Climatic controls of vegetation vigor in four contrasting forest types of India—evaluation from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer datasets (1990–2000)

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R²=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests,a unique vegetation type mainly distributed in East Asia with the largest distnbution in China.It is important to be able to monitor and estimate forest biomass and production,regional carbon storage,and global climate change impacts on these important vegetation types.In this paper,we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region.Nineteen maximum normalized difference vegetation index(NDVI)composite images(acquisition time span of 7 months from February to August),which were derived from 10 days National Oceanographic and Atmospheric Administration(NOAA)Advanced Very High Resolution Radiometer(AVHRR)channel 1 and channel 2 observations,an unsupervised classification method,and the ISODATA algorithm were employed to identify the vegetation types.To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water,the images were processed using principal component analysis(PCA).The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system:evergreen broad-leaved forest,coniferous forest,bamboo forest,shrub-grass,aquatic vegetation,and agricultural vegetation.The spatial distribution and areal extent for the coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were calculated and comscale.The spatial accuracy and the area accuracy for coniferous forests,shrub-grass,evergreen broad-leaved forests,and agricultural vegetation were 79.2%,91.3%,68.2% and 95.9% and 92.1%,95.9%,63.8% and 90.5%,respectively.The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%,respectively;the spatial accuracy of aquatic vegetation was 69.6%,but there was a significant difference in its area accuracy because image acquisition did not cover the full year.Our study demonstrated the fea sibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China.The spatial location of the six identified vegetation types agreed with the actual geo graphical distribution of the vegetation types in East China.     

基于NOAA-AVHRR数据的中国东部地区植被遥感分类研究

该文采用 19幅 (时间跨 8个月 ) 时间序列的NOAA_AVHRR的归一化植被指数 (NDVI) 最大值合成影像遥感数据, 经过主分量分析 (Principlecomponentanalysis, PCA) 处理后, 用非监督分类方法的ISODATA算法, 对中国东部地区的 (五省一市 ) 植被进行分类, 结果可以分出 2 8种土地覆盖类型, 除了两种类型为水体和城市或裸地外, 其余 2 6种类型均为植被类型, 根据中国植被分类系统, 这 2 6类可以归并为 6大植被类型 :1) 常绿阔叶林 ;2 ) 针叶林 ;3) 竹林 ;4 ) 灌草丛 ;5 ) 水生植被 ;6 ) 农业植被。用 1∶10 0 0 0 0 0数字化《中国植被图集》的植被类型检验遥感分类结果表明, 针叶林、灌草丛、常绿阔叶林和农业植被的分类具有较高的位置精度和面积精度, 位置精度分别为 79.2 %、91.3%、6 8.2 %和 95.9%, 面积精度分别达到 92.1%、95.9%、6 3.8%和 90.5 %。这 6大植被类型在地理空间上的分布规律与中国东部常绿阔叶林区植被的地带性分布基本一致。     

Vegetation classification of East China with multi-temporal NOAA-AVHRR data

East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests, a unique vegetation type mainly distributed in East Asia with the largest distribution in China. It is important to be able to monitor and estimate forest biomass and production, regional carbon storage, and global climate change impacts on these important vegetation types. In this paper, we used coarse resolution remote sensing data to identify the vegetation types in East China and developed a map of the spatial distribution of vegetation types in this region. Nineteen maximum normalized difference vegetation index (NDVI) composite images (acquisition time span of 7 months from February to August), which were derived from 10 days National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) channel 1 and channel 2 observations, an unsupervised classification method, and the ISODATA algorithm were employed to identify the vegetation types. To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover of which two clusters were urban/bare soil and water, the images were processed using principal component analysis (PCA). The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system: evergreen broad-leaved forest, coniferous forest, bamboo forest, shrub-grass, aquatic vegetation, and agricultural vegetation. The spatial distribution and areal extent for the coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were calculated and compared with the Vegetation Atlas of China at a 1:1,000,000 scale. The spatial accuracy and the area accuracy for coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were 79.2%, 91.3%, 68.2% and 95.9% and 92.1%, 95.9%, 63.8% and 90.5%, respectively. The spatial accuracy and area accuracy of the bamboo forest were 28.7% and 96.5%, respectively; the spatial accuracy of aquatic vegetation was 69.6%, but there was a significant difference in its area accuracy because image acquisition did not cover the full year. Our study demonstrated the feasibility of using NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China. The spatial location of the six identified vegetation types agreed with the actual geographical distribution of the vegetation types in East China. __________ Translated from Acta Phytoecologica Sinica, 2005, 29(3): 436–443 [译自: 植物生态学报, 2005, 29(3): 436–443]     

Deforestation rates in insular Southeast Asia between 2000 and 2010

Insular Southeast Asia experienced the highest level of deforestation among all humid tropical regions of the world during the 1990s. Owing to the exceptionally high biodiversity in Southeast Asian forest ecosystems and the immense amount of carbon stored in forested peatlands, deforestation in this region has the potential to cause serious global consequences. In this study, we analysed deforestation rates in insular Southeast Asia between 2000 and 2010 utilizing a pair of 250 m spatial resolution land cover maps produced with regional methodology and classification scheme. The results revealed an overall 1.0% yearly decline in forest cover in insular Southeast Asia (including the Indonesian part of New Guinea) with main change trajectories to plantations and secondary vegetation. Throughout the region, peat swamp forests experienced clearly the highest deforestation rates at an average annual rate of 2.2%, while lowland evergreen forests declined by 1.2%/yr. In addition, the analysis showed remarkable spatial variation in deforestation levels within the region and exposed two extreme concentration areas with over 5.0% annual forest loss: the eastern lowlands of Sumatra and the peatlands of Sarawak, Borneo. Both of these areas lost around half of their year 2000 peat swamp forest cover by 2010. As a whole this study has shown that deforestation has continued to take place on high level in insular Southeast Asia since the turn of the millennium. These on‐going changes not only endanger the existence of numerous forest species endemic to this region, but they further increase the elevated carbon emissions from deforested peatlands of insular Southeast Asia thereby directly contributing to the rising carbon dioxide concentration in the atmosphere.     

金华北山南坡主要植被类型的群落特征

浙江省金华北山地处中亚热带北部, 在植被区划上属于中亚热带常绿阔叶林北部亚地带。该区植被是遭砍伐后恢复的次生林, 目前正处于快速的正向演替进程中, 这为研究常绿阔叶林植物群落动态演替机制及受损生态系统的恢复提供了平台。为进一步了解金华北山地区主要植被类型的群落特征, 该文以国际上通用的大样地调查方法, 采用固定样方对其南坡主要植物群落进行了调查, 其中森林样方面积30 m × 30 m, 灌丛样方面积为20 m × 10 m、30 m × 10 m。调查群落物种组成及其数量特征, 记录群落生境信息, 计算木本植物重要值, 分析群落的类型及特征, 并制作每个样方主要木本植物的空间分布图。论文提供了24组详细的群落样方数据(包括21个森林样方和3个灌丛样方), 含有11个群系。     

四川都江堰地区桢楠林、杉木林和常绿阔叶林土壤N库的季节变化

通过对四川都江堰地区桢楠（Phoebe zhennan）林、杉木（Cunninghamia lanceolata（Lamb．））林以及常绿阔叶林为期1a的研究,比较不同森林群落类型中N库各组分的大小以及季节动态,同时研究不同群落类型中N库各组分之间的关系,探讨植被、土壤特性以及微生物对N转化的影响。结果表明：①3种群落类型中土壤NH4^＋-N含量有明显的季节变化,均在冬季（12月份）达到最大。随着植物的生长,NH4^＋-N含量逐渐下降;②3种类型的群落土壤中NO3^--N含量的平均值差别很大,同一个森林群落类型在不同季节NO3^--N含量有明显的季节变化,但并不是所有的季节之间都存在显著差异;③3种森林群落类型在采样期内的土壤平均全N含量存在显著差别,在不同季节,土壤全N含量变化并不大;④微生物量N在采样期内的波动很大,就每个样地来说也具有一定的规律。得出的结论认为：不同的森林群落类型中的N循环同该群落内的土壤和植被类型有密切的联系,土壤微生物量N同环境因素（土壤温度和湿度）的关系存在时空变化。     

黄土高原不同植被覆被类型NDVI对气候变化的响应

植被与气候是目前研究生态与环境的重要内容。为探究黄土高原地区植被与气候因子之间的响应机制,利用线性趋势分析、Pearson相关分析、多元线性回归模型以及通径分析的方法,对黄土高原2000—2015年全区和不同植被覆被类型区内NDVI与气候因子的变化趋势以及相互作用关系进行分析。植被覆被分类数据和植被指数数据分别来源于ESA CCI-LC(The European Space Agency Climate Change Initiative Land Cover)以及MODND1T/NDVI(Normalized Difference Vegetation Index)。结果表明:(1) 2000—2015年黄土高原全区植被年NDVI_(max)显著增加的区域占总面积的74.25%,不同植被覆被类型年NDVI_(max)分别为常绿阔叶林常绿针叶林落叶阔叶林落叶针叶林镶嵌草地农田镶嵌林地草地灌木,并且都呈显著增加趋势,其中常绿阔叶林和农田增加幅度最大,为0.012/a。(2)黄土高原全区NDVI与气温、日照、降水和相对湿度等气候因子之间没有显著相关性,但在不同植被覆被类型区,气候因子对NDVI存在显著作用,且不同植被覆被类型差异明显。(3)在全区和不同植被覆被类型区NDVI仅对降水的响应比较一致,气温无论在整个区域尺度还是不同植被覆被类型区对植被的影响均不显著。(4)常绿阔叶林、落叶阔叶林、常绿针叶林及镶嵌林地等以乔木为主的植被覆被类型受年均相对湿度和年总日照时数的显著负效应驱动,草地、镶嵌草地等以草本为主的植被覆被类型则受到年总降水量的显著正效应影响。这说明对植被类型进行区分,更有利于揭示气候对植被的作用机制。     

大陆东南亚(中南半岛)的主要森林植被类型介绍

大陆东南亚(中南半岛)的植被研究情况鲜为人知,至今仍无系统研究资料。该文依据数次对该地区的野外考察和资料收集,介绍了东南亚植被的研究情况和文献资料以及对该地区主要森林植被的分类和各主要植被类型的特征。大陆东南亚地区在植被分类上包括七个主要的陆生及湿地的森林植被类型:针叶林、针阔混交林、热带山地常绿阔叶林、热带雨林、热带季节性湿润林、热带季风林(季雨林)、干旱刺灌丛/萨王纳植被。其中,针叶林植被型包括温性针叶林和热性针叶林二个植被亚型;针阔混交林包括温性针阔混交林和暖温性针阔混交林二个亚型;热带雨林植被型包括热带低地常绿雨林、热带季节性雨林(热带低地半常绿雨林)、热带山地雨林及泥炭沼泽森林四个植被亚型。该文还对大陆东南亚地区植被研究历史、植被分类系统、类型特征及植物区系组成进行了讨论。     

长株潭城市群生态绿心地区主要植被类型的群落特征

长株潭城市群生态绿心地区地处南方红壤丘陵区的中心地带, 植被区划上属中亚热带常绿阔叶林北部植被亚地带。该区植被以次生林为主, 植被类型复杂多样, 在南方红壤丘陵区现状植被中具有典型代表性, 可为区域植被演替动态和植被恢复研究提供良好的平台。该研究采用统一、规范的方法设置了50个样方, 对区内主要植被类型的物种组成、数量特征、生境信息等进行调查。计算乔木层、灌木层和草本层物种重要值, 运用《中国植被志》编研规范进行植被类型划分和命名, 描述群落物种组成和特征, 并提供10个植被型、22个群系、33个群丛共50个样方的原始数据, 包括森林样方43个, 灌丛样方5个, 草地样方1个, 沼泽样方1个。     

Effects of natural and artificial disturbance on landscape and forest structure in Tiantong National Forest Park,East China

This paper aims to understand the ecological effects of disturbance on broadleaved evergreen forest in East China. We used a manipulative field experiment approximating the common natural and artificial disturbance types in this area to investigate the community physiognomy, floristic composition, and 5-year recovery dynamics of the post-disturbance forest community. The results indicated that the landscape and forest structure have degraded into shrub communities, structure-damaged evergreen broadleaved communities, and so on. The post-disturbance communities presented different means of plant recruitment and vegetation recovery patterns at an early successional stage. The recovery of disturbed forests primarily depended on external seed sources and re-sprouting from stumps, rather than on soil seed banks, as few buried seeds were found. Re-sprouting thus appears to be key in allowing rapid vegetation recovery in evergreen broadleaved forest. Disturbances seem to be one of the most important factors that can contribute to regional species coexistence across temporal and spatial scales in evergreen broadleaved forests.     

Community characteristics of main vegetation types in the ecological “green-core” area of Changzhutan urban cluster

长株潭城市群生态绿心地区地处南方红壤丘陵区的中心地带, 植被区划上属中亚热带常绿阔叶林北部植被亚地带。该区植被以次生林为主, 植被类型复杂多样, 在南方红壤丘陵区现状植被中具有典型代表性, 可为区域植被演替动态和植被恢复研究提供良好的平台。该研究采用统一、规范的方法设置了50个样方, 对区内主要植被类型的物种组成、数量特征、生境信息等进行调查。计算乔木层、灌木层和草本层物种重要值, 运用《中国植被志》编研规范进行植被类型划分和命名, 描述群落物种组成和特征, 并提供10个植被型、22个群系、33个群丛共50个样方的原始数据, 包括森林样方43个, 灌丛样方5个, 草地样方1个, 沼泽样方1个。     

Succession of secondary forests affected by pine wilt disease in western Japan followed on vegetation maps

Abstract. Succession, changes in the distribution pattern of forest vegetation, and Pinus forest survival following pine wilt disease were clarified based on phytosociological analysis and vegetation maps. Survival of Pinus forests was restricted to the early successional stages, which were located on ridges and the upper part of slopes. Subsequent to pine wilt disease, the succession progressed from early to late substages of Pinus forest, mixed deciduous and evergreen Quercus, to evergreen Quercus forest. Succession occurs in abandoned pine forests which apparently are in a bad state and are vulnerable to attacks by pine wilt disease.     

鼎湖山南亚热带季风常绿阔叶林C贮量分布

在对1hm 2永久样地调查的基础上结合优势树种C含量的实测值, 对鼎湖山南亚热带季风常绿阔叶林的C贮量及其空间和种群分布特点进行了分析,结果表明 (1)鼎湖山季风常绿阔叶林现存C贮量为89.75t@hm -2 ,其中, 干、枝、叶、根分别占总量的53.09%、25.36%、2.64%和18.31%; (2)数量上小径级个体占有绝对优势,1hm 2样地内 DBH ＜20cm的个体占总数的95%,个体数量随径级的增加而迅速减少,而C贮量的径级分布则大致呈"M"形; (3)根据树木高度分为4个层次,即Ⅰ层( h ≥20m),Ⅱ层(10＜ h ≤20m),Ⅲ层(5< h ≤10m)和Ⅳ层( h ＜5m), 各亚层之间C贮量与该层次的高度呈正相关,占总C贮量的比例依次为53.97%、31.37%、 11.26%和3.40%.在垂直方向上,干、枝、根C贮量变化与总C贮量的变化趋势大体一致 ,叶的C贮量则以Ⅱ层最大; (4)优势种群对季风常绿阔叶林C贮量贡献排序为 锥栗 C astanopsis chinensis＞荷木Schima superba＞黄果厚壳桂Cryptocarya concinna＞厚壳桂 Cryptocarya chinensis＞肖蒲桃Acmena acuminatissima＞黄杞Engelhardtia roxburghi ana＞白颜树Gironniera subaequalis＞臀形果Pygeum topengii＞橄榄Canarium album＞窄叶半枫荷Pterospermum lanceaefolium＞华润楠Machilus chinensis＞鸭脚木Scheffler a octophylla＞韶子Nephelium chryseum.成熟度较高的种群 C贮量较高,起主导作用.     

NDVI‐based vegetation monitoring in Mau forest complex,Kenya

The normalized difference vegetation index (NDVI) measures vegetation health and density using plant reflectance characteristics recorded by satellite imagery. Dekadal NDVI data were obtained for January 1999–December 2009 from 1‐km resolution SPOT‐VEGETATION sensor for closed woody vegetation type in four blocks of the Mau forest complex. Vegetation response to yearly seasonal variations was plotted and used to compare deviations by specific years. Subnormal vegetation conditions were recorded by the standardized vegetation index (SVI) and persistently low SVI values indicated a drought season or degraded vegetation. The general linear trend of the vegetation was plotted for the study period to identify trends towards degradation or vegetation recovery. Analysis of variance was used to compare forest blocks and shows spatial vegetation variations and also among years to identify vegetation variations with time. Rainfall data recorded for 2002–2009 in east Mau were used to confirm rainfall‐related vegetation variations block. Results show that NDVI patterns within an year follow cyclic trends with a strong dependence on rainfall seasons. The forest vegetation indicated negligible changes over the study period but effects of extended dry periods in 2000 and 2009 were evident. There were significant differences (P < 0.05) in NDVI between forest blocks. East Mau had significantly inferior vegetation that can be attributed to forest type, level of human degradation prior to the study and the lower rainfall. There were significant variations (P < 0.05) of NDVI among years but the forests showed a natural resilience to disturbance and can retain original vegetation vigour once stress is removed. The study proposes further monitoring of the forests including other vegetation types that are more vulnerable to climatic variations and anthropogenic effects.     

Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO₂ based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.     

Effects of eucalyptus afforestation on leaf litter dynamics and macroinvertebrate community structure of streams in Central Portugal

To test the hypothesis whether afforestation with Eucalyptus globulus affects litter dynamics in streams and the structure of macroinvertebrate aquatic communities, we compared streams flowing through eucalyptus and deciduous forests, paying attention to: (i) litterfall dynamics, (ii) accumulation of organic matter, (iii) processing rates of two dominant leaf species: eucalyptus and chestnut, and (iv) macroinvertebrate community structure. The amount of allochthonous inputs was similar in both vegetation types, but the seasonality of litter inputs differed between eucalyptus and natural deciduous forests. Eucalyptus forest streams accumulated more organic matter than deciduous forest streams. Decomposition of both eucalyptus and chestnut leaf litter was higher in streams flowing through deciduous forests. The eucalyptus forest soils were highly hydrophobic resulting in strong seasonal fluctuations in discharge. In autumn the communities of benthic macroinvertebrates of the two stream types were significantly different. Deciduous forest streams contained higher numbers of invertebrates and more taxa than eucalyptus forest streams. Mixed forest streams (streams flowing through eucalyptus forests but bordered by deciduous vegetation) were intermediate between the two other vegetation types in all studied characteristics (accumulation of benthic organic matter, density and diversity of aquatic invertebrates). These results suggest that monocultures of eucalyptus affect low order stream communities. However, the impact may be attenuated if riparian corridors of original vegetation are kept in plantation forestry.     

浙江省森林信息提取及其变化的空间分布

如何利用遥感技术提取森林信息是遥感应用的重要领域之一。以不同时相的Landsat TM/ETM+为数据源,采用面向对象和基于多级决策树的分类方法得到浙江省2000年、2005年以及2010年的森林植被覆被图。经实地采样点验证,2010年分类精度达到92.76%,精度满足要求。介绍了浙江森林信息的快速提取方法,即统计不同森林类型的Landsat TM影像原始波段和LBV变换值以及各种植被指数在各时相上的差异,经过C5决策树训练,选取合适的规则和阈值实现森林信息的提取。结果表明,面向对象分割与决策树算法结合可以作为森林信息提取的有效方法。最后,通过对3期森林专题图进行空间叠加分析,得到了森林资源动态变化的空间分布,并以此为基础对林地变化的类型及原因进行分析,结果显示浙江省森林资源变化主要分布在浙西北山区、浙中南山区以及沿海地带,这一结果可以为有关部门的决策提供依据。     

Soil Organic Matter Dynamics Along a Vertical Vegetation Gradient in the Gongga Mountain on the Tibetan Plateau

Our knowledge about soil organic matter (SOM) dynamics is limited although this is an important issue in the study of responses of ecosystems to global climate changes. Twelve sampling plots were set up every 200 m from 1 700 to 3 900 m along the vertical vegetation gradient along the east slope of Gongga Mountain. Samples were taken from all 12 plots for SOM content measurement, although only 5 of the 12 plots were subjected to radiocarbon measurements. A radiocarbon isotope method and a time-dependent model were used to quantify the SOM dynamics and SOM turnover rates along the vertical vegetation gradient. The results showed that the SOM turnover rate decreased and turnover time increased with soil depth for all vegetation types. The litter layer turnover rates presented a clear trend along the gradient. The litter layer turnover rates decreased with an increase in elevation, except that the litter layer turnover rate of mixed forest was higher than that of evergreen forest. Climatic factors, such as temperature and precipitation, were the main factors influencing the surface soil carbon dynamics. The turnover rates of the subsoil (including the A, B, and C horizons in the soil profiles) along the vertical gradient had no clear trends. The SOM of subalpine shrub and meadow turned over more slowly than that of the forest types in almost all soil horizons. The characteristic of short roots distributing in the upper part of the soil profile leads to different SOM dynamics of shrub and meadow compared with the forest types. Coniferous and mixed forests were susceptible to carbon loss from the young carbon pool, but their long and big roots resulted in high △^14C values of the deep soil profiles and increased the input of young carbon to the deep soil. In evergreen forest, the carbon cumulative ability from the B horizon to the C horizon was weak. The different vegetation types, together with their different modes of nutrient and carbon intake, may be the mechanism conditioning the subsoil organic matter dynamics.     

越南红河流域区不同沉积环境的植被分布

根据中日越三方合作对越南红河流域周边/沿岸植被、生境、土壤和地貌特征等进行的野外踏勘和调查结果,结合前人研究成果,以红河汇水盆地沉积物中植物碎屑及相关微体的潜在源区为出发点,从地形地貌学的角度,阐述了越南红河流域周边植被的组合分布规律。结果表明:(Ⅰ)上游番西邦山区河谷体系:植被垂直分分带明显,海拔由低到高依次分布有热带雨林、季雨林、亚热带常绿阔叶林、山地苔藓林、温带阔叶林、针阔叶混交林、高山灌丛和草地8类植被;(Ⅱ)河床河漫滩堤岸的河流体系:水生植物及沼泽植物—草地、低矮灌丛—热带树种;(Ⅲ)三角洲平原—沿海滩涂体系:沼泽森林—红树林。另外,原始植被经自然火灾或人类种植火烧后形成独特的次生植被类型主要为竹林、松林、草地等。