西藏藏北高原典型植被生长对气候要素变化的响应

选取西藏藏北高原西部高寒草原植被、中部高寒草甸植被及东南部高寒灌丛草甸植被 3 种藏北地区最典型的植被类型, 结合临近 3 个气象观测站的资料, 分析这 3 种典型植被类型地区 1999—2001 年旬平均气温、旬总降水量和 SPOT VEGETATION 卫星 10 d 最大值合成归一化植被指数 (NDVI) 变化特征以及 3 种典型植被基于 SPOT VEGETATION NDVI 的生长变化对旬平均气温和旬总降水量两个主要气候要素变化的响应关系。 结果表明: 藏北地区降水资源的空间分布特点是东南部向西北部逐渐减少, 气温则由南向北逐渐递减, 与降水资源分布相反, 蒸发量西部高, 东部低; SPOT VEGETATION NDVI 能够较为准确地反映 3 种典型植被生长变化特征, 所反映的植被返青期和枯黄期等重要植被生长阶段与由积温计算的植被生长特征基本一致; 藏北地区基于 SPOT VEGETATION NDVI 的植被生长变化与气温的相关系数明显高于与降水的相关系数 , 其中以那曲为代表的高寒草甸植被的 NDVI 与旬气温和旬降水总量的相关系数最大, 分别为 0.81 和 0.68 , 表明藏北地区由于海拔高, 气候寒冷, 气温对该地区植被生长的影响明显高于降水的影响, 即该地区植被生长变化对气温的响应程度明显高于对降水的响应程度 , 是植被生长的限制性因素; 不同植被类型对气温和降水两个要素的响应程度大小依次是高寒草甸、高寒灌丛草甸和高寒草原。     

基于MODIS NDVI和气候信息的草原植被变化监测

对植被的动态监测可以从一定程度上反映气候变化趋势。该文利用2000—2005年MODIS NDVI数据对锡林郭勒盟典型草原植被变化进行动态监测,在此基础上,以降水量、水汽压、平均气温、最高气温、最低气温、日照时数作为气候指标,分析锡林郭勒盟典型草原和荒漠草原MODIS NDVI与同期及前期气候因子的相关性,探讨草原植被变化的气候驱动因子。结果表明:2000—2005年锡林郭勒盟植被改善面积大于退化面积,植被退化面积最大的区域为荒漠草原,占全盟面积的12.84%,植被改善面积最大的区域为典型草原,占全盟面积29.09%。4类草原改善趋势由强到弱的顺序为草甸草原、典型草原、沙地草原、荒漠草原。对于典型草原,其NDVI与最高气温关系最密切,其次为水汽压;对于荒漠草原,其NDVI与最高气温关系最为密切,其次为最低气温。此外,NDVI对气候因子的响应表现出明显的时滞效应。     

基于NDVI的西藏不同草地类型生物量回归建模分析

旨在建立西藏地区不同草地类型的NDVI遥感估测模型,利用多元线性回归建立了不同草地类型的鲜草生物量与SPOT/VEGETATION多年平均年最大归一化植被指数(NDVI)、年降水量和年积温等变量的回归估测模型。并分析了所有草地类型的平均鲜草生物量与平均年最大NDVI、平均年降水量等因子的相关关系。结果表明:年降水量是鲜草长势最重要的影响因子,基于NDVI的鲜草生物量多元线性回归模型能很好的拟合草地(R=0.964)、高寒草甸(R=0.959)、高寒荒漠草原(R=0.772)、温性草原(R=0.892)和高寒草原(R=0.797)等草地类型。      

伊犁地区不同草地类型植被指数与气候因子的关系

基于2006—2012年主要生长季(5—9月)MODIS旬最大值合成NDVI数据,结合同期气温、降水插值栅格资料,采用均值法、线性回归法、相关系数法分析了伊犁河谷地区七大不同草地类型NDVI的时空变化规律及其对气象因子响应的敏感性及滞后性。结果表明:(1)伊犁河谷草地植被NDVI整体呈微弱增加趋势,其中,温性荒漠类草地的增加趋势略高于其他几种类型。(2)温性草甸草原、温性草原、温性荒漠草原、高寒草原、低平地草甸的NDVI主要受降水影响,即NDVI与生长季平均降水量呈极显著正相关,且平均降水量每增加1 mm,其NDVI分别增加0.005、0.006、0.007、0.004、0.003。(3)不同草地类型与气温、降水存在不同的滞后响应,多数草地类型5月气温、降水与7月NDVI表现出显著相关性。其中,温性草甸草原、温性草原、温性荒漠草原NDVI受气温和降水共同影响,气温每升高1℃,NDVI分别减少0.020、0.028、0.027,降水每增加1 mm,NDVI分别增加0.002、0.003、0.003;高寒草原主要受降水影响,降水每增加1 mm,NDVI增加0.003;低平地草甸主要受气温影响,气温每升高1℃,NDVI减少0.016;温性荒漠、沼泽与气温、降水没有明显相关性。不同草地类型对水热因子的需求不同,是产生这种结果的主要原因。     

中国半干旱区草甸草原和典型草原碳通量日变化特征

半干旱草原碳收支对陆地生态系统碳源汇功能变化具有重要影响。本文基于通榆草甸草原站2011～2017年和毛登典型草原站2013~2017年涡动相关法观测数据,分析了生长季碳通量日变化特征,研究了碳通量日变化过程对主要环境因子的响应。结果表明:两处草原7月碳吸收活动最强,草甸草原生长季各月总初级生产力（gross primary production, GPP）、生态系统呼吸（ecosystem respiration, R_e）和净碳交换量（net ecosystem exchange, NEE）的峰值均高于典型草原。NEE的日变化以单峰型为主,但7月、8月饱和水汽压差较高时,GPP在正午前后降低,引起NEE的双峰型日变化。光合有效辐射是草甸草原NEE日变化的主导因子,而在典型草原,浅层土壤含水量（5 cm）也主导了NEE日变化。水分亏缺使草原碳交换速率显著降低,草甸草原固碳速率对水分亏缺的敏感性强于典型草原。同时,水分亏缺也改变了GPP、R_e和NEE对温度和光合有效辐射的响应关系。     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

Sensitivity of carbon budget to historical climate variability and atmospheric CO2 concentration in temperate grassland ecosystems in China

Chinese temperate grasslands play an important role in the terrestrial carbon cycle. Based on the parameterization and validation of Terrestrial Ecosystem Model (TEM, Version 5.0), we analyzed the carbon budgets of Chinese temperate grasslands and their responses to historical atmospheric CO₂ concentration and climate variability during 1951–2007. The results indicated that Chinese temperate grassland acted as a slight carbon sink with annual mean value of 7.3 T?g C, ranging from -80.5 to 79.6 T?g C yr^-1. Our sensitivity experiments further revealed that precipitation variability was the primary factor for decreasing carbon storage. CO₂ fertilization may increase the carbon storage (1.4 %) but cannot offset the proportion caused by climate variability (-15.3 %). Impacts of CO₂ concentration, temperature and precipitation variability on Chinese temperate grassland cannot be simply explained by the sum of the individual effects. Interactions among them increased total carbon storage of 56.6 T?g C which 14.2 T?g C was stored in vegetation and 42.4 T?g C was stored in soil. Besides, different grassland types had different responses to climate change and CO₂ concentration. NPP and R_H of the desert and forest steppes were more sensitive to precipitation variability than temperature variability while the typical steppe responded to temperature variability more sensitively than the desert and forest steppes.     

1982-2012年北半球荒漠草原过渡带植被物候特征及其与气候因子的关系

基于GIMMS（global inventory modeling and mapping studies）NDVI 3g数据,在提取北半球荒漠草原过渡带每年植被物候期的基础上,研究了1982-2012年物候期的时间演化趋势及空间分异特征,并结合全球气候再分析资料,探讨了物候变化的气候驱动因素。结果表明：在1998年之前,荒漠草原过渡带植被物候期变化地区间差异较大,而在1998年之后,北半球荒漠草原过渡带生长季结束期整体提前,平均提前0.41 d/a;同时,除萨赫勒以外的各地区植被生长季长度普遍缩短,平均缩短0.88 d/a。植被物候期与气候因子的相关分析发现,荒漠草原过渡带植被物候变化受气候变化影响显著,且空间差异明显。在中高纬度地区,气温是限制植被活动的关键因子,温度升高可以促进生长季开始期的提前,而降水增加则会妨碍植被生长;在较低纬度地区,水分是影响植被活动的关键因素,高温造成的水分亏缺会导致植被生长季缩短。从植被物候期对各气候因子响应的时滞性来看,荒漠草原过渡带植被的物候期对气温变化的响应最迅速,对蒸散的响应存在一定的滞后性,而对降水的响应不存在时滞差异。     

内蒙古植被NDVI变化特征分析

对植被状况和植被覆盖的研究可以反映植被受环境条件影响产生的时空变化。文章根据GIMMS-NDVI数据集1982—2006年影像数据,分析内蒙古农田、森林、草原三种植被类型NDVI年内、年际的变化趋势以及植被覆盖变化特征的空间差异。各植被类型变化曲线都呈现4—7月NDVI激增,8—10月NDVI猛降,冬季农田、草原植被覆盖接近裸土的特点。农田夏季NDVI平均值的历年线性变化趋势通过显著性检验,森林夏季NDVI平均值呈现下降的趋势,草原夏季NDVI平均值呈现上升的趋势,但都不显著。     

植被归一化植被指数对气候因子的空间敏感性

基于全球土地利用类型和覆盖度,利用生长季多年平均（1982～2015年）归一化植被指数（Normalized Difference Vegetation Index,NDVI）和气候平均态（气温、降水量）数据,讨论了全球植被格局与气候因子之间的关系,建立了两者之间的多元回归模型,并分析了植被对气温和降水气候态敏感性的特征。植被与气候因子在气候梯度上存在明显的对应关系,回归模型可较好拟合气候态NDVI的全球分布格局,拟合与观测NDVI的相关系数达0.90。其中,常绿阔叶林、混交林、常绿针叶林、落叶阔叶林、农田和木本稀树草原空间分布的拟合能力较好（r>0.8）。不同土地覆盖类型的NDVI对气温、降水气候态的空间敏感性特征不同。整体而言,植被对气温和降水的敏感性呈现反相关关系（r=-0.6）。不同土地覆盖类型对气温表现出正/负敏感性,寒带灌木对气温的敏感性最强,而农作物、草原、裸地对气温负敏感性较大;植被对降水的敏感性均表现出正敏感性,其中落叶针叶林、草原和稀树草原对降水的空间敏感性较强。     

2000—2020年呼伦贝尔地区归一化植被指数时空变化及其对气候的响应

利用2000—2020年MOD13Q1和气象观测数据, 结合Sen趋势分析、M-K显著性检验、变异系数、Hurst指数、相关系数等对呼伦贝尔地区归一化植被指数(NDVI)时空变化及气候响应进行分析。结果表明: 呼伦贝尔地区多年生长季平均NDVI为0.63, 平均年变化倾向率为0.028/10 a, 大部分地区呈增加趋势, 其中大兴安岭森林大部及岭西耕地增加显著。呼伦贝尔地区生长季NDVI的平均变异系数为0.08, 其中呼伦贝尔草原西部的波动较大。Hurst指数表明, 呼伦贝尔地区生长季NDVI整体变化呈反持续性趋势, 结合现有NDVI变化趋势, 未来将呈下降趋势, 对生态环境的保护工作较为不利。大兴安岭森林生长季NDVI与气温呈正相关, 耕地与草原区呈负相关, 而呼伦贝尔大部分地区的生长季NDVI与降水普遍呈正相关, 其中呼伦贝尔草原和大兴安岭两麓耕地的生长季NDVI与降水相关显著, 说明气温是制约北部大兴安岭森林生长的主要因素, 而降水是制约呼伦贝尔草原生态平衡和农牧业发展的主要因素。     

NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China

This study analyzes the temporal change of Normalized Difference Vegetation Index (NDVI) for temperate grasslands in China and its correlation with climatic variables over the period of 1982–1999. Average NDVI of the study area increased at rates of 0.5% yr⁻¹ for the growing season (April–October), 0.61% yr⁻¹ for spring (April and May), 0.49% yr⁻¹ for summer (June–August), and 0.6% yr⁻¹ for autumn (September and October) over the study period. The humped-shape pattern between coefficient of correlation (R) of the growing season NDVI to precipitation and growing season precipitation documents various responses of grassland growth to changing precipitation, while the decreased R values of NDVI to temperature with increase of temperature implies that increased temperature declines sensitivity of plant growth to changing temperature. The results also suggest that the NDVI trends induced by climate changes varied between different vegetation types and seasons.     

陆面植被类型对华北地区夏季降水影响的数值模拟研究

为了检验陆面植被类型变化对华北地区夏季降水的影响,共做了５组数值试验,结果表明,在华北地区以草原或沙漠代替落叶林后,华北地区夏季降水略有减少,但降水总量变化不大,这主要是由于降水变化的区域分布不一致所致;在华北西北部以沙漠代替草原后,华北地区平均降水有所增加,这主要是由华北北部地区降水增加引起的。上述三个试验中,华北 中部以南地区的降水变化主要由积云对流降水变化引起,以北主要由大尺度降水变化引起。     

不同草原类型天然牧草生长发育气象条件分析

通过对内蒙古草原3种不同草原类型,牧草生长发育过程和气象条件关系的分析研究,得出:主要牧草各发育期所需≥0℃积温变幅值和天然牧草各生育期所需热量;牧草返青与黄枯期主要取决于温度状况,而与水分关系较小;利用前10天的平均气温可以判断某生长期的发育进程;牧草对水分的需求主要体现在生长盛期,在典型草原和荒漠区更为明显,适当的干旱可使牧草有早熟现象;牧草的产量主要取决于水热搭配状况,通常情况下水分是典型草原与荒漠草原牧草产量的限制因子,热量可成为草甸草原的限制因子。旬降水量草甸草原达40mm、典型草原达30mm、草原化荒漠达10mm,产量有明显增加。     

气候变化对苏尼特草原NDVI的影响

利用苏尼特草原地区1982—2006年NOAA AVHRR的NDVI数字遥感影像,以及1998-2007年逐旬的SPOT VAG-NDVI数据集,结合研究区域内苏尼特左旗、苏尼特右旗、朱日和、二连浩特4个气象站点的同期降水、气温数据,对植被盖度与不同组合方式的降水及气温数据进行了相关分析,探讨了植被盖度与气象因子的关系。结果表明：苏尼特草原生长季平均盖度、逐月盖度与降水呈正相关关系,与气温呈负相关关系,其中降水对盖度的影响存在着时滞及累积效应。     

Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau

The Tibetan Plateau is a region sensitive to climate change, due to its high altitude and large terrain. This sensitivity can be measured through the response of vegetation patterns to climate variability in this region. Time series analysis of Normalized Difference Vegetation Index (NDVI) imagery and correlation analyses are effective tools to study land cover changes and their response to climatic variations. This is especially important for regions like the Tibetan Plateau, which has a complex ecosystem but lacks a lot of detailed in-situ observation data due to its remoteness, vastness and the severity of its climatic conditions. In this research a time series of 315 SPOT VEGETATION scenes, covering the period between 1998 and 2006, has been processed with the Harmonic ANalysis of Time Series (HANTS) algorithm in order to reveal the governing spatiotemporal pattern of variability. Results show that the spatial distribution of NDVI values is in agreement with the general climate pattern in the Tibetan Plateau. The seasonal variation is greatly influenced by the Asian monsoon. Interannual analysis shows that vegetation density (recorded here by the NDVI values) in the entire Tibetan Plateau has generally increased. Using a 1 km resolution land cover map from GLC2000, seven meteorological stations, presenting monthly data on near surface air temperature and precipitation, were selected for correlation analysis between NDVI and climate conditions in this research. A time lag response has also been found between NDVI and climate variables. Except in desert grassland (Shiquanhe station), the NDVI of all selected sites showed strong correlation with air temperature and precipitation, with variations in correlation according to the different land cover types at different locations. The strongest relationship was found in alpine and subalpine plain grass, the weakest in desert grassland.     

Climate change alters growing season flux dynamics in mesic grasslands

Changing climate could affect the functioning of grassland ecosystems through variation in climate forcings and by altering the interactions of forcings with ecological processes. Both the short and long-term effects of changing forcings and ecosystem interactions are a critical part of future impacts to ecosystem ecology and hydrology. To explore these interactions and identify possible characteristics of climate change impacts to mesic grasslands, we employ a low-dimensional modeling framework to assess the IPCC A1B scenario projections for the Central Plains of the United States; forcings include increased precipitation variability, increased potential evaporation, and earlier growing season onset. These forcings are also evaluated by simulations of vegetation photosynthetic capacity to explore the seasonal characteristics of the vegetation carbon assimilation response for species at the Konza Prairie in North Central Kansas, USA. The climate change simulations show decreases in mean annual soil moisture and and carbon assimilation and increased variation in water and carbon fluxes during the growing season. Simulations of the vegetation response show increased variation at the species-level instead of at a larger class scale, with important heterogeneity in how individual species respond to climate forcings. Understanding the drivers and relationships behind these ecosystem responses is important for understanding the likely scale of climate change impacts and for exploring the mechanisms shaping growing season dynamics in grassland ecosystems.     

Modeling responses of the meadow steppe dominated by Leymus chinensis to climate change

Grassland is one of the most widespread vegetation types worldwide and plays a significant role in regional climate and global carbon cycling. Understanding the sensitivity of Chinese grassland ecosystems to climate change and elevated atmospheric CO₂ and the effect of these changes on the grassland ecosystems is a key issue in global carbon cycling. China encompasses vast grassland areas of 354 million ha of 17 major grassland types, according to a national grassland survey. In this study, a process-based terrestrial model the CENTURY model was used to simulate potential changes in net primary productivity (NPP) and soil organic carbon (SOC) of the Leymus chinensis meadow steppe (LCMS) under different scenarios of climatic change and elevated atmospheric CO₂. The LCMS sensitivities, its potential responses to climate change, and the change in capacity of carbon stock and sequestration in the future are evaluated. The results showed that the LCMS NPP and SOC are sensitive to climatic change and elevated CO₂. In the next 100 years, with doubled CO₂ concentration, if temperature increases from 2.7-3.9˚C and precipitation increases by 10% NPP and SOC will increase by 7-21% and 5-6% respectively. However, if temperature increases by 7.5-7.8˚C and precipitation increases by only 10% NPP and SOC would decrease by 24% and 8% respectively. Therefore, changes in the NPP and SOC of the meadow steppe are attributed mainly to the amount of temperature and precipitation change and the atmospheric CO₂ concentration in the future.     

2000-2013年新疆植被覆盖变化多尺度遥感分析

基于中等分辨率成像光谱仪(MODIS)8 d 500 m分辨率地表反射率数据生成归一化植被指数(NDVI)时间序列,利用线性回归、转折点检测和Mann-Kendall趋势分析方法,分析2000—2013年新疆地区植被覆盖时空变化格局,并结合Landsat数据分析典型区域植被变化。研究结果表明：近14 a来,新疆地区植被覆盖整体呈波动型上升的趋势,植被改善区面积占全区的34.02%,恶劣区的占3.20%,其中2000—2003年植被明显增长、2003—2009年的波动下降及2009—2013年的逐渐回升,植被增长显著的区域主要分布在准噶尔盆地南部和塔里木盆地北部绿洲;大多数植被类型NDVI呈增长趋势,其中增长率最高的是作物、开放灌丛和混交林,6种主要植被类型常绿针叶林、混交林、开放灌丛、多树草原、草原、作物呈现出相似的NDVI变化趋势;在植被覆盖变化显著的4个典型区,NDVI变化受土地覆盖类型变化的影响,荒漠、草地被开垦成农田导致NDVI增加,城市建成区扩张导致NDVI降低。     

青藏高原植物返青期变化及其对气候变化的响应

基于连续的植被指数（NDVI）、气温和降水数据,提取了1982—2009年青藏高原典型台站邻近区域的植物返青期以及0℃和5℃旬均温始期的时序数据,分析了其时空变化特征,探讨了青藏高原冬、春季的气温、降水变化对植物返青期的影响。结果表明：1) 青藏高原典型台站邻近区域植物返青期多年平均值在东西向和南北向上存在显著差异;1982—2009年间,青藏高原典型台站邻近区域植物返青期整体呈提前趋势。2) 青藏高原典型台站0℃和5℃旬均温始期整体呈提前趋势,5℃旬均温始期提前趋势更为显著。3) 青藏高原植物返青期随着冬、春季气温升高和降水增加而提前。与降水相比,返青期与气温的相关程度更高。冬季气温比春季气温对植物返青期的影响更大。