为辨识长江流域陆地生态系统植被的时空变化特征及其对水热条件的响应,根据长江流域2000—2015年MODIS NDVI(Normalized Difference Vegetation Index)资料和气象资料,利用时间序列分析技术研究长江流域及主要陆地生态系统NDVI和水热条件的年际变化及相关性特征。结果表明:①近16 a来,全流域及主要生态系统NDVI均呈现出显著的增加趋势,农田、森林、水体与湿地生态系统NDVI增长率较大;②降水量整体略微增加,具有明显的空间差异性,积温(≥10 ℃)增加明显,且在空间上普遍呈现出增加的趋势;③受气候条件和生态系统类型差异性的影响,不同水热条件分区上NDVI与降水量和积温(≥10 ℃)的相关性有所差别,但整体而言,由于长江流域水量相对丰沛,降水量并不是长江流域植被生长的限制性因子,降水量与NDVI相关性并不显著,但对于森林、草地和荒漠生态系统而言,植被NDVI与积温呈现出较为明显的正相关关系,表明热量条件是长江流域植被生长的限制性因子。研究成果可为长江流域主要陆地生态系统变化的监测和预测提供一定的数据和技术支撑。
Abstract
In order to identify the spatiotemporal variations of NDVI in terrestrial ecosystem in Yangtze River Basin and its response to hydrothermal condition, we analyzed the interannual changes of NDVI, accumulated temperature, precipitation and their correlations in the Yangtze River Basin based on the MODIS NDVI, temperature and precipitation data in 2000-2015 using time series analysis techniques. Results revealed that: (1) The NDVI displayed a significant increasing trend in the Yangtze River Basin in recent 16 years. The growth rates of NDVI in farmland, forest, water and wetland ecosystem were larger than those of others. (2) Precipitation increased slightly in the whole basin with evident spatial heterogeneity. Accumulated temperature above 10 ℃significantly increased and generally presented increasing trend in spatial scale. (3) Due to differences in climate and ecosystem patterns, the correlation between NDVI and precipitation and accumulated temperature above 10 ℃varied in different zones. In general,precipitation is not a restrictive factor for vegetation growth in the Yangtze River Basin. The correlation between NDVI and precipitation is not significant. But for forest, grassland and desert ecosystems, NDVI and accumulated temperature present a more significant positive correlation, indicating that heat condition is a restrictive factor of vegetation growth in the Yangtze River Basin.
关键词
陆地生态系统 /
NDVI /
时空变化特征 /
水热条件 /
长江流域
Key words
terrestrial ecosystem /
NDVI /
spatio-temporal change characteristics /
hydrothermal condition /
Yangtze River Basin
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参考文献
[1] 丁明军,张镱锂,刘林山,等.青藏高原植被覆盖对水热条件年内变化的响应及其空间特征[J].地理科学进展,2010,29(4):507-512.
[2] WALTHER G R. Community and Ecosystem Responses to Recent Climate Change[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2010, 365(1549): 2019-2024.
[3] BONAN G B. Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests[J]. Science, 2008, 320(5882): 1444-1449.
[4] XU L, MYNENI R B, CHAPIN III F S, et al. Temperature and Vegetation Seasonality Diminishment over Northern Lands[J]. Nature Climate Change, 2013, 3(6): 581-586.
[5] BAO G, BAO Y H, SANJJAVA A,et al. NDVI-indicated Long-term Vegetation Dynamics in Mongolia and Their Response to Climate Change at Biome Scale [J]. International Journal of Climatology, 2015, 35(14): 4293-4306.
[6] TIAN F, FENSHOLT R, VERBESSELT J,et al. Evaluating Temporal Consistency of Long-term Global NDVI Datasets for Trend Analysis[J]. Remote Sensing of Environment, 2015, 163:326-340.
[7] JU J, MASEK J G. The Vegetation Greenness Trend in Canada and US Alaska from 1984-2012 Landsat Data [J]. Remote Sensing of Environment, 2016, 176: 1-16.
[8] TIAN F, BRANDT M, LIU YY, et al. Remote Sensing of Vegetation Dynamics in Drylands: Evaluating Vegetation Optical Depth (VOD) Using AVHRR NDVI and in situ Green Biomass Data over West African Sahel[J]. Remote Sensing of Environment, 2016, 177: 265-276.
[9] PETTORELLI N, VIK J O, MYSTERUD A, et al. Using the Satellite-derived NDVI to Assess Ecological Responses to Environmental Change[J]. Trends in Ecology and Evolution, 2005, 20(9): 503-510.
[10]HUANG Y, SALAMA M, KROL M S, et al. Estimation of Human-induced Changes in Terrestrial Water Storage through Integration of GRACE Satellite Detection and Hydrological Modeling: A Case Study of the Yangtze River Basin[J]. Water Resources Research, 2015,51(10): 8494-8516.
[11]张晓娅,杨世伦.流域气候变化和人类活动对长江径流量影响的辨识(1956~2011)[J].长江流域资源与环境,2014,23(12):1729-1739.
[12]石培礼,吴 波,程根伟,等.长江上游地区主要森林植被类型蓄水能力的初步研究[J].自然资源学报,2004,19(3):351-360.
[13]STOW D, DAESCHNER S, HOPE A, et al. Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the 1990s[J]. International Journal of Remote Sensing, 2003, 24(5):1111-1117.
[14]高继卿,杨晓光,董朝阳,等.气候变化背景下中国北方干湿区降水资源变化特征分析[J]. 农业工程学报,2015,31(12):99-110.
[15]马明国,王 建,王雪梅.基于遥感的植被年际变化及其与气候关系研究进展[J].遥感学报,2006,10(3):421-431.
[16]HAMED K H. Trend Detection in Hydrologic Data: The Mann-Kendall Trend Test under the Scaling Hypothesis[J]. Journal of hydrology, 2008, 349(3/4): 350-363.
[17]ICHII K, KAWABATA A, YAMAGUCHI Y. Global Correlation Analysis for NDVI and Climatic Variables and NDVI Trends: 1982-1990[J]. International Journal of Remote Sensing, 2002, 23(18): 3873-3878.
基金
国家重点研发计划项目(2017YFC1502404);国家自然科学基金项目(41890821,51709008);湖北省自然科学基金项目(2018CFB655);中央级公益性科研院所基本科研业务费项目(CKSF2017061/SZ,CKSF2017029/SZ);河南省高等学校青年骨干教师培养计划项目(2016GGJS-224)
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