Bayesian entropy for spatial sampling design of environmental data

We develop a spatial statistical methodology to design national air pollution monitoring networks with good predictive capabilities while minimizing the cost of monitoring. The underlying complexity of atmospheric processes and the urgent need to give credible assessments of environmental risk create problems requiring new statistical methodologies to meet these challenges. In this work, we present a new method of ranking various subnetworks taking both the environmental cost and the statistical information into account. A Bayesian algorithm is introduced to obtain an optimal subnetwork using an entropy framework. The final network and accuracy of the spatial predictions is heavily dependent on the underlying model of spatial correlation. Usually the simplifying assumption of stationarity, in the sense that the spatial dependency structure does not change location, is made for spatial prediction. However, it is not uncommon to find spatial data that show strong signs of nonstationary behavior. We build upon an existing approach that creates a nonstationary covariance by a mixture of a family of stationary processes, and we propose a Bayesian method of estimating the associated parameters using the technique of Reversible Jump Markov Chain Monte Carlo. We apply these methods for spatial prediction and network design to ambient ozone data from a monitoring network in the eastern US.     

论环境侵害中因果关系的判定

环境侵害是现代社会的新生问题,作为一种新型的侵害行为,它具有缓慢性、持续性,从而使因果关系判定发生困难。本文提出适用因果关系推定原则,并由加害人承担更多的举证责任来解决这一难题     

汶上县生态农业发展的制约因素及改善措施

通过对影响汶上县生态农业发展制约因素的分析,结合当地实际,从引导农民转变思想认识、发挥政策引导作用等方面入手,提出了汶上生态农业发展的改善措施、发展方向。     

Estimating the critical phosphorus loading of shallow lakes with the ecosystem model PCLake: Sensitivity, calibration and uncertainty

There is a vast body of knowledge that eutrophication of lakes may cause algal blooms. Among lakes, shallow lakes are peculiar systems in that they typically can be in one of two contrasting (equilibrium) states that are self-stabilizing: a ‘clear’ state with submerged macrophytes or a ‘turbid’ state dominated by phytoplankton. Eutrophication may cause a switch from the clear to the turbid state, if the P loading exceeds a critical value. The ecological processes governing this switch are covered by the ecosystem model PCLake, a dynamic model of nutrient cycling and the biota in shallow lakes. Here we present an extensive analysis of the model, using a three-step procedure. (1) A sensitivity analysis revealed the key parameters for the model output. (2) These parameters were calibrated on the combined data on total phosphorus, chlorophyll-a, macrophytes cover and Secchi depth in over 40 lakes. This was done by a Bayesian procedure, giving a weight to each parameter setting based on its likelihood. (3) These weights were used for an uncertainty analysis, applied to the switchpoints (critical phosphorus loading levels) calculated by the model. The model was most sensitive to changes in water depth, P and N loading, retention time and lake size as external input factors, and to zooplankton growth rate, settling rates and maximum growth rates of phytoplankton and macrophytes as process parameters. The results for the ‘best run’ showed an acceptable agreement between model and data and classified nearly all lakes to which the model was applied correctly as either ‘clear’ (macrophyte-dominated) or ‘turbid’ (phytoplankton-dominated). The critical loading levels for a standard lake showed about a factor two uncertainty due to the variation in the posterior parameter distribution. This study calculates in one coherent analysis uncertainties in critical phosphorus loading, a parameter that is of great importance to water quality managers.     

生态环境对我国居民幸福感的影响机制与实证研究

深入揭示生态环境与居民幸福感的内在关系对创造人民美好生活具有重要的理论与现实意义。本研究基于幸福感产生机制对生态环境影响居民幸福感的机制进行了深入的理论探讨,利用2013-2014年我国居民大样本调查数据,定量分析了水、大气,绿化三个关键生态环境要素对我国居民幸福感的影响。研究认为,生态环境对居民幸福感的影响受制于经济发展与居民收入水平及居民对环境价值的认知与重视程度;尽管研究期居民对生态环境质量满意度不高,但生态环境对我国居民幸福感的并没造成显著影响;比较而言,水环境对居民幸福感的影响小于空气环境,而空气环境的影响又小于绿化环境。为提升我国居民生态幸福感并激励居民亲环境行为,应通过科普教育切实提高居民对环境及其价值的认知度,努力营建人地和谐的文化氛围;应在普遍提高居民收入和物质生活水平的基础上,引导和促进居民向环境审美消费需求的升级;当前应重视生态补偿等经济手段的运用,通过影响居民经济利益激发居民环保行为;应优先解决居民直观感知明显且反映强烈的环境问题。     

基于贝叶斯网络的煤矿事故人因推理

煤矿事故的不可重现性决定了事故原因的调查具有很强的不确定性,如何通过事故发生后的相关信息提高事故深层次原因调查的准确性是非常重要的。将HFACS与贝叶斯网络相结合,以煤矿事故HFACS分析结果为样本,通过卡方检验和让步比分析建立人因的贝叶斯网络因果图,进一步利用最大似然估计算法确定了煤矿事故人因的贝叶斯网络参数。最后,以双柳煤业顶板事故的调查信息为证据推理导致煤矿事故发生的深层次原因,提高事故原因调查的准确性,从而验证模型的有效性。     

A guide to qualitative attribution methods for evaluation in conservation

Knowledge of what conservation interventions improve biodiversity outcomes, and in which circumstances, is imperative. Experimental and quasi-experimental methods are increasingly used to establish causal inference and build the evidence base on the effectiveness of interventions, but their ability to provide insight into how and under what conditions an intervention should be implemented to improve biodiversity outcomes faces limitations. A suite of attribution methods that leverage qualitative methods for causal inference is available but underutilized in conversation impact evaluation. This article provides a guide to 5 such qualitative attribution methods: contribution analysis, process tracing, realist evaluation, qualitative comparative analysis, and most significant change. It defines and introduces each method and then illustrates how they could be applied through a case study of community conservancies in Namibia. This guide provides examples of how qualitative attribution methods can advance knowledge of what works, in which contexts, and why in biodiversity conservation.     

超大城市昼夜交通事故严重程度致因对比分析——以深圳市为例

为研究夜间交通事故严重程度致因,基于深圳市3年3 244起交通事故数据,获取昼夜交通事故分布的时空特征;进一步选取交通事故集聚的南山区、福田区、罗湖区的1 798起交通事故,以交通事故严重程度为因变量,以事故原因、日期、事故形态等10个因素为候选自变量,构建广义有序Logit回归模型,对比分析昼夜不同严重程度交通事故的影响因素。结果表明:路口路段类型、疲劳驾驶、事故日期在夜间模型参数估计值分别为0.493,-0.363,-0.309,而在日间模型表现为不显著,道路路面材料在日间模型参数估计值为-0.232,而在夜间表现为不显著;事故原因、道路横断面渠化方式等因素在日间和夜间所引起交通事故的严重等级均存在较大差异。