红外光谱结合多元线性回归法快速测定木塑复合材料中木粉含量

采用KBr压片法对杉木/聚丙烯(PP)复合材料样品进行了红外光谱分析,确定杉木特征吸收谱带为1740~1730、1610~1590、1270~1260、1060~1050以及1040~1030 cm-1,以PP在1377 cm-1处吸收强度(I)为内标,对木塑复合材料(WPC)中木粉含量和杉木特征峰相对吸收强度进行相关性分析,并采用逐步多元线性回归法建立木粉含量与相对峰强间的多元线性回归方程。结果表明,选取I(1060-1050)/I1377、I(1270-1260)/I1377为回归变量建立的二元线性回归方程和以I(1060-1050)/I1377、I(1040-1030)/I1377及I(1270-1260)/I1377为回归变量建立的三元线性回归方程,具有较高的预测精度。木粉含量的预测值和参照值之间具有强烈的相关性,校正决定系数(R2c)超过0.98,验证决定系数(R2p)超过0.96。外部验证结果表明,线性回归方程预测准确性较高,预测相对偏差范围为0.9%至7.4%,其中三元线性回归方程预测准确性稍好于二元线性回归方程。     

硬岩抗剪强度参数的最优化确定法

为了减小岩工程分析计算的工作量和节约研究经费,须利用有限的室内实验样本的测定值,通过对有限实验样本数据的回归分析整理,确定岩石抗剪强度参数c、φ,进而估计岩体的抗剪强度c、φ.由于试验方法、试验条件等有一定局限性,因而,岩石力学参数的试验结果具有一定的不确定性.其不确定性包含随机性和模糊性.而用传统的数理统计方法处理岩石样本值,显然是不合适的,只有通过寻求最优的数学回归分析方法,来处理相关试验结果.笔者通过对硬岩变角度剪切实验和常规三轴压缩实验的数据回归分析,得到利用最小二乘法的抛物线回归分析结果和随机-模糊回归分析结果比较符合.因而,为了优化计算结果而又避免繁琐的计算,通常可以采用最小二乘法的抛物线回归分析计算代替随机-模糊回归分析相关结果.     

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes, where variations in tree growth and species composition occur over short distances. In this study, we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur, California. We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type, distance to edge, amount of surrounding non-forest vegetation, soil properties, fire history) and physiographic drivers (elevation, potential soil moisture and solar radiation, proximity to the coast) of tree growth at each plot location. Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km. Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution. Across randomly selected sample densities (sample size 112 to 280), ecological effects of vegetation community type and distance to forest edge, and physiographic effects of elevation, potential soil moisture and solar radiation were the most consistent predictors of biomass. Topographic moisture index and potential solar radiation had a positive effect on biomass, indicating the importance of topographically-mediated energy and moisture on plant growth and biomass accumulation. RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals. Regression kriging model, developed from RT combined with kriging of regression residuals, was used to map biomass across the Big Sur. This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop spatial models to predict and map biomass distribution across a heterogeneous landscape.     

北京八达岭人工油松林地表枯死可燃物负荷量研究

地表枯死可燃物负荷量多少是森林火灾发生的基础。调查八达岭林场不同地形条件下油松林地表枯死可燃物和林分因子,取得42块样地资料;用线性相关分析法对各因子与地表枯死可燃物负荷量进行分析,平均树高、坡度和海拔与对应负荷量有显著线性关系;应用多元线性回归中的逐步回归剔除法,建立了估测模型,除平均胸径外,平均树高、密度、郁闭度、海拔、坡度被引入,经检验回归显著,该估测模型可用于其它油松林地表可燃物负荷量估测。     

Water adsorption process of bamboo heated at low temperature

Water adsorption capacities were evaluated for moso bamboo samples that were heated at 200°C for various times and conditioned in a closed container at 97% relative humidity at 20°C. Logistic regression analysis was used for curve fitting to the adsorption data and its parameters were analyzed. These parameters were compared with those derived previously from the Dubinin and Radushkevich theory. The properties of the heat-treated samples changed after 5 h of heating. With less than 5 h of heating, hydroxyl groups provided the main adsorption sites but their numbers decreased on heating. After 5 h, gasifi cation of the bamboo increased and capillaries formed. Part of this article was presented at the 57th Annual Meeting of the Japan Wood Research Society, Hiroshima, August 2007     

二元立木材积模型的联立方程组估计方法

文章以兴安落叶松为例,使用联立方程组模型方法建立二元立木材积模型,该方法有效解决了二元立木材积模型的建模和预估前提不一致问题。在联立二元立木材积模型的估计中,分别采用了通常非线性估计方法和两步估计方法进行研究。研究结果证明:两种方法都能对模型进行估计,但两步估计可进一步减小系统偏差,达到通用性模型误差限要求,两步估计方法优于通常非线性估计。     

Identifying important biophysical and social determinants of on-farm tree growing in subsistence-based traditional agroforestry systems

Many expert-designed agroforestry projects enunciated in 1970s around the world, particularly in the developing countries, had uneven success due to inadequate adoption or abandonment after adoption. There are many empirical studies on factors affecting on-farm tree cultivation mainly where expert-designed agroforestry programmes were introduced but lacking in case of traditional agroforestry. Moreover, the concern to identify key factors influencing on-farm tree growing is gaining importance. The present study identifies key factors in on-farm tree growing based on investigation of traditional agroforestry using logistic regression approach. The study is based on household survey of 401 households located in Indian Western Himalaya. The factors affecting on-farm tree growing were grouped into: biophysical (included land use and infrastructural aspects) and social. Models predicting on-farm tree growing for each category were developed and key factors affecting on-farm tree growing in the respective category were identified. A composite model was also developed by combining biophysical and social factors. In the present study, farm size, agroclimatic zone, soil fertility, mobility and importance of tree for future generations respectively were the key factors which influenced tree growing. In contrast to many previous studies which considered either biophysical or social factors, the composite model in the present study reveals that both biophysical and social factors are simultaneously important in motivating the farmers to grow trees on their farms in traditional agroforestry. Moreover, the present study open vistas for using farmers’ experience and knowledge of adoption of agroforestry to stimulate on-farm tree growing. The wider implication of the study is that biophysical as well as social variables should be considered together in designing suitable agroforestry systems in various parts of the world.     

多元线性回归分析在经济林产品需求预测中的应用

详细分析了多元线性回归模型的基本原理,以5种水果为例,利用1991-2005年数据,论述多元线性回归在经济林产品需求预测的应用过程,最后依据所建模型对2006-2010年各水果需求进行预测及分析。     

我国杉木通用性立木生物量模型研究

以我国南方地区的最重要针叶树种杉木为研究对象,综合利用非线性混合模型、哑变量模型和误差变量联立方程组方法,建立了适合杉木不同生长区域（总体）应用的一体化一元和二元地上生物量方程及根茎比函数.结果表明：不同总体的地上生物量模型之间存在显著差异,总体（一）的估计值要大于总体（二）,而地下生物量则差异不明显;地上和地下生物量方程的平均预估误差分别在5％和10％以内,可应用于不同区域的杉木林生物量估计.