拟松材线虫对黑松致病性研究

松材线虫病（Ｂｕｒａｐｈｅｌｅｎｃｈｕｓｍｕｃｒｏｎａｔｕｓ）是发生在松树上的一种毁灭性病害 ,目前已在日本、中国、美国、加拿大和韩国等分布 ,并在日本和中国造成巨大的损失。在北美洲 ,松材线虫分布也很广。针叶树中还有一些形态与松材线虫非常相近的伞滑刃线虫 ,统称松材线虫复合种（ＰＷＮＣ） ,其中最常见的是拟松材线虫。拟松材线虫在东亚、美洲、欧洲都有 ,分布极广泛。杂交试验和ＤＮＡ分析证实松材线虫和拟松材线虫有密切的关系 ,能用ＲＡＰＤ和ＲＦＬＰ技术进行区分 ,拟松材线虫的ＤＮＡ有东亚和欧洲两种类型 ,前者主要分…     

松林线虫群体致病性测定和潜伏侵染的探讨

由松材线虫（Ｂｕｒｓａｐｈｅｌｅｎｃｈｕｓｘｙｌｏｐｈｉｌｕｓ）引起的松树萎蔫病 ,是松树上的一种毁灭性病害 ,已在日本、美国、黑西哥、加拿大、韩国发生和流行。目前松材线虫的发生范围还在继续扩大。我国最早在１９８２年秋于南京紫金山的松林中发现该病 ,当年仅见枯树２６０株 ,现已查明在苏、浙、粤、皖、港、台均有分布 ,各地呈迅速扩展蔓延趋势。至１９９９年底该病在我国的发病面积已超过６０万公顷 ,累计死树１６００万株 ,直接经济损失１．２８亿元。ＴｏｍｏｙａＫｉｙｏｈａｒｅ从日本松材线虫分布区内收集到３７个线虫群…     

松材线虫病危害的马尾松林木光谱特征分析

松材线虫是一种危险的外来入侵种,对我国的森林资源破坏很大。而遥感技术作为一种先进的空间信息技术,在森林病虫害监测方面具有独特优势,而受害林木实测光谱的研究对于遥感监测具有重要的意义。通过对马尾松4种不同受害类型的林木进行反射光谱测量,并对光谱反射曲线进行一阶微分分析,研究了绿光区、红光区和近红外区反射光谱的变化特征,为应用遥感技术研究松材线虫入侵过程中,森林资源动态变化提供了实验依据。     

科尔沁沙地黑沙蒿人工植被土壤线虫群落特征

本文针对科尔沁沙地黑沙蒿人工植被土壤线虫的总数、群落组成、营养类群进行了研究。结果表明,随着黑沙蒿种植年限的增加,土壤线虫数量显著增加。不同年限黑沙蒿植被之间土壤线虫总数差异显著(P<0.01)。在本研究中共获得线虫13科19属,其中Acrobeles为优势属。在半流动沙丘生态系统中,植物寄生线虫为优势营养类群;而在黑沙蒿人工植被生态系统中,线虫群落逐渐向以食细菌线虫占优势的方向演替。本实验结果表明,土壤线虫群落结构对退化沙漠生态系统的恢复阶段具有很好的生物指示作用。     

松材线虫病害高光谱时序与敏感特征研究

采用高光谱仪ASD FieldSpec Pro FR,连续观测了健康和发病马尾松针叶的时序高光谱,分析了松材线虫病害光谱的时序特征、敏感时期和敏感特征。结果表明:与健康马尾松相比,病害马尾松时序光谱差异较大;病害首先造成红边区域内光谱反射率减低,然后再出现红边蓝移的2阶段光谱变化规律;感染松材线虫的马尾松9月初已经出现了病态植被典型的光谱特征;近红外平台内最大的一阶微分值、红边内一阶微分的总和(SDr)与蓝边内一阶微分的总和(SDb)的比值等是指示病害发生的显著性高光谱特征。     

多点肥料效应函数方程分类与土壤养分相关性研究

采用主成分分析方法对多点动态肥料试验聚类分析结果与土壤养分间的关系进行了研究。结果表明,土壤氮素状况是分类的第一主因子,磷素状况是第二主因子,有机质含量是第三主因子。确定类肥料效应函数应用范围的主要依据是土壤碱解氮和全氮含量,其次是土壤有效磷含量,再次是土壤有机质含量。     

陆地碳循环中的微生物分解作用及其影响因素

土壤微生物是有机物的主要分解者,在陆地生态系统碳循环中扮演着重要角色,土壤微生物活性与底物性质和环境因子密切相关,环境条件的改变对微生物的分解活动影响很大。本文概述了制约有机物分解的因素,包括有机物自身的物理化学性质、非生物因素(温度、水分和通气状况、pH值、粘粒含量、激发效应等)和生物因素等。人为活动(如土地利用/覆被变化)和气候变暖对土壤微生物活性具有一定的影响并产生相应的陆地碳循环变化。最后提出了陆地生态系统碳循环与土壤微生物驱动相关联的研究热点问题。     

土壤生物的生态学研究

土壤生物是土壤圈的核心组分,对土壤的矿质营养循环起推动作用。土壤中食物资源的质量状况影响着各生物类群的数量动态和分布,归根结底是由田间管理措施改变了土壤的结构、营养和生物条件引起的。反过来,生物类群的结构和数量变动以及分布特点又可以反映土壤的状况及可持续性。本文逐次对土壤微生物、原生动物、线虫及小型节肢动物的生态学研究作了概述,并分析比较了各生物类群在土壤生态系统中的功能作用。     

多年生樟子松人工纯林生长衰退及地力衰退原因分析

对章古台地区不同林龄樟子松生长状况和土壤肥力状况进行调查，结果证实多年生樟子松人工纯林存在生长衰退及地力衰退问题。应用双重筛选逐步回归方法，找出影响樟子松树高和胸径生长的主导因子分别为土壤中速效磷含量、最大持水量及土壤有机质含量和全氮含量。对40年生樟子松纯林和樟子松杨树混交林进行比较分析，发现混交林中樟子松生长量和林地土壤肥力均较纯林高，因此营造混交林是防治樟子松生长衰退及地力衰退的有效措施之一。     

影响土壤磷有效性变化作用机理

土壤磷有效性对植物生长以及磷的生态系统生物循环过程具有重要意义,一直以来也是国内外磷素研究的重点之一,文章综合介绍了土壤环境中影响磷有效性的一些因子及其作用机理,以期为系统的认识土壤中磷的有效性的变化提供借鉴。     

A hybrid pansharpening approach and multiscale object-based image analysis for mapping diseased pine and oak trees

We developed a multiscale object-based classification method for detecting diseased trees (Japanese Oak Wilt and Japanese Pine Wilt) in high-resolution multispectral satellite imagery. The proposed method involved (1) a hybrid intensity–hue–saturation smoothing filter-based intensity modulation (IHS-SFIM) pansharpening approach to obtain more spatially and spectrally accurate image segments; (2) synthetically oversampling the training data of the ‘Diseased tree’ class using the Synthetic Minority Over-sampling Technique (SMOTE); and (3) using a multiscale object-based image classification approach. Using the proposed method, we were able to map diseased trees in the study area with a user's accuracy of 96.6% and a producer's accuracy of 92.5%. For comparison, the diseased trees were mapped at a user's accuracy of 84.0% and a producer's accuracy of 70.1% when IHS pansharpening was used alone and a single-scale classification approach was implemented without oversampling the ‘Diseased tree’ class.     

A hyperspectral GA-PLSR model for prediction of pine wilt disease

Pine wilt disease caused by a forest-invasive alien species, the pine wood nematode (Bursaphelenchus xylophilus) is considered as one of the most destructive pest problems. In recent years, spectroscopic technologies have shown great potentials for the assessment of forest damage due to their nondestructive, noninvasive, cost-effective, and rapidly responsive nature. This paper first identified the hyperspectral characteristics of pine wilt disease by measuring and analyzing the changes in spectral reflectance of healthy and infected Pinus massoniana trees. Then 16 spectral features were extracted from the spectral bands covering the green region (510~580 nm), the red region (620~680 nm), the red edge (680~760 nm), the near-infrared region (780~1100 nm), and coded as genes composing the chromosome of a genetic algorithm (GA). Based on the optimal spectral features with suitable fitness from the GA, a partial least squares regression (PLSR) prediction model was built with highest determination coefficient R²_c?=?0.91, R²_v?=?0.82, relative prediction deviation RPD?=?3.3 and lowest root mean square error RMSE_c?=?0.23, RMSE_v?=?0.33 on the calibration and validation datasets. Compared with other PLSR models, our proposed GA-based approach significantly improves the prediction accuracy with few input spectral features.

     

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were recorded at 400 Hz over three intensive areas of 1 km² where transects were spaced at 200 m, and along 64 transects spaced 1 km apart (total of ca. 2500 km²). LIDAR and field measurements of canopy height were similar in the three intensive study areas, with the 80th percentile of LIDAR returns explaining the greatest amount of variability (79%). Correlations between LIDAR data and aboveground tree biomass measured in the field were highly significant when all three 1 km² areas were analyzed collectively, with the 80th percentile again explaining the greatest amount of variability (74%). However, when intensive areas were analyzed separately, correlations were poor for Oak/Pine and Pine/Scrub Oak stands. Similar results were obtained using FIA data; at the landscape scale, mean canopy height was positively correlated with aboveground tree biomass, but when forest types were analyzed separately, correlations were significant only for some wetland forests (Pitch Pine lowlands and mixed hardwoods; r² = 0.74 and 0.59, respectively), and correlations were poor for upland forests (Oak/Pine, Pine/Oak and Pine/Scrub Oak, r² = 0.33, 0.11 and 0.21, respectively). When LIDAR data were binned into 1-m height classes, more LIDAR pulses were recorded from the lowest height classes in stands with greater shrub biomass, and significant differences were detected between stands where recent prescribed fire treatments had been conducted and unburned areas. Our research indicates that single-beam LIDAR can be used for regional-scale (forest biomass) estimates, but that relationships between height and biomass can be poorer at finer scales within individual forest types. Binned data are useful for estimating the presence of ladder fuels (vertical continuity of leaves and branches) and horizontal fuel continuity below the canopy.     

Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies

Leaf chlorophyll content in coniferous forest canopies, a measure of stand condition, is the target of studies and models linking leaf reflectance and transmittance and canopy hyperspectral reflectance imagery. The viability of estimation of needle chlorophyll content from airborne hyperspectral optical data through inversion of linked leaf level and canopy level radiative transfer models is discussed in this paper. This study is focused on five sites of Jack Pine (Pinus banksiana Lamb.) in the Algoma Region (Canada), where field, laboratory and airborne data were collected in 1998 and 1999 campaigns. Airborne hyperspectral CASI data of 72 bands in the visible and near-infrared region and 2 m spatial resolution were collected from 20×20 m study sites of Jack Pine in 2 consecutive years. It was found that needle chlorophyll content could be estimated at the leaf level (r²=0.4) by inversion of the PROSPECT leaf model from needle reflectance and transmittance spectra collected with a special needle carrier apparatus coupled to the Li-Cor 1800 integrating sphere. The Jack Pine forest stands used for this study with LAI>2, and the high spatial resolution hyperspectral reflectance collected, allowed the use of the SPRINT canopy reflectance model coupled to PROSPECT for needle chlorophyll content estimation by model inversion. The optical index R750/R710 was used as the merit function in the numerical inversion to minimize the effect of shadows and LAI variation in the mean canopy reflectance from the 20×20 m plots. Estimates of needle pigment content from airborne hyperspectral reflectance using this linked leaf-canopy model inversion methodology showed an r²=0.4 and RMSE=8.1 μg/cm² when targeting sunlit crown pixels in Jack Pine sites with pigment content ranging between 26.8 and 56.8 μg/cm² (1570-3320 μg/g).     

Estimation of tree growth in a conifer plantation over 19 years from multi-satellite L-band SAR

The general capability of synthetic aperture radar (SAR) for monitoring forest ecosystems is well documented. However, the majority of SAR studies of forest dynamics use only imagery acquired by one SAR system and are thus limited to the lifecycle of a particular satellite. The synergistic analysis of SAR data from one of the earliest spaceborne SAR missions, the SEASAT mission, with the Japanese JERS-1 satellite-borne SAR is presented. Biophysical parameters frequently retrieved from SAR are tree biomass using backscatter and tree height from the interferometric phase. One potential application that has not been thoroughly examined is mapping of incremental tree growth from SAR backscatter changes. Tree growth measures biomass changes over time, and is correlated to the amount of carbon sequestered by the trees. This paper examines the retrieval of tree growth from multitemporal spaceborne L-band SAR. A SEASAT SAR image from 1978 and a JERS-1 SAR image from 1997 over Thetford forest, UK are used to retrieve tree growth of Corsican Pine stands. Incremental growth was estimated from the changes in backscatter coefficient, and compared to the expected tree growth from general yield class models used by the UK Forestry Commission. The accuracy of the retrieval algorithm depends on the minimum forest stand size included in the analysis. For managed forest plantations, multitemporal L-band SAR has some potential for detecting incremental biomass to support sustainable forest management.     

森林病虫灾害的航空录像监测技

摘要:我国自20世纪90年代中期开始引进和消化吸收航空录像监测系统,该系统主要由数据获取、数据处理、灾害区(点)现地调查和飞行器4个部分组成。主要介绍了该系统的应用方法,以及在我国重大森林病虫害--松毛虫和松材线虫灾害监测生产中的研究应用情况。生产实践表明,这种集成了遥感、地理信息系统和全球定位系统技术的监测系统,具有灵活、方便、机动性强、成本低廉的优势,在森林病虫灾害的监测中将大有可为。关　键　词:森林病虫害;监测;航空录像中图分类号:TP 79     

Elevation changes in Pine Island Glacier,Walgreen Coast,Antarctica, based on GLAS (2003) and ERS‐1 (1995) altimeter data analyses and glaciological implications

The Geoscience Laser Altimeter System (GLAS) aboard ICESat, launched in January 2003, has been designed to detect and monitor changes in the cryosphere. The first objective of this paper is to present high‐resolution ice‐surface elevation maps derived from GLAS data, using geostatistical analysis. In a regional study of Walgreen Coast and Northern Ellsworth Land, West Antarctica, differences in the representation of geographic and morphologic features in maps based on ERS‐1 radar altimeter data and on GLAS data are investigated, with the result that in particular in topographically complex coastal areas and the margin of the ice sheet the improvement in precision and accuracy of the laser altimeter is significant.

A second, applied objective is to map elevation changes in Pine Island Glacier, a glacier that plays a key role in the question of stability of the West Antarctic Ice Sheet and has been changing rapidly in recent years. Results of elevation differencing of 2003‐GLAS‐data and 1995‐ERS‐1‐radar‐altimeter‐data DEMs (1) show that thinning rates have been increasing and (2) are applied to attribute the observed changes in Pine Island Glacier to internal processes in the glacier, related to dynamic thinning. More generally, this application serves to demonstrate that GLAS data facilitate study of cryospheric change.     

基于遍历序列的唯一确定树或二叉树的方法

基于遍历序列的唯一确定树或二叉树的方法既体现了树或二叉村的遍历序列的部分性质,又是建立树或二叉村的存储结构的主要依据,本文首先介绍了由一棵二叉树的某两种遍历序列或某种遍历序列和结点的某种信息可以唯一确定该二叉树的各种可能方法,然后分别针对树、严格二叉树与雨季叉排序树加以介绍,本文比较全面的介绍了基于遍历离列的唯一确定树或二叉树的方法,进一步完善了树或二叉树的遍历序列的性质。