三峡库区不同植被类型土壤养分特征

通过三峡库区8个植被类型370个样地的群落调查和土壤分析,研究了不同植被类型、土壤类型、海拔对表层土壤有机质及全氮、速效磷、速效钾含量的影响.结果表明:(1)三峡库区不同植被类型土壤有机质、全氮平均含量规律为阔叶林＞竹林＞针叶林＞灌丛＞草丛,森林土壤有机质及全氮平均含量丰富;速效磷平均含量表现为草丛＞落叶阔叶林＞灌丛＞暖性针叶林＞常绿落叶阔叶混交林＞温性针叶林＞竹林＞常绿阔叶林,草丛与其他植被类型差异显著;速效钾平均含量表现为常绿落叶阔叶混交林＞落叶阔叶林＞灌丛＞针叶林＞竹林＞草丛＞常绿阔叶林,竹林、草丛、常绿阔叶林与常绿落叶阔叶混交林、落叶阔叶林、灌丛、针叶林差异显著.(2)不同土壤类型养分含量差异显著,黄棕壤中有机质、全氮含量高,分别为6.83%、0.44%,紫色土中速效磷含量高,达到54.24mg/kg.(3)随海拔升高,有机质、全氮含量呈明显增加趋势,速效磷、速效钾含量变化趋势不明显.     

浙江天童常绿阔叶林、常绿针叶林与落叶阔叶林的C:N:P化学计量特征

以浙江天童常绿阔叶林、常绿针叶林和落叶阔叶林为对象, 通过对叶片和凋落物C:N:P比率与N、P重吸收的研究, 揭示3种植被类型N、P养分限制和N、P重吸收的内在联系。结果显示: 1)叶片C:N:P在常绿阔叶林为758:18:1, 在常绿针叶林为678:14:1, 在落叶阔叶林为338:11:1; 凋落物C:N:P在常绿阔叶林为777:13:1, 常绿针叶林为691:14:1, 落叶阔叶林为567:14:1; 2)常绿阔叶林和常绿针叶林叶片与凋落物C:N均显著高于落叶阔叶林; 叶片C:P在常绿阔叶林最高, 常绿针叶林中等, 落叶阔叶林最低, 常绿阔叶林和常绿针叶林凋落物C:P显著高于落叶阔叶林; 叶片N:P比也是常绿阔叶林最高、常绿针叶林次之, 落叶阔叶林最低, 但常绿阔叶林凋落物N:P最低; 3)植被叶片N、P含量间(N为x, P为y)的II类线性回归斜率显著大于1 (p < 0.05), 表明叶片P含量的增加可显著提高叶片N含量; 凋落物N、P含量的回归斜率约等于1, 反映了凋落物中单位P含量与单位N含量间的等速损耗关系; 4)常绿阔叶林N重吸收率显著高于常绿针叶林与落叶阔叶林, 落叶阔叶林P重吸收率显著高于常绿阔叶林和常绿针叶林。虽然植被的N:P指示常绿阔叶林受P限制, 落叶阔叶林受N限制, 常绿针叶林受N、P的共同限制, 但是N、P重吸收研究结果表明: 受N素限制的常绿阔叶林具有高的N重吸收率, 受P限制的落叶阔叶林并不具有高的P重吸收率。可见, 较高的N、P养分转移率可能不是植物对N、P养分胁迫的一种重要适应机制, 是物种固有的特征。     

贡嘎山东坡典型植被类型土壤动物群落特征

为了掌握贡嘎山垂直植被带间土壤动物群落结构及多样性,2012年5月至10月间对贡嘎山东坡的常绿阔叶林、落叶阔叶林、针阔混交林和暗针叶林4种典型植被土壤动物群落进行了调查。共捕获土壤动物347只,隶属于10纲29目68类,其中山蛩属(Spirobolus)为优势类群。土壤动物的群落密度、生物量以及多样性呈常绿阔叶林落叶阔叶林针阔混交林暗针叶林趋势,其中密度、类群丰富度和Shannon-Wiener指数的变化具有显著差异(P0.05);落叶阔叶林和针阔混交林间的土壤动物群落结构差异明显,其他植被类型间的差异性受季节影响。从各功能群结构来看,腐食性和杂食性土壤动物占主要地位;各功能群的生物量均以常绿阔叶林和落叶阔叶林较高,针阔混交林和暗针叶林较低,而相对生物量的变化趋势各不相同,仅有腐食性功能群的生物量及植食性功能群的相对生物量在各垂直植被带间有显著差异(P0.05)。群落密度、生物量、类群丰富度、Shannon-Wiener指数以及腐食性和捕食性功能群的生物量与土壤温度呈显著相关(P0.05)。研究结果表明:贡嘎山东坡土壤动物的群落组成、多样性及功能群结构在各典型植被类型间有明显差异,土壤温度是影响土壤动物垂直分布格局的主要环境因子。     

河南植被水平地带性的分布规律

河南植被纬向性分布与气温有关。北部属温带落叶林区域,典型植被,山地为落叶阔叶林和常绿针叶林,东部平原的农作物为一年两作或两年三作。南部为亚热带常绿阔叶林区域的常绿、落叶阔叶混交林地带,典型植被为含有常绿成分的落叶阔叶林,针叶林由马尾松、黄山松和杉木林组成。河南植被的经向性分布职决于干燥度引起的地带性变化,东部大别山的植被由黄山松林和茶园来表征,南部的桐柏山地带则没有黄山松林和茶园。     

中国成熟天然林土壤有机碳垂直分异特征

以分布在中国不同气候区的131个成熟天然林土壤为研究对象,测定不同土层(0～10、10～20、20～30、30～50和50～100 cm)土壤有机碳(SOC)密度,分析其与气象因子、土壤性质的关系,研究天然林SOC垂直分布特征及其影响机理。结果表明: 温带针叶林、温带落叶阔叶林、亚热带落叶阔叶林和亚热带常绿阔叶林0～30 cm土层SOC密度均随土壤深度增加而降低。在0～100 cm土层,SOC密度地带性分异明显,温带针叶林SOC密度显著高于温带落叶阔叶林,亚热带常绿阔叶林SOC密度显著高于亚热带落叶阔叶林。SOC密度与土壤黏粒、年降水量以及地上净初级生产力呈显著正相关,与土壤pH和年均温呈显著负相关。年降水量与年均温调节天然林SOC输入与输出,土壤pH与黏粒影响天然林SOC积累,对成熟的天然针叶林与常绿阔叶林进行有效保护,有利于增加我国森林土壤碳库。     

台湾植被分类方案

复杂的自然条件导致面积仅为36 000多平方公里的台湾兼有热带和寒温带的群落类型,堪称中国乃至世界植被之缩影.它的植被分类也是对中国乃至世界植被分类的补充.台湾植被分类采用的是外貌-区系原则,分类单位和系统自上而下是:植被型纲、植被型目、植被型、群团组、群团和群丛.高级单位(植被型纲、植被型目和植被型)以群落的生态外貌为依据;中、低级单位主要依据种类组成,兼顾优势种和标志种的指示意义.在中级单位中(群团组、群团),重视优势种的作用,在低级单位中(群丛)更重视特征种(或标志种)的意义.按此原则将台湾植被划分为5个植被型纲(森林、灌丛、草本植被、岩原植被、沼泽和水生植被),29个植被型目(寒温性针叶林,凉温性针叶林,暖温性针叶林,暖性针叶林、落叶阔叶林、常绿阔叶落叶阔叶混交林、常绿苔藓林、常绿硬叶林、常绿阔叶林、热带雨林、热带季雨林海岸林、暖性竹林、常绿针叶灌丛、革叶灌丛、落叶阔叶灌丛、常绿阔叶灌丛、刺肉灌丛、竹灌丛、草甸、疏灌草地、干热早生草地、岩屑堆稀疏群落、石隙植被、木本沼泽、草本沼泽、藓类沼泽、淡水水生植被和咸水水生植被),53个植被型.列举了各个植被型中的重要群团.     

台湾植被分类方案

复杂的自然条件导致面积仅为36000多平办公里的台湾兼有热带和寒温带的群落类型,堪称中国乃至世界植被之缩影。它的植被分类也是对中国乃至世界植被分类的补充。台湾植被分类采用的是外貌-区系原则,分类单位和系统自上而下是：植被型纲、植被型目、植被型、群团组、群团和群丛。高级单位(植被型纲、植被型目和植被型)以群落的生态外貌为依据;中、低级单位主要依据种类组成,兼顾优势种和标志种的指示意义。在中级单位中(群团组、群团),重视优势种的作用,在低级单位中(群丛)更重视特征种(或标志种)的意义。按此原则将台湾植被划分为5个植被型纲(森林、灌丛、草本植被、岩原植被、沼泽和水生植被),29个植被型目(寒温性针叶林,凉温性针叶林,暖温性针叶林,暖性针叶林、落叶阔叶林、常绿阔叶落叶阔叶混交林、常绿苔藓林、常绿硬叶林、常绿阔叶林、热带雨林、热带季雨林海岸林、暖性竹林、常绿针叶灌丛、革叶灌从、落叶阔叶灌丛、常绿阔叶灌丛、刺肉灌从、竹灌丛、草甸、疏灌草地、干热旱生草地、岩屑堆稀疏群落、石隙植被、木本沼泽、草本沼洋、藓类沼泽、淡水水生植被和成水水生植被),53个植被型。列举了各个植被型中的重要群团。     

鼎湖山森林凋落物量及营养元素含量研究

 本文研究了鼎湖山南亚热带常绿阔叶林和针叶林的凋落物量及凋落物中主要营养元素(N、P、K、Ca、Mg)的含量。8年的测定结果表明,两个森林类型的年均凋落物量(t·ha-1)及凋落物中主要营养元素的含量(t·ha-1·yr-1)分别为：常绿阔叶林9.056,0.220;针叶林2.695,0.032。凋落物中叶、枝和花果的百分组成及凋落特征各异。鼎湖山南亚热带常绿阔叶林的年均凋落物量低于热带雨林而高于暖温带落叶阔叶林,说明不同气候带的森林类型,其凋落物量是有差异的。与针叶林相比较,常绿阔叶林的凋落物量较大,凋落物中主要营养元素的含量较高,凋落物的分解速率也较快,因此从提高森林的质量和增强森林的生态效益来考虑,在造林绿化上应提倡多营造常绿阔叶林或针阔叶混交林。     

广西金钟山自然保护区主要植被类型的特征

金钟山自然保护区计有种子植物101科273属514种,落叶栎林分布面积最广。随海拔升高,植被依次呈现出4个分布带:沟谷落叶阔叶林、沟谷常绿阔叶林、常绿落叶阔叶混交林和落叶阔叶林、山地苔藓矮林和山地常绿阔叶林。该区主要有4个分布区类型:世界分布、热带分布、温带分布和中国特有分布,其中热带分布占总属数的75.21%,表明本保护区的植物分布具有热带性质。其天然植被类型可划分为5个植被型组,7个植被型含暖性针叶林、暖性落叶阔叶林、常绿落叶阔叶混交林、常绿阔叶林、竹林和草丛,2个植被亚型含南亚热带山地常绿阔叶林、山顶阔叶矮林,以及33个群系。     

西南地区不同植被类型归一化植被指数与气候因子的相关分析

基于中国西南地区1982—2006年的归一化植被指数(NDVI)遥感数据集和气象数据,运用GIS技术对年均气温、年降水量和干旱指数进行插值,分析了西南地区不同植被类型(沼泽、灌丛、草丛、草原、草甸、针叶林、阔叶林、高山植被、栽培植被)NDVI的年际变化及其与气候因子的相关性.结果表明:研究期间,西南地区NDVI、年均气温、年降水量总体呈上升趋势,其中,年均气温的上升趋势达极显著水平,干旱指数则呈下降趋势;在9种植被类型中,沼泽和草丛NDVI呈下降趋势,且草丛的下降趋势达显著水平,其他7种植被类型的NDVI均呈上升趋势,且针叶林、草甸和高山植被的NDVI上升趋势达显著水平,灌丛NDVI呈极显著上升趋势.9种植被类型所在地区的年均气温均显著上升;年降水量的变化均不显著;沼泽、草丛和栽培植被所在地区的干旱指数呈上升趋势,草甸和高山植被所在地区的干旱指数显著下降,其他4种植被类型所在地区的干旱指数呈不明显的下降趋势.研究区灌丛和针叶林NDVI与年均气温呈显著正相关,灌丛和草甸NDVI与干旱指数呈显著负相关.在保持其他2个气候因子不变的情况下,针叶林、阔叶林、高山植被NDVI与年均气温的相关性最大,草丛NDVI与年降水...     

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.     

A global assessment of forest surface albedo and its relationships with climate and atmospheric nitrogen deposition

We present a global assessment of the relationships between the short‐wave surface albedo of forests, derived from the MODIS satellite instrument product at 0.5° spatial resolution, with simulated atmospheric nitrogen deposition rates (N_dep), and climatic variables (mean annual temperature T_m and total annual precipitation P), compiled at the same spatial resolution. The analysis was performed on the following five forest plant functional types (PFTs): evergreen needle‐leaf forests (ENF); evergreen broad‐leaf forests (EBF); deciduous needle‐leaf forests (DNF); deciduous broad‐leaf forests (DBF); and mixed‐forests (MF). Generalized additive models (GAMs) were applied in the exploratory analysis to assess the functional nature of short‐wave surface albedo relations to environmental variables. The analysis showed evident correlations of albedo with environmental predictors when data were pooled across PFTs: T_m and N_dep displayed a positive relationship with forest albedo, while a negative relationship was detected with P. These correlations are primarily due to surface albedo differences between conifer and broad‐leaf species, and different species geographical distributions. However, the analysis performed within individual PFTs, strengthened by attempts to select ‘pure’ pixels in terms of species composition, showed significant correlations with annual precipitation and nitrogen deposition, pointing toward the potential effect of environmental variables on forest surface albedo at the ecosystem level. Overall, our global assessment emphasizes the importance of elucidating the ecological mechanisms that link environmental conditions and forest canopy properties for an improved parameterization of surface albedo in climate models.     

Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices

Wildfires have major effects on forest dynamics, succession and the carbon cycle in the boreal biome. They are a significant source of carbon emissions, and current observed changes in wildfire regimes due to changes in climate could affect the balance of the boreal carbon pool. A better understanding of postwildfire vegetation dynamics in boreal forests will help predict the future role of boreal forests as a carbon sink or source. Time series of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Shortwave Infrared Index (NDSWIR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite were used to investigate whether characteristic temporal patterns exist for stands of different ages in the Siberian boreal forests and whether their postwildfire dynamics are influenced by variables such as prewildfire vegetation cover. Two types of forests, evergreen needle‐leaf (ENF) and deciduous needle‐leaf (DNF), were studied by analysing a sample of 78 burned forest areas. In order to study a longer time frame, a chronosequence of burned areas of different ages was built by coupling information on location and age provided by a forest burned area database (from 1992 to 2003) to MODIS NDVI and NDSWIR time series acquired from 2001 to 2005. For each of the burned areas, an adjacent unburned control plot representing the same forest type was selected, with the aim of separating the interannual variations caused by climate from changes in NDVI and NDSWIR behaviour due to a wildfire. The results suggest that it takes more than 13 years for the temporal NDVI and NDSWIR signal to recover fully after wildfire. NDSWIR, which is associated to canopy moisture, needs a longer recovery period than NDVI, which is associated to vegetation greenness. The results also suggest that variability observed in postwildfire NDVI and NDSWIR can be explained partially by the dominant forest type: while 13 years after a fire NDVI and NDSWIR are similar for ENF and DNF, the initial impact appears to be greater on the NDVI and NDSWIR of ENF, suggesting a faster recovery by ENF.     

中国4种典型森林中常见乔木叶片的非结构性碳水化合物研究

植物叶片的非结构性碳水化合物(non-structural carbohydrates,NSC)不仅为植物的代谢过程提供重要能量,还能一定程度上反映植物对外界环境的适应策略。以温带针阔混交林(长白山)、温带阔叶林(东灵山)、亚热带常绿阔叶林(神农架)和热带雨林(尖峰岭)4种森林类型的树种为研究对象,利用蒽酮比色法测定了163种常见乔木叶片可溶性糖、淀粉和NSC(可溶性糖+淀粉)含量,探讨了不同森林类型植物叶片NSC的差异及其地带性变化规律。结果显示：（1）从森林类型上看,植物叶片NSC含量从北到南递减,即温带针阔混交林(170.79 mg/g)>温带阔叶林(100.27 mg/g)>亚热带常绿阔叶林(91.24 mg/g)>热带雨林(80.13 mg/g)。（2）从生活型上看,无论是落叶树还是阔叶树,其叶片可溶性糖、淀粉和NSC含量均表现为：温带针阔混交林>温带阔叶林>亚热带常绿阔叶林>热带雨林;北方森林叶片可溶性糖、淀粉和NSC含量均表现为落叶树种>常绿树种,或阔叶树种>针叶树种。（3）森林植物叶片NSC含量、可溶性糖与淀粉含量比值与年均温和年均降水量均呈显著负相关。研究表明,森林植物叶片可溶性糖、淀粉和NSC含量以及可溶性糖与淀粉含量比值均具有明显的从北到南递减的地带性规律;其NSC含量以及可溶性糖与淀粉含量比值与温度和水分均呈显著负相关的变化规律可能是植物对外界环境适应的重要机制之一。该研究结果不仅为阐明中国主要森林树种碳代谢和生长适应对策提供了数据基础,而且为理解区域尺度森林植被对未来气候变化的响应机理提供新的视角。     

我国陆地植被净初级生产力变化规律及其对气候的响应

在GIS系统的支持下,利用卫星遥感资料和地面气象观测资料,构建了基于光能利用率的植被净初级生产力(NPP)遥感模型,估算了我国陆地1982—2000年1—12月植被NPP,分析了1982—2000年我国不同植被类型NPP的季节性和年际性变化规律,基于像元空间尺度讨论了植被NPP对气候的响应关系.结果表明,我国植被NPP年内季节性变化规律明显;我国主要植被类型年NPP在1982—2000年基本呈上升趋势,增长幅度最大的是落叶针叶林,增长幅度最小的是草地;1982—2000年,NPP年际间波动最大的植被类型是常绿阔叶林,年际间波动最小的植被类型是草地.通过NPP对气候因子(降水、温度)变化的响应分析表明,我国降水对植被NPP季节性变化的驱动作用高于温度,气候因子(降水、温度)对北方植被NPP季节性变化的驱动作用高于南方;我国气候因子(降水、温度)对NPP年际变化的驱动作用(强度、方向)随季节 及纬度的不同而不同.     

Geographical and climatic gradients of evergreen versus deciduous broad‐leaved tree species in subtropical China: Implications for the definition of the mixed forest

Understanding climatic influences on the proportion of evergreen versus deciduous broad‐leaved tree species in forests is of crucial importance when predicting the impact of climate change on broad‐leaved forests. Here, we quantified the geographical distribution of evergreen versus deciduous broad‐leaved tree species in subtropical China. The Relative Importance Value index (RIV ) was used to examine regional patterns in tree species dominance and was related to three key climatic variables: mean annual temperature (MAT ), minimum temperature of the coldest month (MinT), and mean annual precipitation (MAP ). We found the RIV of evergreen species to decrease with latitude at a lapse rate of 10% per degree between 23.5 and 25°N, 1% per degree at 25–29.1°N, and 15% per degree at 29.1–34°N. The RIV of evergreen species increased with: MinT at a lapse rate of 10% per °C between ?4.5 and 2.5°C and 2% per °C at 2.5–10.5°C; MAP at a lapse rate of 10% per 100 mm between 900 and 1,600 mm and 4% per 100 mm between 1,600 and 2,250 mm. All selected climatic variables cumulatively explained 71% of the geographical variation in dominance of evergreen and deciduous broad‐leaved tree species and the climatic variables, ranked in order of decreasing effects were as follows: MinT > MAP  > MAT . We further proposed that the latitudinal limit of evergreen and deciduous broad‐leaved mixed forests was 29.1–32°N, corresponding with MAT of 11–18.1°C, MinT of ?2.5 to 2.51°C, and MAP of 1,000–1,630 mm. This study is the first quantitative assessment of climatic correlates with the evergreenness and deciduousness of broad‐leaved forests in subtropical China and underscores that extreme cold temperature is the most important climatic determinant of evergreen and deciduous broad‐leaved tree species’ distributions, a finding that confirms earlier qualitative studies. Our findings also offer new insight into the definition and distribution of the mixed forest and an accurate assessment of vulnerability of mixed forests to future climate change.     

Climate-induced changes in the vegetation pattern of China in the 21st century

Quantifying climate-induced changes in vegetation patterns is essential to understanding land–climate interactions and ecosystem changes. In the present study, we estimated various distributional changes of vegetation under different climate-change scenarios in the 21st century. Both hypothetical scenarios and Hedley RCM scenarios show that the transitional vegetation types, such as shrubland and grassland, have higher sensitivity to climatic change compared to vegetation under extreme climatic conditions, such as the evergreen broadleaf forest or desert, barren lands. Mainly, the sensitive areas in China lie in the Tibetan Plateau, Yunnan-Guizhou Plateau, northeastern plain of China and eco-zones between different vegetations. As the temperature increases, mixed forests and deciduous broadleaf forests will shift towards northern China. Grassland, shrubland and wooded grassland will extend to southeastern China. The RCM-project climate changes generally have caused positive vegetation changes; vegetation cover will probably improve 19% relative to baseline, and the forest will expand to 8% relative to baseline, while the desert and bare ground will reduce by about 13%.     

Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade‐offs that determine trait diversity. In this study, we show how physiological trade‐offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual‐based dynamic vegetation model (i.e., LM3‐PPA). The evolutionary analysis shows that these leaf traits set up a trade‐off between carbon‐ and nitrogen‐use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen‐use efficiency to one that is high in carbon‐use efficiency or, equivalently, from high‐LMA/long‐lived leaves (i.e., evergreen) to low‐LMA/short‐lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3‐PPA from the leaf physiological trade‐offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones.     

西南地区灌丛归一化植被指数动态及其与气候因子的相关性

基于西南地区1982-2006年的归一化植被指数(NDVI)和气象数据,使用ANUS-PLIN、ArcGIS和SPSS软件分析了该区6种灌丛类型NDVI的季节和年际变化,及其与气候因子的相关性.结果表明:25年来,3种高海拔亚高山灌丛(亚高山常绿针叶灌丛、亚高山落叶阔叶灌丛、亚高山革质常绿阔叶灌丛)年均NDVI显著增大,其他3种中低海拔灌丛(温带落叶灌丛、亚热带热带旱生肉质多刺灌丛和亚热带热带常绿落叶阔叶灌丛)增加不显著;除亚热带热带旱生肉质灌丛外,其他5种灌丛年均温均呈显著增加趋势;亚高山常绿针叶灌丛年降水量呈增加趋势,但不显著;其他5种灌丛年降水量呈减少趋势,其中温带落叶灌丛减少显著.3种亚高山灌丛月NDVI与温度和降水均达到极显著正相关,且与前一个月的温度、降水相关性最大,存在明显的滞后效应;位于中低海拔的其他3种灌丛NDVI与温度和降水的相关性明显降低.在高海拔亚高山区,气候变暖导致了年均NDVI增加,温度是3种亚高山灌丛NDVI年际变化的驱动因子;在中低海拔,温度的显著上升没有引起NDVI的显著增加.     

中国东部森林植被带划分之我见

简要回顾了中国东部森林植被带划分研究的历史及当前存在的争论。提出了中国东部植被带划分应以植被本身的特征，特别是地带性的生物群落集为主要依据，同时参照它们的区系组成和气候指标。根据上述原则将中国东部划分为６个植被带∶北方针叶林带、凉温带针阔混交林带、温带落叶阔叶林带、暖温带常绿落叶阔叶混交林带、亚热带常绿阔叶林带和热带雨林、季雨林带，并对各植被带的特征作了简要的描述。阐述了对一些植被带名称、界线改动的原因，特别讨论了我国常绿落叶阔叶混交林以及常绿阔叶林生物气候带的归属问题，认为前者归属于暖温带植被，后者归属于亚热带植被为宜。