Simulating correlated count data

In this study we compare two techniques for simulating count-valued random n-vectors Y with specified mean and correlation structure. The first technique is to use a lognormal-Poisson hierarchy (L-P method). A vector of correlated normals Z is generated and transformed to a vector of lognormals X. Then, Y is generated as conditionally independent Poissons with means X _i . The L-P method is simple, fast, and familiar to many researchers. However, the method requires each Y _i to be overdispersed (i.e., σ² > μ), and only low correlations are possible with this method when the variables have small means. We develop a second technique to generate the elements of Y as overlapping sums (OS) of independent X _j ’s (OS method). For example, suppose X, X ₁, and X ₂ are independent. If Y ₁ = X + X ₁ and Y ₂ = X + X ₂, then Y ₁ and Y ₂ are correlated because they share the common component X. A generalized version of the OS method for simulating n-vectors of two-parameter count-valued distributions is presented. The OS method is shown to address some of the shortcomings of the L-P method. In particular, underdispersed random variables can be simulated, and high correlations are feasible even when the means are small. However, negative correlations cannot be simulated with the OS method, and when n > 3, the OS method is more complicated to implement than the L-P method.     

Patch Size and Connectivity Thresholds for Butterfly Habitat Restoration

Abstract:  Recovery of endangered species in highly fragmented habitats often requires habitat restoration. Selection of restoration sites typically involves too many options and too much uncertainty to reach a decision based on existing reserve design methods. The Fender's blue butterfly (  Icaricia icarioides fenderi ) survives in small, isolated patches of remnant prairie in Oregon's Willamette Valley—a habitat for which <0.5% of the original remains. Recovery of this species will require considerable habitat restoration. We investigated the potential of biologically based rules of thumb and more complex models to serve as tools in making land acquisitions. Based on Fender's blue dispersal behavior and demography, we have estimated that restored patches should be <1 km from existing habitat and at least 2 ha. We compared these rules to the results of two modeling approaches: an incidence function model and a spatially explicit simulation of demography and dispersal behavior. Not surprisingly, the simple rules and complex models all conclude that large (>2 ha) connected (<1 km) patches have the highest restoration value. The dispersal model, however, suggests that small, connected patches have more restoration value than large, isolated patches, whereas the incidence function model suggests that size and connectivity are equally important. These differences stem from model assumptions. We used incidence functions to predict long-term, stochastic, steady-state conditions and dispersal simulations to predict short-term (25-year) colonization dynamics. To apply our results in the context of selecting restoration sites on the ground, we recommend selecting nearby sites when short-term colonization dynamics are expected to be an important aspect of a species' biology.     

新疆中部天山雪岭云杉种群动态初步研究

雪岭云杉PiceaschrenkianaFisch.etMey在中部天山林区内分布于海拔1500m～2700m之间,形成一个垂直分布带。作者采用样方法进行调查,沿海拔梯度每隔100m选取两块样地(20m×20m),在海拔1500～2700m的雪岭云杉林内共选样地26块来调查中部天山雪岭云杉种群的年龄结构、密度和生物量动态。在所选样地内,调查所有雪岭云杉树木(h≥2m)的胸径并按5cm分成不同的径级,每一径级至少选取两棵树,每棵树在不同方向上钻取两个树芯,建立年龄-胸径方程推算样地内所有雪岭云杉树(h≥2m)的年龄;调查样地内所有幼苗(h<50cm)和幼树(50cm≤h<200cm)的高度并根据主干上轮枝数查数一定数目幼苗幼树的年龄,建立年龄-高度方程并推算样地内所有幼苗幼树的年龄。研究结果表明中部天山雪岭云杉种群的胸径、年龄结构和种群密度都呈倒-J型分布,种群生物量呈钟型分布,存活曲线基本介于DeeveyⅡ和DeeveyⅢ型之间。以上研究结果表明中部天山的雪岭云杉种群处于不断更新和稳定发展的时期。     

北京大气CH4、CO2、TOC日变化规律及垂直分布的自动连续观测

提出了一种能自动连续监测CH4、CO2、TOC日变化及垂直分布的系统,利用该系统监测了2002年冬季CH4、CO2、TOC垂直分布的日变化的变化趋势.结果发现,距地面高度增加,受湍流扩散的影响,CH4、CO2、TOC浓度降低.冬季CH4浓度的日变化呈现明显的单峰周期变化,CO2日变化呈双峰形分布,TOC日变化没有明显的特征,其日变化受机动车尾气排放的影响很大.根据2002年冬季CO2浓度与2000年以前的对比结果发现,北京市冬季燃煤排放的污染物已处于一个相对稳定期,而随着北京市机动车保有量迅速增加,尾气排放成为影响某些大气微量气体日变化的主要因素.     

毛乌素沙地地下水浅埋区田间水分动态

毛乌素沙地种植区地下水埋深较浅,地下水与土壤水分之间联系紧密,为揭示春玉米生长过程中水分运移关键过程,本文基于原位监测,利用Hydrus-1D建立模型研究毛乌素沙地的田间水分动态。结果发现:在包气带中,40 cm深以上土层水分受根系吸水和气象条件影响变化剧烈,50 cm深以下土层水分变化受地下水影响显著;在玉米整个生长期内,蒸发量占蒸散量的比例为31%,地下水对玉米生长的水分贡献总量为220.09 mm,占玉米耗水总量的37.9%;为了减少深层入渗,实现节水灌溉,在当前地下水埋深条件下,可将每次的灌溉量减少为原水量的72%;地下水位的下降会减少玉米对地下水的利用,并增大灌溉需求量,模拟发现,当平均地下水埋深下降至147 cm深时,玉米生长将不再利用地下水。研究成果可为毛乌素沙地的农田水分利用及生态环境保护提供重要的理论依据和参考信息。     

基于SD的污水处理厂减排潜力与费用效益——以昆明市为例

针对当前城市污水处理厂进水浓度偏低,进而影响其污水处理潜力发挥和经济效益等问题,以昆明市为例,构建了基于系统动力学的城市排水系统模拟仿真模型.依据昆明市“十三五”规划目标,以2015年为基准年,设计4种减排情景,模拟预测了不同时期下不同情景的污水处理厂减排潜力及费用效益.结果表明：城市排水管网改造与强化管理对提高污水处理厂运行效率,充分挖掘其污水处理潜力至关重要,该情景近期与远期污水处理厂COD削减量较基准情景分别提高了314772,389126t;NH₃-N削减量较基准情景分别提高24223,27234t;费效比较基准情景分别降低0.2和0.17,污水处理潜力得到充分挖掘,经济效益明显改善.     

水环境承载力中长期预警研究-以昆明市为例

基于系统动力学动态模拟仿真方法,构建水环境承载力预警方法体系,并以昆明市为研究对象,对其水环境承载力超载状态进行预警.研究结果显示：在目前发展情景（BAU）下,2015~2025年10a间,昆明市水环境承载力超载状态综合指数从1.78逐渐增大到2.22,水环境超载状态不断恶化;昆明市系统耦合协调度一直处于0.5~0.8之间,且社会总功效大于水环境总功效,社会经济子系统与水环境子系统互相拮抗;警度自中警转为巨警,信号灯由橙灯转化为红灯,昆明市未来面临着严峻的水环境承载力超载问题.     

建筑废弃物资源化环境效益分析:以重庆为例

为了向政府提供可以提升建筑废弃物资源化环境效益的有利政策,以促进建筑废弃物资源化的可持续发展,本文从系统角度,应用系统动力学通过文献分析、实地调研、调查问卷等方法对建筑废弃物资源化的环境效益进行建模和模拟仿真.通过对环境效益模型进行情景分析,得出当非法排放单位罚款在50~60元/t,单位填埋收费取30元/t左右,建筑废弃物到资源化处置中心距离在15~25km左右,资源化的单位补贴额为25元/t左右时,可以使环境效益处于较优状态.同时政府应提高建筑废弃物相关法律的完善程度、培养相关人员的现场回收意识、促进相关科研研发,以期促进建筑废弃物资源化的环境效益.     

公众环境关注、环境规制与中国能源密集型产业动态

自十八大以来,公众环境治理与环境规制成为影响能源密集型产业动态的重要因素。基于2011—2016年百度指数数据与中国海关进出口数据库,将能源密集型产业面临的环境压力划分为公众环境关注、非正式环境规制和正式环境规制,采用Logit模型综合探讨了环境压力对能源密集型产业动态的影响。研究发现：公众环境关注显著降低了能源密集型产业进入的概率,除环境建议与提案外,其他非正式与正式的环境规制均能够抑制能源密集型产业的进入。此外,在公众环境关注度高的区域,非正式和正式的环境规制对能源密集型产业进入的抑制作用更强。     

基于直升机耦合分析的振动响应预测研究

目的预测直升机振动响应。方法采用中等变形梁理论建立直升机旋翼桨叶结构有限元模型,以准定常气动力模型及Pitt动态入流理论模拟旋翼上的气动作用力,结合旋翼结构及气动模型形成旋翼动力学分析模型,并以旋翼动力学试验结果验证模型的正确性。基于Patran建立直升机机体动力学模型,根据旋翼动力学分析结果,筛选并提取机体模态信息。结果耦合旋翼动力学及机体动力学模型,形成直升机全机耦合动力学分析模型,采用时间有限元方法求解耦合模型,以此模型进行直升机机体振动响应预测及与试验对比分析研究。结论该方法机体振动响应计算值与试验值变化规律相同。