A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

基于BP神经网络的天线识别

本文比较研究了BP神经网络中的几种常用算法,针对这些不同算法下的BP神经网络进行训练,并得出了各自网络的性能。在此基础上,针对经典BP算法和LM算法进行对比研究,找到LM算法的改进之处。此外,在实际的应用中表明,不仅不同的BP算法对网络的运算速度、泛化能力等有较大的影响,而且BP神经网络对隐含层神经元数目也很敏感。我们希望在BP神经网络的基础上,构建一种合适的天线模型,来应用于天线的分类识别,这将具有很大的现实意义。     

Effect of Monitoring Technique on Quality of Conservation Science

Monitoring free‐ranging animals in their natural habitat is a keystone of ecosystem conservation and increasingly important in the context of current rates of loss of biological diversity. Data collected from individuals of endangered species inform conservation policies. Conservation professionals assume that these data are reliable—that the animals from whom data are collected are representative of the species in their physiology, ecology, and behavior and of the populations from which they are drawn. In the last few decades, there has been an enthusiastic adoption of invasive techniques for gathering ecological and conservation data. Although these can provide impressive quantities of data, and apparent insights into animal ranges and distributions, there is increasing evidence that these techniques can result in animal welfare problems, through the wide‐ranging physiological effects of acute and chronic stress and through direct or indirect injuries or compromised movement. Much less commonly, however, do conservation scientists consider the issue of how these effects may alter the behavior of individuals to the extent that the data they collect could be unreliable. The emerging literature on the immediate and longer‐term effects of capture and handling indicate it can no longer be assumed that a wild animal's survival of the process implies the safety of the procedure, that the procedure is ethical, or the scientific validity of the resulting data. I argue that conservation professionals should routinely assess study populations for negative effects of their monitoring techniques and adopt noninvasive approaches for best outcomes not only for the animals, but also for conservation science. Efecto de la Técnica de Monitoreo en la Calidad de la Ciencia de la Conservación     

可持续发展环境约束条件下的水资源最优配置及实证研究

在相关理论分析和Weber模型的基础上。拓展建立了面向水资源可持续发展的水资源最优配置模型。引入了基于政府管制的影响作用、沿河流域的水用户的实际消耗水量、实际排放水量、河流中可供使用水量及所排放污水水质水平等5个变量函数．通过政府管制下的水质和水量的河道内流量需求等环境约束条件．确保水资源利用始终满足最小基流水量。通过求量优解，计算得出在环境约束下达到最优配置时各个变量函数与对下游地区外部性之间的相关性。接着。本文对陕北黄土高原沿Y河的35家企业进行了实际调查．收集了2个年度共8个季度的观测值，应用计量经济Pand Data模型。对35个节点、8个季度的共280个数据作为混合样本进行经济计量分析。验证了相关结论。最后。还提出一些制定环境约束条件以及水用户间建立水资源环境生态补偿金机制等政策建议。     

Presence–Absence versus Abundance Data for Monitoring Threatened Species

Abstract:  Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola ( Hylacola pyrrhopygia parkeri ), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence–absence surveys, under financial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence–absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence–absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence–absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence–absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.     

土地督察对土地市场化的影响效果评估

为评估土地督察对土地市场化的影响,论文把目标分解为两个问题:即土地督察制度的实施是否对土地市场化程度产生影响;如果有影响,影响的效果如何。论文收集了2003—2009年的省级面板数据,基于固定效应和随机效应模型估计了土地督察对土地市场化的影响。通过相关检验,采用了固定效应模型的估计结果,并在模型估计的基础上,对影响效果进行了评价。结果表明:①土地督察对土地市场化的发展有积极的促进作用,2007—2009年专项督察覆盖度每提高1%,约能促进土地市场化程度提升0.14%,例行督察覆盖度每提高1%,约能促进土地市场化程度提升1.12%;②通过实施专项督察,2007—2009年全国土地市场化程度分别提升了2.06%、 0.19%和0.55%,通过实行例行督察,2008—2009年全国土地市场化程度分别提升5.01%和12.47%;③2007—2009年通过开展土地督察,全国土地市场化程度分别提高了2.04%、 5.21%和13.02%。     

几种网格数据处理方法的应用与评述

对于利用网格布点所测得数据的处理,可采用积分法、趋势面法、多项式法和平均值法,各种处理方法各有其特点。平均值法计算简单,各个网格权重相同,意义明了,但精度不高;积分法和趋势面法考虑到了位于中心的网格对整个区域的贡献率大,组成的三角形多,统计时利用次数就多,边缘的网格数据利用次数少,物理意义明确。积分法还可计算总量,趋势面法可以在图上表示区域分布及变化趋势;多项式法除了计算其平均值外,还可模拟测定值,可计算测得数值序列趋势值和偏差值,分析污染物分布及变化情况。使用时要根据分析对象的物理意义及研究目的不同,选择不同的数学模型和计算公式。     

基于数据挖掘算法和数值模拟技术的大气污染减排效果评估

近年来,京津冀地区采取了大量污染减排措施进行大气污染治理,如何客观评估减排效果是目前大气环境领域的研究难点.为准确评估大气污染过程的减排效果,本文利用北京地区常规气象资料、国控站PM_(2.5)浓度资料,遴选了北京地区2018年3月11—14日和2013年3月14—17日两次空气污染过程,计算了大气容量系数、静稳指数,并利用KNN数据挖掘算法和WRF-Chem模式,对比分析了有无减排条件下的PM_(2.5)日均浓度.结果表明:两次空气污染过程的天气形势和局地气象条件较相似,就大气热力和动力的垂直结构来看,2018年空气污染过程比2013年空气污染过程的大气稳定性更强、边界层高度更低、环境容量更小,但PM_(2.5)峰值浓度却显著下降,平均浓度明显降低,PM_(2.5)小时浓度的增长趋势相对平缓,重污染持续时间缩短.KNN数据挖掘算法减排评估结果显示,该方法能够较好地预测PM_(2.5)日均浓度的变化趋势,2018年3月11—14日,在减排和不减排情景下PM_(2.5)日均值分别为171和229μg·m~(-3),减排使得污染过程PM_(2.5)平均浓度下降了25.3%.数值模拟结果与KNN数据分析结论吻合,进一步验证了减排措施的有效性.综合看来,2018年空气污染过程中PM_(2.5)浓度相比历史相似气象条件下的污染过程显著降低,这是长期大力度减排效果的体现.