三江源植被碳利用率动态变化及其对气候响应

本文基于MODIS GPP/NPP数据估算了三江源植被碳利用率(CUE),结合气象数据和高程数据采用一元线性回归和相关分析法,探讨了2001~2017年三江源植被CUE的时空变化特征及植被CUE对气温、降水量和蒸散量变化的响应.结果表明:(1)三江源植被CUE年内3~10月表现为先增加后降低的变化趋势,其中6月植被CUE最高.(2)三江源年植被碳利用率位于0.73~1,平均水平为0.85;植被CUE空间上呈现北高南低,西高东低的分布特征.(3)整体上,三江源4~10月植被碳利用率与同期气温、降水量和蒸散量分别呈现正相关、负相关和负相关关系,降水量是影响三江源植被CUE变化的主要影响因素,气温为次要因素,蒸散量影响程度最小.

雅鲁藏布江下游高山峡谷区林下草本植物多样性沿海拔梯度变化特征研究

研究山地植物多样性的海拔梯度分布规律,对揭示草本植物物种多样性对环境变化的响应机制至关重要。以派墨公路沿线森林草本植物群落为研究对象,通过野外调查分析了不同海拔段(2300~3500 m)林下草本植物群落结构及物种多样性(α多样性、β多样性)的变化格局。结果发现:1)调查区内共分布物种29科47属60种,群落物种组成具有明显的温带性质;2)林下草本植物α多样性指数呈波动变化趋势,除Pielou指数外,海拔对Patrick指数、Shannon-Wiener指数、Simpson指数均具有显著性影响,且在较低海拔和高海拔处呈现较高的多样性;3)林下草本β多样性Sorensen指数在海拔2337~2557 m和2971~3203 m出现两个最小值,而Cody指数在海拔2337~2557 m和2971~3203 m呈上升趋势且在2337~2557 m和2971~3203 m出现2个峰值,表明该海拔地段β多样性最大,在这两个海拔段内群落间相似性低,成为物种更替速率较快的过渡地带。本研究能够为公路沿线森林生态系统草本植物多样性的保护提供理论指导和支撑。

Response of Lakes to Climate Change in Xainza Basin Tibetan Plateau Using Multi-Mission Satellite Data from 1976 to 2008

Changes in the lake areas of Xainza basin in the past 33 years （1976 to 2008） were studied using Landsat data from Multispectral Scanners （1973- 1977）, Thematic Mapper （1989-1992, 2007-2009）, and Enhanced Thematic Mapper Plus （1999-2002）. The results indicated that lakes in the study area evidently expanded from 1976 to 2008, with total expansion of 1512.64km2. The mean annual air temperature presented an upward trend with certain fluctuations from 1966 to 2008. The air temperature rise rates in the cold season （o.31~C/loa） were higher than those in the hot season （0.24℃/1oa）, in the Xainza station example. Precipitation exhibited evident seasonal differences. Mean annual precipitation in hot season is 281.48 mm and cold season is 32.66 mm from 1966 to 2008 in study area. Precipitation in the hot season was the major contributor to the increase in annual precipitation. Grey relational analysis （GRA） was used to study the response of lake areas to climatic factors. The mean air temperature and precipitation were selected as comoared series, and the lake areas were regarded as the reference series. The grey relational grade （GRG） between compared series and reference series were calculated through GRA. The results indicated that changes in lake areas were mainly affected by climatic factors in the hot season. Lakes in this region were classified into three grades, namely, Grades I, II, and III according to the recharge source and elevation. The GRGs of each series varied for different grade lakes： the area of Grade III lakes were the most relevant to the hot season factors, the GRGs of precipitation and air temperature were 0.7570 and 0.6606; followed by the Grade II lakes; Grade I lakes were more sensitive to the air temperature.

A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China

Accurate measurements of the associated vegetation phenological dynamics are crucial for understanding the relationship between climate change and terrestrial ecosystems. However, at present, most vegetation phenological calculations are based on a single algorithm or method. Because of the spatial, temporal, and ecological complexity of the vegetation growth processes, a single algorithm or method for monitoring all these processes has been indicated to be elusive. Therefore, in this study, from the perspective of plant growth characteristics, we established a method to remotely determine the start of the growth season(SOG) and the end of the growth season(EOG), in which the maximum relative change rate of the normalized difference vegetation index(NDVI) corresponds to the SOG, and the next minimum absolute change rate of the NDVI corresponds to the EOG. Taking the Three-River Headwaters Region in 2000–2013 as an example, we ascertained the spatiotemporal and vertical characteristics of its vegetation phenological changes. Then, in contrast to the actual air temperature data, observed data and other related studies, we found that the SOG and EOG calculated by the proposed method is closer to the time corresponding to the air temperature, and the trends of the SOG and EOG calculated by the proposed method are in good agreement with other relevant studies. Meantime, the error of the SOG between the calculated and observed in this study is smaller than that in other studies.

Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China

The Fraction of Absorbed Photosynthetically Active Radiation(FPAR) is an important indicator of the primary productivity of vegetation. FPAR is often used to estimate the assimilation of carbon dioxide in vegetation. Based on MOD15 A2 H/FPAR data product, the temporal and spatial variation characteristics and variation trend of FPAR in different vegetation types in 2001 to 2018 were analyzed in the Hengduan Mountains. The response of FPAR to climate change was investigated by using Pearson correlation analytical method and partial least squares regression analysis. Results showed that the FPAR in Hengduan Mountains presented an increasing trend with time. Spatially, it was high in the south and low in the north, and it also showed obvious vertical zonality by elevation gradient.The vegetation FPAR was found to be positively correlated with air temperature and sunshine duration but negatively correlated with precipitation. Partial least squares regression analysis showed that the influence of sunshine duration on vegetation FPAR in Hengduan Mountains was stronger than that of air temperature and precipitation.

Erratum to: Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China

Erratum to:J.Mt.Sci.(2021)18(4):891-906 https://doi.org/10.1007/s11629-020-6465-9 On Page 894,Fig.1d is redundant in the original article and should be removed.On Page 895,in Section 2.2,the 4th paragraph,the figure number"Fig.1d"in the last sentence is incorrect.It should be corrected into"Fig.1c".On Page 896,in Section 3.2,the 1st paragraph,the figure number"Fig.1d"in the 2nd sentence is incorrect.It should be corrected into"Fig.1c".

青藏高原气候变化对草地碳汇/源格局的影响

草地碳汇/源是植被生态系统中碳收支和碳平衡的一个重要内容,区分碳汇和碳源对气候变化的响应可为减源增汇提供科学依据。基于MODIS NPP数据和土壤呼吸模型量化了2001—2019年青藏高原草地净生态系统生产力(NEP)的时空变化和碳汇/源格局,利用通径分析方法分析了青藏高原气候变化对草地碳汇/源的影响。结果表明:青藏高原草地NEP呈现东高西低的分布格局,年平均值为54.41 g C m^(-2)。草地整体上以碳汇功能为主。碳汇区面积约为72.26万km^(2),碳源区面积约为47.82万km^(2),净碳汇总量65.35 Tg C a^(-1)。近19年青藏高原草地NEP以增加趋势为主,青藏高原气候暖湿化趋势有利于草地NEP的增加,增强碳汇;而暖干化趋势对NEP的影响在不同生态地理区差异较大。

2000～2015年川西高原植被EVI海拔梯度变化及其对气候变化的响应

川西高原植被系统受地形因子影响在垂直方向上空间特征差异明显。以MODIS EVI遥感数据作为植被动态监测指数,结合高程数据分析2000~2015年川西高原植被EVI沿海拔梯度的变化规律,然后根据川西高原内部及附近39个气象站点的气温和降水资料开展川西高原植被EVI变化对气候变化的响应研究。结果表明:(1)川西高原近16年生长季植被EVI以0.8%/10 a的速率波动增加,沿海拔梯度具有先升高后降低的特点,垂直分布特征差异显著;(2)川西高原植被EVI变化趋势整体处于稳定状态,改善面积多于退化面积。在<1000 m的低海拔区域,由于人类活动的干扰,植被退化严重;中等海拔范围内水热条件充足,利于植被生长,植被逐渐得到改善,局部地区有轻微退化现象;在>4000 m的高海拔地带,植被EVI波动幅度较低并趋于稳定;(3)不同高程区间内植被EVI变化受气候影响不同,川西高原高海拔地区植被生长主要受气温控制,而中等海拔地区受降水影响较大。(4)在0.05显著性水平下,川西高原植被EVI变化受非气候因子驱动的面积分布较广,约84.22%;受气候因子驱动的面积占比为15.78%,气温对植被生长和分布的驱动作用强于降水驱动作用。

青藏高原植被生长季NDVI时空变化与影响因素

青藏高原是中国乃至亚洲的生态屏障,研究其植被对气候变化的响应对区域生态保护具有重要的现实意义。基于MOD09A1数据反演的生长季归一化植被指数(NDVI),分析2001—2018年青藏高原植被生长季NDVI时空特征和变化趋势,结合气象站点数据阐释NDVI与气候因子的关系。结果表明:研究期间,青藏高原植被生长季NDVI呈缓慢上升趋势,不同气候区生长季NDVI年际变化差异明显,NDVI值波动幅度表现为高原湿润气候区>半湿润气候区>半干旱气候区>干旱气候区。青藏高原湿润气候区、半湿润气候区、干旱气候区、半干旱气候区NDVI显著升高和降低面积占比分别为1.4%和1.9%、4.9%和1.5%、16.4%和0.8%、7.0%和2.0%,干旱和半干旱气候区NDVI升高面积占比明显大于湿润和半湿润气候区。气温是影响湿润气候区和半湿润气候区NDVI变化的主导因子,而在干旱气候区,降水对NDVI的影响明显强于其他气候因子。气温对整个青藏高原植被生长季NDVI的驱动作用强于降水和相对湿度。

四川盆地PM_(2.5)浓度时空变化特征遥感监测与影响因子分析

四川盆地因其独特的地形地貌、静风和高湿等气象条件,导致盆地内部大气污染物扩散难度大,随着城市化与工业化进程加快,区内PM_(2.5)污染日益加重,四川盆地已成为国家大气污染防治的重点地区之一.基于PM_(2.5)浓度遥感反演产品,采用空间自相关分析与灰色关联分析方法,研究了四川盆地PM_(2.5)浓度的时空分布特征及其影响因素.结果表明,四川盆地PM_(2.5)浓度具有显著的空间聚集性,高-高聚集类型分布集中,低-低聚集类型分布较为分散;针叶林对PM_(2.5)的吸收抑制作用明显高于灌丛和草地等其他植被类型.研究认为,影响四川盆地PM_(2.5)浓度的主要气象因子是风速和气温,人口密度与经济规模则是影响四川盆地PM_(2.5)浓度的主要人类活动因子,产业结构及其规模变化对四川盆地PM_(2.5)浓度也产生一定影响.

2000年以来内蒙古生长季旱情变化遥感监测及其影响因素分析

为探讨内蒙古旱情状况及其影响因素,利用MODIS 16 d合成的植被指数产品数据MOD13A2和8 d合成的地表温度产品数据MOD11A2构建Ts-NDVI特征空间,计算温度植被干旱指数(TVDI),基于内蒙古2000-2017年生长季每16 d的TVDI分析了近18年来内蒙古生长季旱情时空分布特征,结合气温和降水资料初步探讨了旱情变化的影响因素。结果表明:(1)2000-2017年内蒙古生长季TVDI平均值为0.6,重旱和中旱所占面积最大,其中2007年、2010年为旱情最为严重的年份。内蒙古干旱空间分异明显,西南部以轻旱为主,中部地区以中旱为主,大兴安岭以西的呼伦贝尔草原等地旱情严重。(2)近18年内蒙古生长季干旱程度呈现轻微加重趋势,年际变化值θslope介于-0.07~0.7之间,阿鲁科尔沁旗东北部至霍林河一带旱情加重趋势最为严重,阿荣旗和扎兰屯等农业生产地区旱情有轻微加重趋势。(3)2017年内蒙古生长季以区域性和局域性干旱为主,6月和9月干旱最为严重,呼伦贝尔草原和鄂尔多斯高原西部干旱发生频率高且程度重。(4)内蒙古干旱影响因子分析结果表明,TVDI值与气温呈正相关、与降水和坡度呈负相关、与小于1300 m的高程呈正相关、与大于1300 m的高程呈负相关关系。内蒙古生长季TVDI与气温和降水偏相关分析结果表明,锡林郭勒盟苏尼特左旗北部、呼伦贝尔鄂伦春自治旗和呼伦贝尔草原等地旱情与气温正相关关系较为显著(P<0.01),锡林郭勒盟东北部干旱情况与降水负相关关系较为显著(P<0.01),其中,气温对旱情的影响强于降水。

气候变化背景下横断山区植被叶面积指数时空变化特征分析

叶面积指数作为陆地生态过程的重要参数,对生态系统碳循环和区域水土保持具有重要意义。基于MOD15A2H/LAI遥感数据集,利用Theil-Sen media斜率分析、Mann-Kendall趋势检验法以及相关分析法,研究了2001~2018年横断山区植被LAI时空分布格局及变化趋势,根据气象数据、土地覆盖数据和DEM数据,重点分析了横断山区植被LAI对气候变化的响应。结果表明:(1)2001~2018年横断山区植被LAI均值为1.22,空间上呈由北向南逐渐递增的分布特征;(2)横断山区植被LAI受地形影响明显,植被LAI值随海拔升高表现为“升高-降低-稳定”的特征,随坡度增加植被LAI值呈上升趋势;(3)近18a横断山区植被LAI整体以0.07·(10a)^(-1)的速率增加,其中68.92%的区域呈增加趋势,31.08%的区域呈退化趋势;(4)横断山区植被LAI与气温和日照时长呈正相关关系,与降水呈负相关关系。在P<0.05显著性水平下,植被LAI与气温、降水和日照时长的显著相关面积比例依次为22.7%、33.58%和31.80%,表明植被LAI受降水和日照时长影响较大,气温的影响相对较弱。