Threats to Avifauna on Oceanic Islands

Abstract:  Results of the study by Blackburn et al. (2004 a ) of avifauna on oceanic islands suggest that distance from the mainland and time since European colonization have major influences on species extinctions and that island area is a significant but secondary contributing factor. After augmenting the data of the study on geographical properties for some of the islands they examined, we used a causal analysis approach with structural equation modeling to reexamine their conclusions. In our model geographical properties of islands, such as island area and isolation, were considered constraints on biological factors, such as the number of introduced mammalian predators and existing number of avifauna, that can directly or indirectly influence extinction. Of the variables we tested, island area had the greatest total influence on the threat of extinction due to its direct and indirect effects on the size of island avifauna. Larger islands had both a greater number of threatened bird species and more avifauna, increasing the number of species that could become threatened with extinction. Island isolation also had a significant, positive, and direct effect on threats to island avifauna because islands farther from the mainland had fewer current extant avifauna. Time since European colonization had a significant negative, but relatively weaker, influence on threats compared with the traditional biogeographic factors of island area and distance to the mainland. We also tested the hypothesis that the amount of threat is proportionally lower on islands that have had more extinctions (i.e., there is a "filter effect"). Because the proportion of bird extinctions potentially explained only 2.3% of the variation in the proportion of threatened species on islands, our results did not support this hypothesis. Causal modeling provided a powerful tool for examining threat of extinction patterns of known and hypothesized pathways of influence.     

A Bayesian hierarchical framework for calibrating aquatic biogeochemical models

Model practitioners increasingly place emphasis on rigorous quantitative error analysis in aquatic biogeochemical models and the existing initiatives range from the development of alternative metrics for goodness of fit, to data assimilation into operational models, to parameter estimation techniques. However, the treatment of error in many of these efforts is arguably selective and/or ad hoc. A Bayesian hierarchical framework enables the development of robust probabilistic analysis of error and uncertainty in model predictions by explicitly accommodating measurement error, parameter uncertainty, and model structure imperfection. This paper presents a Bayesian hierarchical formulation for simultaneously calibrating aquatic biogeochemical models at multiple systems (or sites of the same system) with differences in their trophic conditions, prior precisions of model parameters, available information, measurement error or inter-annual variability. Our statistical formulation also explicitly considers the uncertainty in model inputs (model parameters, initial conditions), the analytical/sampling error associated with the field data, and the discrepancy between model structure and the natural system dynamics (e.g., missing key ecological processes, erroneous formulations, misspecified forcing functions). The comparison between observations and posterior predictive monthly distributions indicates that the plankton models calibrated under the Bayesian hierarchical scheme provided accurate system representations for all the scenarios examined. Our results also suggest that the Bayesian hierarchical approach allows overcoming problems of insufficient local data by “borrowing strength” from well-studied sites and this feature will be highly relevant to conservation practices of regions with a high number of freshwater resources for which complete data could never be practically collected. Finally, we discuss the prospect of extending this framework to spatially explicit biogeochemical models (e.g., more effectively connect inshore with offshore areas) along with the benefits for environmental management, such as the optimization of the sampling design of monitoring programs and the alignment with the policy practice of adaptive management.     

外源硅对土壤镉吸附特性的影响

通过吸附等温试验,研究了不同加入量的硅对两种水田土壤吸附镉特性的影响。实验中调节介质的pH值至中性,从而消除了因硅酸盐的加入对土壤pH产生的影响。结果表明:在硅的加入量相同时,pH值较低的土壤对镉的吸附量要低于pH值较高的土壤;镉的加入质量浓度为0～50mg·L-1时,应用Freundlich方程拟合土壤对镉的吸附等温线效果最好;外源硅的加入量在0～120mg·L-1范围内时,随硅的加入量的增加土壤对镉的吸附量会有不同程度的降低。由此推断,对于以往研究发现的外源硅能够降低土壤镉的有效性、缓解植物的镉毒害作用,并非是促进了土壤对镉的吸附,而是可能存在着其他机制,这有待于进一步研究。     

Numerical integration of chemical ODE problems arising in air pollution models

The numerical treatment of a regional air pollution model (such models are, as a rule, described mathematically by systems of partial differential equations) leads to the solution of very large computational problems. The chemical submodel of an air pollution model is normally the most timeconsuming part of the computational work. The application of appropriate discretization and splitting procedures reduces the chemical submodel to a large number of relatively small ODE systems (one such system per gridpoint). In the process of searching for efficient numerical algorithms for the chemical submodels one can carry out experiments by using only one such ODE system in order to facilitate the work. This approach has been used in connection with a particular chemical scheme, the condensed CBM IV scheme, which is used in several large air pollution models. Six integration algorithms have been tested on a set of typical scenarios (consisting of different starting concentrations and/or of different values of the emissions). The advantages and the disadvantages of the algorithms tested are discussed. The final decision about the most efficient algorithm, among the algorithms tested, should be made after a second series of experiments. The coupling of the chemical process with the transport of air pollution (on, at least, a twodimensional domain) together with the application of highspeed computers has to be studied in the second series of experiments, which will be performed in a subsequent paper.     

重庆大气污染与儿童肺功能横截面研究

1995年 ,在重庆市城区及远郊区进行了儿童家庭问卷调查、气溶胶 (PM1 0 、PM2 .5 )及 SO2 的测试 ,并在两个点 (城区华新小学 ,远郊北碚红岩小学 )进行二次儿童肺功能的测定。通过城区和郊区 3 53 6例 (其中男性 1 74 4例 ,女性 1 792例 )儿童肺功能数据的比较 ,说明重庆大气污染 ,特别是气溶胶的污染已影响到儿童肺功能。与美国比较 ,重庆儿童较美国的儿童肺功能 (FVC,FEV1 )要低 9%～ 1 4 %。同时得到青春前期 (7～ 1 4岁 )儿童肺功能 (FVC,FEV1 )的参考值的计算公式     

Evaluating response surface designs for uncertainty analysis and prescriptive applications of a large-scale water quality model

Environmental models are often too large and cumbersome for effective use in regulatory decision making or in the characterization of uncertainty. This paper describes and compares four response surfaces that could complement a large-scale water quality model, the U.S. National Water Pollution Control Assessment Model (NWPCAM), in simulation and regulatory decision support applications. Results show that a physically based reduced-form model that exploits the mathematical structure of the underlying water quality model is a better predictor of policy-relevant outputs than the polynomial expansions that are frequently used in response surface studies.     

Mathematical Modeling of Leachates from Ash Ponds of Thermal Power Plants

The present study describes the development of empirical models for the prediction of various trace metals i.e., Mn, Cu, Fe, Zn and Pb found in the leachates generated from the ash ponds of various thermal power plants. The dispersion phenomenon of these trace metals followed first order reaction rate kinetics. The empirical models for individual trace metals derived from the lab scale models data correlate well with the real field data with regression coefficients varying from 0.93 to 0.98. The predicted concentrations of the trace metals varied within ±3% of the observed values in the leachates generated from the ash ponds of four thermal power plants with standard deviation varying from 0.001 to 0.032. The empirical models derived from the study can be applied for prediction of trace metals in leachates generated from similar thermal power plants.     

工业废水BOD5与CODCr相关关系以及BOD5测定的简化法

通过研究BOD5与CODCr的相关性,用线性函数BOD5=a+bCODCr的形式进行一元回归,间接求出BOD5或指导BOD5的测定,验证BOD5结果的准确性以及通过对稀释法公式的推导得出简化法的公式,并与稀释法进行比较,结果表明,简化后的方法与稀释法无显著差异,精密度、准确度较好。     

水上事故溢油运动轨迹与环境归宿预测模型的研究进展

以事故溢油在水面上的运动轨迹和环境归宿为研究对象,重点对溢油水下分散过程、岸边黏附及受水流冲刷下油膜质量衰减过程、水体悬浮物对石油黏附/吸附量的预测模型研究成果,以及目前日益受到关注的河流溢油模型的研究进展进行归纳总结。对比分析了不同预测模型结构功能差异和适用性问题,为不同环境条件下溢油事故的后预警、后预测提供模型选择依据和技术支持。最后就溢油模型尚存的一些问题及未来发展的方向进行了探讨。     

青草沙输水隧道安全施工通风模型及湍流流动特性研究

随着我国隧道总里程的迅速增加,隧道施工的通风问题日益突出。文中将着重分析上海市青草沙水源地原水工程7200m过江隧道施工的通风问题,即从流体力学的三维不可压缩雷诺时均Navier-stokes方程出发,基于RNGk-ε湍流模型及近壁区两层壁面模型,采用有限体积方法和SIMPLE算法,对隧道内湍流流动进行数值模拟。数值分析有害气体的分布情况,讨论正常施工、发生事故时不同通风量条件下,隧道盾构掘进工作面附近流场、温度及有害气体浓度的变化规律。得出：对于隧道施工中有害气体的连续泄漏事故,随着通风风量的增加,有害气体的浓度逐渐降低。对于有害气体瞬时泄漏的事故,当盾构机架通风管的通风量约为380.00m3/min,放置于机架中部附近的排风管压力为200Pa时,隧道施工的通风效果最佳。本文涉及的通风方式和有关的研究结果为保证隧道施工的安全性提供理论依据。