Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models.The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is ‘poolable’.     

Using the maximum principle of impulse control for ecology-economical models

In this work we present mathematical models for population of single cohort and homogeneous animals. Investigating these mathematical models, we determine structure of optimal impulsive control which used maximum principle for optimal processes with impulse control.     

The role of size inequality in self-thinning: A pattern-oriented simulation model for arid savannas

The self-thinning line is a very robust pattern, which can be obtained in modeling studies by a variety of different mechanistic assumptions. Our opinion is that we can only advance in our understanding of mechanisms leading to the self-thinning relationship if we demand that the model also reproduces several other characteristic features (patterns) of the self-thinning process such as the degree of size inequality and the average size. We use a pattern-oriented modeling approach to develop a model of self-thinning under size inequality in overcrowded, even-aged stands, which reproduces these three patterns simultaneously. Our approach is to first develop an initial model based on our current ecological knowledge and then to refine the model by modifying the initial model to derive the model that reproduces all patterns of interest.The initial model is as simple as possible while avoiding incidental, ecologically unjustified, assumptions. It is a further development of zone of influence-simulation models: each plant is described by two circles, one describing a minimum-domain-area and one describing the zone of influence. In the initial model, mortality is “death-by-contact” of minimum-domain-areas and growth is a function of inter-tree competition, i.e. overlapping zones of influence. Model parameterization is based on field data on Acacia reficiens in southern Africa. Simulations follow patches of initially small trees through time for up to 1000 years with five parameters, three describing growth and two describing inter-tree competition. A sensitivity analysis shows that all parameters of the initial model contribute significantly to the number and size of plants through time. The two competition parameters, which describe competitive asymmetry and the size of the zone of influence relative to canopy size, are both important for generating size inequality. Thus, both competitive asymmetry and spatial pattern contribute to size inequality, and their relative importance may vary greatly.The sensitivity analysis suggests that all processes included in the initial model are essential to the evolution of size inequality. However, size inequality under the initial model is below field values, meaning that additional, as yet unconsidered processes, contribute to size inequality. Our best-fit model additionally contains details on growth stochasticity.This study establishes the often-proposed direct link between mortality driven by local competition and self-thinning and highlights the importance of stochasticity in ecological processes.     

甘肃省迭部县居民森林生态环境支付意愿影响因素分析

公众的生态环境认知水平及支付意愿对森林生态环境保护具有重要的影响和作用.根据甘肃省迭部县居民的291份有效调查问卷,采用描述性统计方法和结构方程模型对森林生态环境支付意愿的影响因素进行了分析.结果表明:①居民对生态环境服务价值的认知、对生态环境补偿的认知、对生态环境保护的预期收益、居民个人资金技术因素、外部环境因素与居民森林生态环境支付意愿之间存在正相关关系,且影响显著,其中影响程度最大的是外部环境因素,标准相关系数为0.830,解释效果良好,影响程度最小的是资金技术因素,相关系数仅为0.283.②多群组结构方程模型研究结果显示,男性居民的森林生态环境支付意愿主要受对森林生态环境认知程度的影响,女性更容易受外部环境因素的影响.不同年龄段的居民在森林生态环境服务价值认知、资金技术因素和外部环境因素方面存在差异性.不同教育程度居民之间的差异主要体现在对森林生态环境服务价值的认知和对森林生态环境补偿的认知上.③性别、年龄、教育程度等因素对生态环境服务价值认知、预期收益等有显著影响,且不同因素的影响程度存在差异.研究显示,对森林生态环境支付意愿影响因素分析反映了环境支付意愿的普适性问题,研究结果可为生态资源和环境管理等提供参考.      

The Impact of Perceptual and Situational Factors on Environmental Communication: A Study of Citizen Engagement in China

This study applied a situational approach to understanding an environmental problem: PM2.5 (its resulted haze and smog air pollution) in China. Based on a national sample of 374 citizens living in China, it tested a situational model of problem solving and extended it by adding citizens’ environmental engagement behaviour as an immediate consequence of their communicative action. Results of a structural equation modelling analysis supported all the causal links in the conceptual model. Moreover, communicative action significantly mediated the relationship between referent criterion and environmental engagement. Problem recognition, constraint recognition, and involvement recognition did not influence environmental engagement directly, but exerted their significant indirect impact via two key mediators in the model: situational motivation in problem solving and communicative action in problem solving. Theoretical and practical implications of the present study were discussed.     

Characterizing Interpersonal Influence for Grassland Conservation Behaviours in a Unique Population

Interpersonal communication can influence the decisions people make about engaging in conservation behaviours. In-depth interviews with Tibetan pastoralists serve as the basis for examining interpersonal communication patterns and sources of interpersonal influence about grassland conservation behaviours. Herding and family groups are key collectives; salient sources of information vary across types of information. Salient individuals are those with credibility and means control: community leaders, elders, veterinarians, and government officials. Explicit information about conservation comes from religious leaders. The findings have significant implications for understanding the function and nature of interpersonal influence in unique population groups regarding conservation actions.     

基于贝叶斯网络的高速动车组运营故障分析

为研究影响高速动车组正常运行的各故障因素间的因果关系,分析其耦合强度,将故障因素分为人、机、环3类,从系统角度又将机器因素分为5个子系统。人、机、环3类共识别27个故障因素;使用K2算法生成贝叶斯网络结构,引入扩展因果效应算法确定节点优先次序作为K2算法的先验知识,采用EM算法学习贝叶斯网络参数,构建基于贝叶斯网络的高速动车组运营故障分析模型;以209个CRH详细故障报告为例,对故障因素的故障发生概率进行排序并分析因素间的影响强度和灵敏度。结果表明:牵引供电系统故障发生概率较高;车门系统故障、牵引变流器故障易由内部零件故障引起,外界异物击打对受电弓影响较大;人、环因素更易引起多故障耦合;环境因素对牵引供电系统表现出较高的灵敏度。贝叶斯网络在分析高速动车组运营系统故障问题上具有可行性,分析结果有助于提升运营单位的管控能力。     

基于RPN-BN的平台-隔水管系统遇内波风险分析

为保障内孤立波作用下的深水半潜式钻井平台-隔水管系统的安全,同时解决海洋平台系统设备失效数据的缺失问题,提出1种风险优先系数（RPN）与贝叶斯（BN）结合的定量风险分析方法。首先,基于故障树和安全屏障方法,建立平台-隔水管系统Bow tie模型和贝叶斯风险演化模型;其次,根据贝叶斯推断和风险优先系数中的事故发生频度估计,得到平台-隔水管系统失效事故的发生概率;最后,通过贝叶斯网络的逆向推理能力辨识内孤立波作用下引起平台-隔水管系统失效的主要风险节点,实现对平台-隔水管系统失效事故的定量风险分析。结果表明:RPN-BN法可应用于平台-隔水管系统遇内波的定量风险分析;加强对平台漂移量的控制,提高动力定位系统控制设备的可靠性可有效抵御内波对系统造成的影响。     

异常环流背景下贺兰山地形对8.21特大致洪暴雨的影响分析

利用常规气象观测资料、NCEP再分析资料对2016年8月21日傍晚到夜间贺兰山沿山特大致洪极值暴雨展开研究,分析了异常大气环流形势及其影响,并利用天气研究和预报模式WRF(Weather Research and Forecasting model)进行数值模拟和地形敏感性试验,研究了贺兰山地形对暴雨过程的影响。结果表明:超强厄尔尼诺结束后的盛夏,大气环流形势发展异常,8月南亚高压和副热带高压异常偏强,西北地区东部处于高温、高湿、高能控制,副高的快速进退和冷平流的入侵,触发暖湿不稳定能量强烈聚集与快速释放,导致特大暴雨的爆发。其发生在200hPa高空急流分流区即强辐散区、中空西南气流的高温高湿区、低空偏南急流轴左侧流场最大弯曲处的强暖平流区、850hPa偏东大风速轴南侧的风速辐合区,天气尺度强迫作用相对较弱的环境中,500hPa短波槽与700hPa、850hPa低涡切变线和偏南偏东急流以及地面气旋式切变辐合线共同作用是其发生的主要影响系统。贺兰山地形对特大暴雨的发生有明显的增幅效应,主要是贺兰山地形阻挡与强迫抬升作用,促使低涡切变强烈发展从而影响了降水范围、强降水落区及其中心位置等。     

Prevalence of alcohol impairment and odds of a driver injury or fatality in on-road farm equipment crashes

Objective: The objective of this article was to estimate the prevalence of alcohol impairment in crashes involving farm equipment on public roadways and the effect of alcohol impairment on the odds of crash injury or fatality.

Methods: On-road farm equipment crashes were collected from 4 Great Plains state departments of transportation during 2005–2010. Alcohol impairment was defined as an involved driver having blood alcohol content of ≥0.08 g/100 ml or a finding of alcohol impairment as a driver contributing circumstance recorded on the police crash report. Injury or fatality was categorized as (a) no injury (no and possible injury combined), (b) injury (nonincapacitating or incapacitating injury), and (c) fatality. Hierarchical multivariable logistic regression modeling, clustered on crash, was used to estimate the odds of an injury/fatality in crashes involving an alcohol-impaired driver.

Results: During the 5 years under study, 3.1% (61 of 1971) of on-road farm equipment crashes involved an alcohol-impaired driver. One in 20 (5.6%) injury crashes and 1 in 6 (17.8%) fatality crashes involved an alcohol-impaired driver. The non-farm equipment driver was significantly more likely to be alcohol impaired than the farm equipment driver (2.4% versus 1.1% respectively, P = .0012). After controlling for covariates, crashes involving an alcohol-impaired driver had 4.10 (95% confidence interval [CI], 2.30–7.28) times the odds of an injury or fatality. In addition, the non-farm vehicle driver was at 2.28 (95% CI, 1.92–2.71) times higher odds of an injury or fatality than the farm vehicle driver. No differences in rurality of the crash site were found in the multivariable model.

Conclusion: On-road farm equipment crashes involving alcohol result in greater odds of an injury or fatality. The risk of injury or fatality is higher among the non-farm equipment vehicle drivers who are also more likely to be alcohol impaired. Further studies are needed to measure the impact of alcohol impairment in on-road farm equipment crashes.