特大火灾定量与定性风险管理技术应用探讨

定量化风险管理技术有其无可比拟的优势，但无法对风险因素中的人为因素进行管理。本文通过分析量化管理的缺陷和定性化管理的优势，提出应根据具体情况，采用定量化与定性化管理相结合的管理方式，并提出定性化管理的具体方法。     

提高洪水智能预报中洪峰预报精度方法的研究

针对防洪减灾的实际需要,对如何提高智能网络对洪峰的预报精度问题进行了深入系统的研究,提出了峰值放大修正系数和遗传算法优化网络初始权重相结合的改进算法,历史资料的检验结果表明了这些改进策略的有效性和可靠性.     

基于ANN的山东省可持续发展水平的区域差异

针对区域可持续发展系统的非线性,采用人工神经网络中较为先进的自组织特征映射网络构建模型.以山东省17个地市2001年的经济、人口、资源、环境、生活和科教状况作为带分样本,用自组织特征映射模型对山东省可持续发展区域差异进行了研究.研究结果表明,山东省可持续发展水平的区域差异可划分为4类,模拟结果比较理想.     

新疆中低产田发展人工草地的初步研究

从新疆天然草地的利用，农业面临的问题出发，说明在绿洲内发展人工草地的必要性。针对全疆中低产田特点，将其分成7种基本类型。按类型总结出相应适生的饲草种类。通过人工种植这些饲草，达到合理利用改良耕地的目的，进而带动整个农业产业结构的调整，建立起适宜新疆农业发展的草地农业模式。     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

湿地生态系统累积影响评价研究

定量分析湿地生态系统的累积环境影响,确定所要评价的功能,然后定量分析影响该功能的各种累积方式,将湿地生态系统的累积方式分为四种方式进行描述,对各种干扰活动的相互关系予以定性并进行量化,探讨湿地生态系统累积影响评价的步骤,有助于湿地生态系统CEA方法体系的建立与完善.     

土地利用变化对浙江生态系统服务价值的影响

生态系统服务功能价值理论可定量估算各类生态系统为人类提供服务的经济价值.土地是一切陆地生态系统的载体,在人类改造和利用自然的过程中不可避免地要影响各类生态系统的状况,进而影响到它们为人类提供的服务与功能.以浙江省1990年、1995年、1999年和2002年的土地利用类型数据为依据,结合浙江省的具体情况对生态价值计算方法进行修正,估算了该省生态服务价值的动态变化环境效益.结果表明,浙江省的生态服务价值经历了一个先缓慢上升后迅速下降的过程,其中水分调节和水分供应项变化的幅度大,而且不同土地类型发挥了不同的效应.     

开发区生态系统健康研究─以苏州高新区为例

采用生态系统健康理论分析开发区生态环境问题具有较强的理论意义和现实意义。着重构建了开发区生态系统健康评价的指标体系和模糊评价模型,提出评价标准。并对苏州高新区生态系统健康进行评价。进而指出制约因子并提出相应的诊断方案,为其优化生态系统结构和完善系统功能提供科学依据。     

Non-native Species <Emphasis Type="Italic">DO</Emphasis> Threaten the Natural Environment!

Sagoff [Journal of Agricultural and Environmental Ethics 18 (2005), 215–236] argues, against growing empirical evidence, that major environmental impacts of non-native species are unproven. However, many such impacts, including extinctions of both island and continental species, have both been demonstrated and judged by the public to be harmful. Although more public attention has been focused on non-native animals than non-native plants, the latter more often cause ecosystem-wide impacts. Increased regulation of introduction of non-native species is, therefore, warranted, and, contra Sagoff’s assertions, invasion biologists have recently developed methods that greatly aid prediction of which introduced species will harm the environment and thus enable more efficient regulation. The fact that introduced species may increase local biodiversity in certain instances has not been shown to result in desired changes in ecosystem function. In other locales, they decrease biodiversity, as they do globally.     

Impact of Human Activities on Carbon Dioxide (CO<Subscript>2</Subscript>) Emissions: A Statistical Analysis

Summary The balance of evidence suggests a perceptible human influence on global ecosystems. Human activities are affecting the global ecosystem, some directly and some indirectly. If researchers could clarify the extent to which specific human activities affect global ecosystems, they would be in a much better position to suggest strategies for mitigating against the worst disturbances. Sophisticated statistical analysis can help in interpreting the influence of specific human activities on global ecosystems more carefully. This study aims at identifying significant or influential human activities (i.e. factors) on CO₂ emissions using statistical analyses. The study was conducted for two cases: (i) developed countries and (ii) developing countries. In developed countries, this study identified three influential human activities for CO₂ emissions: (i) combustion of fossil fuels, (ii) population pressure on natural and terrestrial ecosystems, and (iii) land use change. In developing countries, the significant human activities causing an upsurge of CO₂ emissions are: (i) combustion of fossil fuels, (ii) terrestrial ecosystem strength and (iii) land use change. Among these factors, combustion of fossil fuels is the most influential human activity for CO₂ emissions both in developed and developing countries. Regression analysis based on the factor scores indicated that combustion of fossil fuels has significant positive influence on CO₂ emissions in both developed and developing countries. Terrestrial ecosystem strength has a significant negative influence on CO₂ emissions. Land use change and CO₂ emissions are positively related, although regression analysis showed that the influence of land use change on CO₂ emissions was still insignificant. It is anticipated, from the findings of this study, that CO₂ emissions can be reduced by reducing fossil-fuel consumption and switching to alternative energy sources, preserving exiting forests, planting trees on abandoned and degraded forest lands, or by planting trees by social/agroforestry on agricultural lands.