Estimation of tree transpiration and response of tree conductance to meteorological variables in desert-oasis system of Northwest China

Transpirations of three dominated tree species, namely Mongol Scotch Pine (Pinus sylvestris var. mongolica Litvin), White elm (Ulmus pumila) and Gansu Poplar (Populus gansuensis Wang et Yang) in oasis shelter forest (Linze site) and of two dominated tree species,namely Euphrates Poplar (Populus euphratica Oliv.) and Russia olive (Elaeagnus angustifolia Linn.) in lowland desert (Erjinaqi site) have been estimated using measured sapflow in summer,autumn and winter, 2002 and in spring, 2003. An ENVIS System was used for each site to measure microclimate variables, soil moisture and sapflow every half an hour, and the study time scale is one day. In the 104 days of observation during the growing season at the Linze site, the average daily sapflow of Gansu Poplar is 9.93L·d-1,and the average transpiration per unit leaf area is 1.99mm·d-1.For White elm tree,the daily average sapflow is 4.08L·d-1,while the daily average transpiration per unit leaf area is 0.49mm·d-1.The values for Mongol Scotch Pine are 3.91L·d-1 and 0.25mm·d-1,respectively.In the total 73 days of observation during the growing season at the Erjinaqi site, the daily average sapflows of Russia olive and Euphrates Poplar are 12.1 and 20.97L·d-1,respectively,and the average transpirations per unit leaf area are 0.22 amd 0.31mm·d-1,respectively.In the observation period of the growing season,tree conductances of Mongol Scotch Pine, White elm, Gansu Poplar or Russia olive show an exponential relationship with the daily average air temperature or vapour pressure deficit, but the relationship is not so obvious between tree conductance and global radiation. The transpiration process of each tree species is affected by all the observed four environmental variables. The response of tree conductance to different climatic factors changes with tree species. The effect of the same factor to the same tree species is also variable in different growing stages. The sapflow of every tree species is relatively large in later spring to early summer, and low in summer, and then reaches its largest value in later September. In the mid-November, the sapflow is relatively large, especially the deciduous tree species. This may be characteristic of the tree species in Arid Regions of Northwest China.     

Non-destructive assessing and monitoring of populations of Isoetes lacustris L

Extensive studies of Isoetes lacustris, performed throughout Europe, resulted in regressions between the number of leaves per rosette and (1) the number of spores per megasporangium, (2) length of seasonal growth, (3) Secchi depth and (4) water colour plus a relationship between pH and the number of spores per megasporangium. The evaluation of Isoetes populations requires measurements of the lake data Secchi depth, water colour, pH and conductivity, the establishment of climate data and leaf counts on 20–30 plants with the aid of SCUBA. The method may be applied to lakes in a range of situations, varying between lowland and highland, and between temperate and subarctic climate regions. The regressions are displayed graphically. The actual mean leaf number and corresponding megaspore number are compared with the numbers referred to in the environmental data. Consistent values point to the parameters which influence growth and vitality of the quillwort and to what extent, in a particular lake. Examples of evaluation and monitoring are given.     

基于冠层反射光谱的水稻产量预测模型

基于地面实测的水稻冠层反射光谱,计算了常用的8个植被指数,并在产量形成生理特征的基础上,系统分析了水稻籽粒产量及其构成因素与各植被指数之间的关系。结果表明,通过单一生育时期或某个生育阶段的光谱植被指数来直接估测产量精度较低。发现叶面积氮指数(叶片氮百分含量与叶面积指数的乘积)的变化趋势很好地反映了产量的形成过程,且与光谱植被指数极显著正相关,基于此建立了水稻的光谱植被指数-累积叶面积氮指数-产量估测模型(VICLANIYieldModel)。并将其与LAD-产量模型、多生育期复合估产模型进行了比较,表明本模型预测精度最高。     

Identifying insect infestation hot spots: an approach using conditional spatial randomization

Epidemic populations of mountain pine beetle highlight the need to understand landscape scale spatial patterns of infestation. The observed infestation patterns were explored using a randomization procedure conditioned on the probability of forest risk to beetle attack. Four randomization algorithms reflecting different representations of the data and beetle processes were investigated. Local test statistics computed from raster representations of surfaces of kernel density estimates of infestation intensity were used to identify locations where infestation values were significantly higher than expected by chance (hot spots). The investigation of landscape characteristics associated with hot spots suggests factors that may contribute to high observed infestations.     

REVIEW ARTICLE MULTIVARIATE EXPLORATORY DATA ANALYSIS AND GRAPHICS:A TUTORIAL

Exploratory data analysis(EDA)is a toolbox of data manipulation methods for looking at data to seewhat they seem to say,i.e.one tries to let the data speak for themselves.In this way there is hope thatthe data will lead to indications about'models'of relationships not expected a priori.In this respect EDAis a pre-step to confirmatory data analysis which delivers measures of how adequate a model is.In thistutorial the focus is on multivariate exploratory data analysis for quantitative data using linear methodsfor dimension reduction and prediction.Purely graphical multivariate tools such as 3D rotation andscatterplot matrices are discussed after having introduced the univariate and bivariate tools on which theyare based.The main tasks of multivariate exploratory data analysis are identified as'search for structure'by dimension reduction and'model selection'by comparing predictive power.Resampling is used tosupport validity,and variables selection to improve interpretability.     

Biomass production of different ecotypes of threegrass species of the semi-arid grasslands of southern Africa

Biomass production of different ecotypes within three ecological importantgrass species was determined during cultivation under uniform environmental conditions. Results obtained clearly indicate that ecotypes of these species exhibit a significant degree of variation with regard to biomass production. Furthermore, indications from this investigation are that no correlation exists between production ability of a species and long-term average rainfall, and the effect of both genetic and environmental factors on the production ability of a species determines the eventual biomass production of a species. Biomass production represents one of various ecologically important characteristics to be used in conjunction with other ecological characters to construct a usable, special purpose classification system. This system will assist rangeland ecologists in identifying functional ecotypes within grass species, thus facilitating the understanding and interpretation of vegetation dynamic models and rangeland condition assessments.     

基于TM数据的植被覆盖度反演

本文首先对TM影像进行了几何纠正、辐射校正、大气校正;然后根据混合像元的结构特征,利用TM数据从植被指数(NDVI)中采用“等密度模型”和“非密度模型”提取了宜昌南部地区的植被覆盖度。在用“非密度模型”反演植被覆盖度的过程中,叶面积指数(LAI)是一个必要的参数,本文提出了一种改进的借助可见光波段和近红外波段反射值来提取叶面积指数(LAI)的方法。通过和MODIS数据反演结果比较表明:“非密度模型”的估算精度要高于“等密度模型”;利用“等密度模型”和“非密度模型”反演植被覆盖度是可行。     

应用LSF概念模型反演草冠层叶面温度的试验

试验在已知土壤表面温度的前提下，分别利用AVHRR卫星遥感资料和准同步地面观测数据，应用LSF概念模型成功反演了草冠层叶面温度。通过对星、地资料反演的草冠层叶面温度比较发现，二者反演结果相差小于0．2K，说明利用卫星遥感资料，应用LSF概念模型反演草场冠层叶面温度可获得比较满意的结果。假设其他参数不变，分别对不同叶面发射率和不同土壤表面发射率反演的叶面温度分析发现，组分发射率的估算精度对反演结果影响较小，而整层空气柱可降水量的估算精度对卫星资料反演草冠层叶面温度影响大，用探空资料和露点温度估算的整层空气柱可降水量可导致反演的叶面温度相差达1．1K。在水分供应充足条件下，晴天11：00-17：00时，即使太阳总辐射强，叶面温度的变化幅度比土壤表面温度、空气温度小。以1999年8月6日为例，叶面温度变化仅有1．22K，而同时土壤表面温度变化为9．5K，1．5m高的空气温度变化为6．0K，叶面温度变化幅度比土壤表面温度、空气温度平缓。试验结果还表明，采用Becker和李召良的分裂窗模型反演青藏高原东南缘地区的陆地表面温度效果较好。     

基于MODIS图像的植被叶面水反演与农业干旱监测

研究了应用MODIS数据,采用与植被物种无关的GVMI指数模型反演出植被水含量指标EWT,并以气象局发布的实际温度降雨数据和旱灾报告验证了植被水含量与旱灾的相关性。     

水稻叶片不同光谱形式反演叶绿素含量的对比分析研究

通过对常优1号和武粳15两个品种水稻叶片的反射率R、lg(1/R)、反射率一阶微分（FD）和反射率归一化（BN）等光谱形式的测量和计算，分析了叶片光谱不同变化形式与叶绿素含量的相关关系，建立了统计方程，并进行了比较与评价，同时，对反演方程的最佳波段选择进行了探讨。结果表明，叶绿素含量与反射率一阶微分光谱方程的相关性最强，而采用lg(1/R)的光谱形式能够提高遥感反演叶绿素含量的效果。经验证，两个水稻品种叶绿素含量的模拟值与实测值的复相关系数R2分别达到0.641和0. 818。