磺胺类化合物对大肠杆菌突变QSAR预测模型初探

抗生素被广泛应用于医疗、农业和畜牧业等领域,但是长期滥用会促进细菌的突变作用。本文以大肠杆菌(E.coli)为受试生物,测定了10种磺胺类抗生素(SAs)单一暴露时对E.coli的突变效应,采用物化参数Ebinding(抗生素与其靶蛋白的相互作用能力)与突变效应参数lgRC0-2(最高可观测突变促进效应浓度)或lgRCmax(突变促进率最大值对应的浓度),建立了突变效应的QSAR模型,并采用雷达图进行验证。结果表明,lgRC0-2与Ebinding模型和lgRCmax与Ebinding、DMG(偶极矩)模型的拟合系数R2分别是0.888、0.873,即lgRC0-2或lgRCmax与Ebinding相关性均较好,可能由于磺胺类化合物(SAs)会作用于叶酸合成通路,影响嘌呤、嘧啶碱基的合成,从而对E.coli的突变具有促进效应,且雷达图验证表明,上述2个模型均具有良好的内部预测能力。本研究有望为抗生素使用带来的生态风险评价以及药物设计提供相关指导。     

重庆市内环货车错时限行对空气质量的影响

在分析货车实施错时限行后内环车流量时段分布变化基础上,通过对PM_(2.5)、NO_2等指标的ADMS模型模拟和实际监测数据对比分析,探讨了内环货车错时限行对环境空气质量的影响。结果表明,货车错时限行后主城区环境空气中PM_(2.5)、NO_2小时平均质量浓度分别降低了9.4%和6.0%,峰值浓度明显降低,晚上出现峰值时间往后推移了2~3 h。经ADMS模型模拟计算,内环高峰时段机动车排放对主城区NO_2、PM、VOCs的浓度贡献分别降低了54.1%、56.3%、17.5%,CO浓度贡献不大。内环货车错时限行措施对重庆市主城区空气质量的改善有一定的积极作用。     

环境污染物计算毒理学分析及环境行为模拟研究进展

根据国内外研究报道,系统地总结了计算毒理学和化合物环境行为模拟在环境科学领域的研究进展,包括二者的概念、理论、研究方法以及在环境研究中的应用;分析了计算毒理学和化合物环境行为模拟在发展中所面临的挑战,并提出对策;展望了计算毒理学和化合物环境行为模拟在环境研究中的发展前景。     

A simple approach to modeling microbial biomass in the rhizosphere

Microorganisms make an important contribution to the degradation of contaminants in bioremediation as well as in phytoremediation. An accurate estimation of microbial concentrations in the soil would be valuable in predicting contaminant dissipation during various bioremediation processes. A simple modeling approach to quantify the microbial biomass in the rhizosphere was developed in this study. Experiments were conducted using field column lysimeters planted with Eastern gamagrass. The microbial biomass concentrations from the rhizosphere soil, bulk soil, and unplanted soil were monitored for six months using an incubation–fumigation method. The proposed model was applied to the field microbial biomass data and good correlation between simulated and experimental data was achieved. The results indicate that plants increase microbial concentrations in the soil by providing root exudates as growth substrates for microorganisms. Since plant roots are initially small and do not produce large quantities of exudates when first seeded, the addition of exogenous substrates may be needed to increase initial microbial concentrations at the start of phytoremediation projects.     

The control of emigration and its consequences for the survival of populations

Dispersal is the key process enhancing the long-term persistence of metapopulations in heterogeneous and dynamic landscapes. However, any individual emigrating from a occupied patch also increases the risk of local population extinction. The consequences of this increase for metapopulation persistence likely depend on the control of emigration. In this paper, we present results of individual-based simulations to compare the consequences of density-independent (DIE) and density-dependent (DDE) emigration on the extinction risk of local populations and a two-patch metapopulation. (1) For completely isolated patches extinction risk increases linearly with realised emigration rates in the DIE scenario. (2) For the DDE scenario extinction risk is nearly insensitive to emigration as longs as emigration probabilities remain below ≈0.2. Survival chances are up to half an order of magnitude larger than for populations with DIE. (3) For low dispersal mortality both modes of emigration increase survival of a metapopulation by ca. one order of magnitude. (4) For high dispersal mortality only DDE can improve the global survival chances of the metapopulation. (5) With DDE individuals are only removed from a population at high population density and the risk of extinction due to demographic stochasticity is thus much smaller compared to the DIE scenario.With density-dependent emigration prospects of metapopulations survival may thus be much higher compared to a system with density-independent emigration. Consequently, the knowledge about the factors driving emigration may significantly affect our conclusions concerning the conservation status of species.     

Dynamics of soil organic matter in primary and secondary forest succession on sandy soils in The Netherlands: An application of the ROMUL model

We applied the simulation model ROMUL of soil organic matter dynamics in order to analyse and predict forest soil organic matter (SOM) changes following stand growth and also to identify gaps of data and modelling problems. SOM build-up was analysed (a) from bare sand to forest soil during a primary succession in Scots pine forest and (b) on mature forest soil under Douglas fir plantations as an example of secondary succession in The Netherlands. As some of the experimental data were unreliable we compiled a set of various scenarios with different soil moisture regime, initial SOM pools and amount and quality of above and below ground litter input. This allowed us to find the scenarios that reflect the SOM dynamics more realistically. In the Scots pine forest, total litter input was estimated as 0.50 kg m⁻² year⁻¹. Two scenarios were defined for the test runs: (a) forest floor moisture regimes—‘dry, mesic and hydric’ and (b) augmenting a root litter pool with three ratios of needles and branches to roots: 1:1, 1:1.5 and 1:2.0. The scenario finally compiled had the following characteristics: (a) climate for dry site with summer drought and high winter moisture of forest floor; (b) a litter input of 0.25 kg m⁻² year⁻¹ above ground and 0.50 kg m⁻² year⁻¹ below ground; (c) a low nitrogen and ash content in all litter fall fractions. The test runs for the estimation of the initial SOM pools and the amount and proportion of above and below ground litter fall were also performed in the Douglas fir plantation. The inputs of above ground litter tested in various combinations were 0.30 and 0.60 kg m⁻² year⁻¹, and below ground litter 0.30, 0.60 and 0.90 kg m⁻² year⁻¹. The scenario that fitted the experimental data had an SOM pool of 20–25 kg m⁻², an aboveground litter input of 0.6 kg m⁻² year⁻¹and a below ground litter input of 0.9 kg m⁻² year⁻¹. The long-term simulation corresponded well with the observed patterns of soil organic matter accumulation associated with the forest soil development in primary and secondary succession. During primary succession in Scots pine forest on dry sand there is a consistent accumulation of a raw humus forest floor. The soil dynamics in the Douglas fir plantation also coincide with the observed patterns of SOM changes during the secondary succession, with SOM decreasing significantly under young forest, and SOM being restored in the older stands.     

Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risks

An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures.     

Evaluating the ability of habitat suitability models to predict species presences

Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presence-only evaluators to usual presence/absence measures.     

Parameterizing,evaluating and comparing metapopulation models with data from individual-based simulations

Due to the lack of sufficient data and appropriate ecological information parameterizing predictive population dynamical models usually is a difficult task. The approach proposed in this study is meant to overcome this problem by using detailed individual-based simulations to generate artificial data. With short-term data samples, the models to be investigated can be parameterized and their predictions be compared. The flexibility of individual-based simulations as experimental tools also facilitates the evaluation and comparison of different (aggregated) model types. The presented approach is a step towards unifying models of different complexity. As an example we applied it to two metapopulation models of insect species in a highly fragmented landscape: the well-known incidence function model with a patch-based representation of space and a grid-based analogue. The models are tested with respect to their data requirement and recommendations for a better data sampling are derived.     

三唑酮在油菜-土壤生态系统中的降解与建模

为评价三唑酮可湿性粉剂在土壤-油菜生态系统中使用后的残留行为和环境安全性,进行了2 a大田试验,并比较了指数模型、GM(1,1)灰色模型、阻滞动力学模型对三唑酮降解规律的描述。结果表明:3种模型的拟合结果均达到统计学意义上显著相关;对三唑酮在土壤和油菜中降解行为模拟结果最好的分别为GM(1,1)模型和阻滞动力学模型;三唑酮在土壤中2 a的半衰期分别为3.48和4.38 d,油菜植株中分别为1.98和3.78 d,其降解受温度影响较大。