(如云滴、雾滴、雨滴等)到达地面或海面。     

TiO2-Fe3+可见光催化H2O2降解阿特拉津的协同效应

以内分泌干扰物阿特拉津为模型污染物,研究了TiO2-Fe3+可见光催化H2O2降解阿特拉津的协同效应.结果表明,在H2O2存在条件下,金红石TiO2经可见光激发可持续稳定地产生.OH自由基,在Fe3+协同作用下,.OH自由基生成量急剧增加;TiO2能可见光催化H2O2降解阿特拉津,金红石TiO2显示出较锐钛矿TiO2及混晶TiO2(TiO2P25)更高的催化活性,反应60 min,阿特拉津的降解率可达40%;以Fe3+协同TiO2可见光催化H2O2降解阿特拉津时,反应效率显著加快,反应5 min即对阿特拉津的降解率达到100%,而金红石TiO2显示出更为明显的协同效应.     

基于生物导向的水生态健康监测及评估概述

环境监测是水生态健康监测与评估的重要环节,基于物理、化学监测的传统水质监测通常仅能提供独立的数据信息,不能全面、直观地反映水环境状况。基于生物等生命体导向的水生态监测通过生物对环境的响应,能够直接反应复杂水体状况,在水环境健康监测与评估中占据重要地位。基于病原微生物、指示生物介绍了生物监测中的常规生物指标,总结了包括藻类、无脊椎动物和鱼类在内的常见指示生物在不同类型污染水体中的环境指示作用。从生物毒性效应出发介绍了常用的毒性效应测试方法、分析了污染物在不同生物学水平的响应,从而指明生物毒性效应在水环境健康评估中的发展优势。再从生态完整性角度阐述了生态完整性评价的一般方法和新兴分子生物学技术在水生态健康评估中的应用。重点指出环境毒理学和分子生物学在水环境监测的优势,以期为更加科学精确地进行水生态健康监测预警提供支撑。     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.