干旱区研究

Arid Zone Research >

2024 , Vol. 41 >Issue 8: 1395 - 1404

DOI: https://doi.org/10.13866/j.azr.2024.08.13

Plant Ecology

Changes in NDVI and its multiscale spatiotemporal responses to precipitation in the Mu Us Desert

  • SHI Tianyi ,
  • ZHANG Mengmeng ,
  • PU Yang ,
  • LIU Shuoyuan
Expand
  • School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China

Received date: 2024-03-28

  Revised date: 2024-05-27

  Online published: 2024-08-22

Fold

Abstract

The Mu Us Desert possesses a delicate ecological environment. It is therefore of utmost importance to understand the correlation between sand-fixing vegetation and precipitation to achieve effective ecological restoration and implement the concept of “water-oriented greening” in the desert. This study examined the fluctuation patterns in vegetation within the Mu Us Desert from 2000 to 2018, as well as its reaction to delayed and cumulative precipitation effects. Our findings revealed significant trends in the annual and seasonal average NDVI of the study area from 2000 to 2018 (P<0.01). However, the spatial distribution of these trends exhibited substantial variation. Notably, the region with a significant increase in summer NDVI accounted for 83.2% of the total area, whereas the region with a significant increase in annual NDVI accounted for only 34.15% of the total area. Moreover, the annual and monthly variations in vegetation NDVI showed no significant time lag in response to precipitation, but a significant cumulative effect was observed. Approximately 38.58% of the study region exhibited a cumulative response of NDVI to precipitation lasting between one and two years, which was mostly concentrated in areas with lower annual precipitation and negligible changes in annual NDVI. Finally, the spatial and temporal distribution of the correlation coefficient between seasonal NDVI and cumulative monthly precipitation exhibited pronounced differences. The response time and percentage of NDVI to precipitation varied across seasons, with a range of 2-3 months (19.25%) for spring, 4 months (73.58%) for summer, and either 1 month (27.22%) or 3 months (34.91%) for autumn. This study revealed the absence of significant temporal delays in the vegetation response to precipitation in the Mu Us Desert. Additionally, it revealed that the cumulative effects varied significantly across different spatiotemporal scales. Consequently, the findings of this study serve as a foundation for optimizing ecological restoration programs involving artificial vegetation, as well as implementing the “water-based greening” approach.

Key words： vegetation NDVI; precipitation; time lag and cumulative effects; water-based greening; Mu Us Desert

Cite this article

SHI Tianyi , ZHANG Mengmeng , PU Yang , LIU Shuoyuan . Changes in NDVI and its multiscale spatiotemporal responses to precipitation in the Mu Us Desert[J]. Arid Zone Research, 2024 , 41(8) : 1395 -1404 . DOI: 10.13866/j.azr.2024.08.13

References

[1] Li C, Fu B, Wang S, et al. Climate-driven ecological thresholds in China’s drylands modulated by grazing[J]. Nature Sustainability, 2023, 6: 1363-1372.
[2] O Sungmin, Park S K. Global ecosystem responses to flash droughts are modulated by background climate and vegetation conditions[J]. Communications Earth & Environment, 2024, 5(1): 1-7.
[3] Yang L, Wylie B K, Tieszen L L, et al. An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the U.S. Northern and Central Great Plains[J]. Remote Sensing of Environment, 1998, 65: 25-37.
[4] Ren H, Wen Z, Liu Y, et al. Vegetation response to changes in climate across different climate zones in China[J]. Ecological Indicators, 2023, 155: 110932.
[5] Jiang L, Jiapaer G, Bao A, et al. Vegetation dynamics and responses to climate change and human activities in Central Asia[J]. Science of the Total Environment, 2017, 599-600: 967-980.
[6] Sun G, Li L, Li J, et al. Impacts of climate change on vegetation pattern: Mathematical modeling and data analysis[J]. Physics of Life Reviews, 2022, 43: 239-270.
[7] 吴万民, 刘涛, 陈鑫. 西北干旱半干旱区NDVI季节性变化及其影响因素[J]. 干旱区研究, 2023, 40(12): 1969-1981.
  [ Wu Wanmin, Liu Tao, Chen Xin. Seasonal changes of NDVI in the arid and semi-arid regions of Northwest China and its influencing factors[J]. Arid Zone Research, 2023, 40(12): 1969-1981. ]
[8] 裴志林, 曹晓娟, 王冬, 等. 内蒙古植被覆盖时空变化特征及其对人类活动的响应[J]. 干旱区研究, 2024, 41(4): 629-638.
  [ Pei Zhilin, Cao Xiaojuan, Wang Dong, et al. Spatiotemporal variation in vegetation coverage in Inner Mongolia and its response to human activities[J]. Arid Zone Research, 2024, 41(4): 629-638. ]
[9] 赵东颖, 蒙仲举, 孟芮冰, 等. 乌兰布和沙漠风沙入黄段植被覆盖动态变化特征及驱动力[J]. 干旱区研究, 2024, 41(4): 639-649.
  [ Zhao Dongying, Meng Zhongju, Meng Ruibing, et al. Dynamic change characteristics and driving forces of vegetation cover in the Ulan Buhe Desert along the Yellow River[J]. Arid Zone Research, 2024, 41(4): 639-649. ]
[10] Chen Z, Wang W, Fu J. Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China[J]. Scientific Reports, 2020, 10: 830.
[11] Zhao J, Huang S, Huang Q, et al. Time-lagged response of vegetation dynamics to climatic and teleconnection factors[J]. Catena, 2020, 189: 104474.
[12] Guo L, Cheng J, Luedeling E, et al. Critical climate periods for grassland productivity on China’s Loess Plateau[J]. Agricultural and Forest Meteorology, 2017, 233: 101-109.
[13] Wei X, He W, Zhou Y, et al. Global assessment of lagged and cumulative effects of drought on grassland gross primary production[J]. Ecological Indicators, 2022, 136: 108646.
[14] Wang X, Cheng H, Li H, et al. Key driving forces of desertification in the Mu Us Desert, China[J]. Scientific Reports, 2017, 7(1): 3933.
[15] 刘如龙, 赵媛媛, 陈国清, 等. 内蒙古黄河流域1990—2020年生境质量评估[J]. 干旱区研究, 2024, 41(4): 674-683.
  [ Liu Rulong, Zhao Yuanyuan, Chen Guoqing, et al. Assessment of habitat quality in the Yellow River Basin in Inner Mongolia from 1990 to 2020[J]. Arid Zone Research, 2024, 41(4): 674-683. ]
[16] Xiu L, Yan C, Li X, et al. Monitoring the response of vegetation dynamics to ecological engineering in the Mu Us Sandy Land of China from 1982 to 2014[J]. Environmental Monitoring and Assessment, 2018, 190: 543.
[17] Sun Z, Mao Z, Yang L, et al. Impacts of climate change and afforestation on vegetation dynamic in the Mu Us Desert, China[J]. Ecological Indicators, 2021, 129: 108020.
[18] Gao W, Zheng C, Liu X, et al. NDVI-based vegetation dynamics and their responses to climate change and human activities from 1982 to 2020: A case study in the Mu Us Sandy Land, China[J]. Ecological Indicators, 2022, 137: 108745.
[19] Feng X, Li J, Cheng W, et al. Evaluation of AMSRE retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China[J]. Remote Sensing of Environment, 2017, 196: 253-264.
[20] Wang X, Wang B, Xu X, et al. Spatial and temporal variations in surface soil moisture and vegetation cover in the Loess Plateau from 2000 to 2015[J]. Ecological Indicators, 2018, 95: 320-330.
[21] Zhang M, Wu X. The rebound effects of recent vegetation restoration projects in Mu Us Sandy Land of China[J]. Ecological Indicators, 2020, 113: 106228.
[22] 杨梅焕, 靳小燕, 王涛. 毛乌素沙地植被物候变化及其对气候变化的响应[J]. 水土保持通报, 2022, 42(2): 242-249.
  [ Yang Meihuan, Jin Xiaoyan, Wang Tao. Vegetation phenology change of Mu Us Sandy Land and its response to climate change[J]. Bulletin of Soil and Water Conservation, 2022, 42(2): 242-249. ]
[23] 雷雅凯. 毛乌素沙地油蒿种群格局研究[D]. 北京: 中国林业科学研究院, 2012.
  [ Lei Yakai. Spatial Pattern of Artemisia Ordosica Population in Mu Us Sand Land, in Inner Mongolia[D]. Beijing: Chinese Academy of Forestry, 2012. ]
[24] 牛振国, 李保国, 张凤荣, 等. 参考作物蒸散量的分布式模型[J]. 水科学进展, 2002, 13(3): 303-307.
  [ Niu Zhenguo, Li Baoguo, Zhang Fengrong, et al. A distributed model of reference evapotranspiration based on the DEM[J]. Advances in Water Science, 2002, 13(3): 303-307. ]
[25] 朱娅坤, 秦树高, 张宇清, 等. 毛乌素沙地植被物候动态及其对气象因子变化的响应[J]. 北京林业大学学报, 2018, 40(9): 98-106.
  [ Zhu Yakun, Qin Shugao, Zhang Yuqing, et al. Vegetation phenology dynamic and its responses to meteorological factor changes in the Mu Us Desert of northern China[J]. Journal of Beijing Forestry University, 2018, 40(9): 98-106. ]
[26] 杨梅焕, 李扬, 王涛, 等. 毛乌素沙地植被水分利用效率时空变化特征及其对水热条件的响应[J]. 测绘通报, 2023(7): 44-50, 79.
  [ Yang Meihuan, Li Yang, Wang Tao, et al. Spatial and temporal change of water use efficiency and its response to air temperature and precipitation in the Mu Us Sandy Land[J]. Bulletin of Surveying and Mapping, 2023(7): 44-50, 79. ]
[27] 高吉喜, 史园莉, 张宏伟, 等. 中国区域250米归一化植被指数数据集(2000—2022)[DB/OL]. 国家青藏高原数据中心, 2023.
  [ Gao Jixi, Shi Yuanli, Zhang Hongwei, et al. China regional 250 m normalized difference vegetation index data set (2000-2022)[DB/OL]. National Tibetan Plateau/Third Pole Environment Data Center, 2023. ]
[28] 彭守璋. 中国1 km分辨率逐月降水量数据集(1901-2022)[DB/OL]. 国家青藏高原数据中心, 2020.
  [ Peng Shouzhang. 1-km monthly precipitation dataset for China (1901-2022)[DB/OL]. National Tibetan Plateau/Third Pole Environment Data Center, 2020. ]
[29] Sen P K. Estimates of the regression coefficient based on Kendall’s tau[J]. Journal of the American Statistical Association, 1968, 63: 1379-1389.
[30] Hamed K H, Rao A R. A modified Mann-Kendall trend test for autocorrelated data[J]. Journal of Hydrology, 1998, 204(1-4): 182-196.
[31] Pearson K. Notes on the history of correlation[J]. Biometrika, 1920, 13(1): 25-45.
[32] Wu D, Zhao X, Liang S, et al. Time-lag effects of global vegetation responses to climate change[J]. Global Change Biology, 2015, 21: 3520-3531.
[33] 赵东升, 高璇, 吴绍洪, 等. 基于自然分区的1960—2018年中国气候变化特征[J]. 地球科学进展, 2020, 35(7): 750-760.
  [ Zhao Dongsheng, Gao Xuan, Wu Shaohong, et al. Trend of climate variation in China from 1960 to 2018 based on natural regionalization[J]. Advances in Earth Science, 2020, 35(7): 750-760. ]
[34] Miao L, Moore J C, Zeng F, et al. Footprint of research in desertification management in China[J]. Land Degradation & Development, 2015, 26(5): 450-457.
[35] 许冬梅, 刘彩凤, 谢应忠, 等. 毛乌素沙地南缘生态过渡带植被物种多样性的研究[J]. 干旱区资源与环境, 2010, 24(3): 153-157.
  [ Xu Dongmei, Liu Caifeng, Xie Yingzhong, et al. Studies on species diversity in southern ecotone of Mu Us Sandy Land[J]. Journal of Arid Land Resources and Environment, 2010, 24(3): 153-157. ]
[36] Propastin P A, Kappas M, Muratova N R. Inter-annual changes in vegetation activities and their relationship to temperature and precipitation in Central Asia from 1982 to 2003[J]. Journal of Environmental Informatics, 2008, 12: 75-87.
[37] 王祎宸, 贺洁, 何亮, 等. 黄河流域2001—2020年植被物候及其对气候变化的响应[J]. 生态学报, 2024, 44(2): 844-857.
  [ Wang Yichen, He Jie, He Liang, et al. Vegetation phenology and its response to climate change in the Yellow River Basin from 2001 to 2020[J]. Acta Ecologica Sinica, 2024, 44(2): 844-857. ]
Options
Outlines

/

〈 〉