Multistate models for monitoring individual trees in permanent observation plots

This interdisciplinary research on forest ecosystems begins with some characteristics of ecosystems which are the basis for the derivation of statistical models for the development and vitality of trees. Several ecological problems which could be solved by longitudinal studies are mentioned. Statistical methods for the evaluation of the crowns of spruce trees (Picea abies Karst) in three permanent observation plots in Switzerland are described. In particular, the time-dependent proportional odds model and a transitional model are used. Through application of these multistate models the data give information on the dependence of an ordered categorical response variable on covariates characterizing the ecosystem. The response variable is observed through infrared aerial photographs. This monitoring system gives insight into the dynamic behaviour of the forest ecosystem. The need for more eco-systematically motivated statistical research using longitudinal studies is identified.     

拟面积多波长数据线性双组合解析萘,1—萘酚和2—萘酚同步荧光光谱的研究

本文研究了Δλ（λｅｍ－λｅｘ）为１３０ｎｍ和ＰＨ１２．０条件下，萘、１－萘粉和２－萘酚混合物的同步荧光光谱，获三者同步荧光峰信息，且萘被完全分辨，另外，提出用拟面积多波长线性双组合计算解析重叠的１－萘酚和２－萘酚同步荧光光谱，解析结果的精密度、组份间浓度比范围均较多波长线性回归、双峰增配平和一阶导数解析混合物同步荧光光谱结果为优。     

Linear regression with Type I interval- and left-censored response data

Laboratory analyses in a variety of contexts may result in left- and interval-censored measurements. We develop and evaluate a maximum likelihood approach to linear regression analysis in this setting and compare this approach to commonly used simple substitution methods. We explore via simulation the impact on bias and power of censoring fraction and sample size in a range of settings. The maximum likelihood approach represents only a moderate increase in power, but we show that the bias in substitution estimates may be substantial.     

Soil Lead and Children’s Blood Lead Levels in Syracuse, NY, USA

A geo-referenced data set of 12 228 first-time blood lead screening values for Syracuse, NY, children was established for the 4-year period 1992–1996. Soil lead values were measured in a 600 m by 600 m tessellation grid covering the city. The two data sets were merged for evaluation of relationships between them. Strong seasonal variation in blood lead levels suggests the importance of contaminated soils as an exposure source. When the data were aggregated at a large geographic scale (3 km²), a logarithmic model showed an R² of > 0.65 for the regression of geometric mean blood lead on median soil lead values. Results showed a striking similarity to those obtained by Mielke et al. (1999) for a study in New Orleans, LA, USA.     

Bayesian analysis under ordered functions of parameters

Ordered parameter problems arise in a wide variety of real world situations and are dealt with extensively in the literature. Traditional frequentist methods for dealing with these problems are rather complicated theoretically, especially when sample sizes are small. Bayesian methods are not widely used because high dimensional numerical integration is often required. However, Markov chain Monte Carlo methods provide alternatives to such numerical integration and also deal with ordered parameter problems in a straightforward manner. Little is known about the situation where functions of parameters are ordered. Such problems may seem to be of little practical concern initially, but one can readily see their importance in situations where ordering is placed on the means and variances of several normal or Gamma populations. For the Gamma distribution we will present real examples where we will analyze monthly precipitation data from San Francisco, California and Oakland Mills, Iowa. For the San Francisco data we will simultaneously order both monthly precipitation means and variances. For the Iowa data we will place ordering on seasonal average while still estimating monthly means. Our results show that we would obtain sharper, more accurate inference when order restrictions are employed.     

在环境地学研究中应用GIS急需解决的问题分析

地理信息系统已经成为环境地学的常用工具，但主要被用来存储和显示地图，没有发挥其应有的功能。本文认为多源空间数据集成、空间数据分析和挖掘队及模型集成等是其中三个最主要问题。多源环境数据集成是基础，空间分析是连接多源数据集成与模型集成的桥梁和纽带，数据通过这个桥梁传输给模型，模型对环境系统进行模拟和仿真。这些问题的解决有利于更好地在环境地学中应用地理信息系统。     

HKB—1型磁化率仪研制及计算机联机的实现

本文介绍了一种新研制的磁化率仪,它可测定自然界中大多数物质(良导体除外)的初始磁化率,特别适合于岩石的磁化率及其各向异性(AMS)测量。仪器工作磁场300A/m,频率920Hz,样机总磁化率测量灵敏度达到 2×10~(-12)m~3,读数采用数字显示方式并具有自动锁定功能。与计算机的联机采用了标准EIARS-232C串行接口,因此具有良好的通用性。在软件的控制下,计算机可自动完成测量数据的采集、计算处理、座标转换以及成图或存贮等工作,AMS参数的测量效率得到很大提高。     

排污申报数据审核的一般方法

排污申报登记工作具有数据量大、逻辑性强、专业要求高的特点,环保部门必须力求通过强化数据的审核来获得完整、准确的排污申报数据。     

基于CESM-EnSRF系统全球甲烷及臭氧卫星资料同化试验研究

臭氧(O3)与甲烷(CH4)均是大气中重要的微量气体,对全球气候变化有着重要的影响.为提高全球范围的臭氧、甲烷在气候模式中的预报效果,使用集合平方根滤波(En SRF)同化方法及地球系统模式(CESM)构建了CESM-En SRF卫星资料同化预报系统,并通过设计试验,将大气红外探测器(AIRS)的臭氧与甲烷观测资料同化到气候模式中,对模式的同化再预报效果进行系统的测试与评估.结果显示,臭氧、甲烷分析集合均值的偏差及均方根误差皆低于背景集合均值的偏差及均方根误差.臭氧、甲烷的同化再预报偏差及均方根误差较控制实验都得到改善,但对5 h Pa以上高度臭氧预报准确性的改进效果很小.随循环同化的进行,平流层臭氧与甲烷的平均同化改进率呈增加趋势,并逐渐趋于稳定;对流层平均同化改进率随时间变化不明显.试验表明,该系统可有效利用臭氧与甲烷的观测资料对模式场进行合理的改善,从而有效地提高臭氧、甲烷在气候模式中的再预报效果,但对于平流层顶-中间层高度(5 h Pa以上)臭氧预报准确度的提高,模式中臭氧光化学过程的准确模拟较同化观测资料具有更重要的作用.此外,循环同化对提高5~150 h Pa高度臭氧及1~200 h Pa高度甲烷在CESM模式中的预报效果最有效.     

生态环境监测服务平台设计——以宁波市为例

建成“一网-二库-二系统”的生态环境监测服务平台,为宁波市环境监测部门、政府管理部门、科研机构、社会公众等提供数据支持服务。介绍了该平台的总体架构、应用模式,以及实现、部署与应用。