Integrating Paleobiology,Archeology, and History to Inform Biological Conservation

The search for novel approaches to establishing ecological baselines (reference conditions) is constrained by the fact that most ecological studies span the past few decades, at most, and investigate ecosystems that have been substantially altered by human activities for decades, centuries, or more. Paleobiology, archeology, and history provide historical ecological context for biological conservation, remediation, and restoration. We argue that linking historical ecology explicitly with conservation can help unify related disciplines of conservation paleobiology, conservation archeobiology, and environmental history. Differences in the spatial and temporal resolution and extent (scale) of prehistoric, historic, and modern ecological data remain obstacles to integrating historical ecology and conservation biology, but the prolonged temporal extents of historical ecological data can help establish more complete baselines for restoration, document a historical range of ecological variability, and assist in determining desired future conditions. We used the eastern oyster (Crassostrea virginica) fishery of the Chesapeake Bay (U.S.A.) to demonstrate the utility of historical ecological data for elucidating oyster conservation and the need for an approach to conservation that transcends disciplinary boundaries. Historical ecological studies from the Chesapeake have documented dramatic declines (as much as 99%) in oyster abundance since the early to mid‐1800s, changes in oyster size in response to different nutrient levels from the sixteenth to nineteenth centuries, and substantial reductions in oyster accretion rates (from 10 mm/year to effectively 0 mm/year) from the Late Holocene to modern times. Better integration of different historical ecological data sets and increased collaboration between paleobiologists, geologists, archeologists, environmental historians, and ecologists to create standardized research designs and methodologies will help unify prehistoric, historic, and modern time perspectives on biological conservation. Integración de Paleobiología, Arqueología e Historia para Informar a la Biología de la Conservación     

事故致因的突变模型

在众多论述伤亡事故致因的理论中，都没有解释为何系统元素的连续变化引起系统状态的突变（事故），以及人、物因素在这种突变过程中的作用。本文引入突变理论这一数学工具，指出系统内某些元素的连续变化导致系统状态的突然改变，较好地解决了这个问题，通过建立事故致因突变模型，提出了提高系统安全性的原则。     

SOME PROBLEMS IN STOCHASTIC HYDROLOGY1

In order to decrease the uncertainty that results in water resource planning and management studies due to the assumed recurrence of historical hydrological sequences, considerable study of stochastic processes in hydrology has taken place during the past 10 or 15 years. The general objective has been to develop a capability for generating a number of valid sequences, each of which could as resonably occur as could a recurrence of past events. A number of serious problems have been encountered, the consequence of which has been a serious lag in the application of stochastic processes to real planning and management problems. These problems include: a. an inability to generate droughts in some cases that are as extreme as have occurred historically, b. the generation of inconsistent values of stream flow at 2 locations on the same stream, c. the lack of mathematical techniques for the management of incomplete data sets, d. a great increase in the required computation for planning and management studies, and e. theoretical and computational difficulties in expanding the scope of stochastic hydrology from monthly quantities to short-period quantities. This paper discusses these problems and various approaches used in attempting their solution.     

活性污泥1#数学模型(ASM1)中的组分

活性污泥l#数学模型(AMl)常常用于预测污水处理厂中的生物过程。活性污泥数学模型组分的鉴定对活性污泥l#数学模型的应用具有重要的意义。本文描述了在活性污泥l#模型(ASMl)中污水组分的概念,以及组分鉴定的研究现状。     

OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.     

STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

基于随机模拟的地下水污染物最优水力截获量

水力截获技术是净化或抑制地下水污染最为广泛使用的一种方法，而该技术实施过程中，如何确定最优水力截获量是其需要重点解决的关键问题.本文针对传统确定性方法计算最优水力截获量不合理的问题，从水文地质参数的随机性出发，应用基于随机理论的蒙特卡罗方法，通过实例来研究渗透系数的空间变异性对地下水污染物水力截获系统的影响，并寻求估算最优水力截获量的新方法.通过研究表明：基于确定性方法计算出最优水力截获量为110m³/d时恰好能完全截获污染区的污染物；应用随机模拟研究含水层渗透系数的空间变异性对水力截获系统的影响，发现当以传统确定性方法所计算的最优水力截获量（110m³/d）抽水时，并不能总是完全截获地下水污染物，其面临的稳定平均风险率高达24%；充分考虑了含水层渗透系数空间变异的Monte Carlo方法较以往传统确定性方法更为可靠，为此本文提出利用随机方法从截获系统可接受风险角度确定最优截获量的新思路.     

地铁运营突发事件应急响应模式的马尔科夫链分析

为研究城市轨道交通网络化运营线路的风险传导规律和耦合关系,构建基于随机Petri网的同构马尔科夫链模型。通过模型分析突发事件应急响应模式中线路之间的相互影响,以及各线路启动突发事件应急响应模式对整个系统稳态的影响。结果表明,用该模型可从数学上研究城市轨道交通运营线路之间的传导规律和耦合关系,找出影响整个应急指挥系统效率的关键因素,最终提高地铁应对突发事件的能力。     

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.