Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Identifying time-lag effects of temperature and precipitation on vegetation growth variation in the lower Yellow River of east China
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 07 March 2026

Identifying time-lag effects of temperature and precipitation on vegetation growth variation in the lower Yellow River of east China

  • Xinying Lu1,
  • Yan Xiao1,2,
  • Yifang Duan1 &
  • …
  • Nianci Duan1 

Scientific Reports , Article number:  (2026) Cite this article

  • 2736 Accesses

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate change
  • Climate-change ecology
  • Climate-change impacts
  • Climate sciences
  • Ecology
  • Environmental impact
  • Environmental sciences
  • Phenology
  • Projection and prediction
  • Urban ecology

Abstract

Addressing the backdrop of global climatic changes and focusing on how vegetation reacts to these shifts,this article acting a imperative significant.This article investigates the administrative jurisdictions in the eastern of lower of the Yellow River.It selects MODIS NDVI remote sensing data spanning from 2001 to 2021 and employs different analysis methods including simple correlation, partial correlation, and multiple regression to quantitatively assess the response of NDVI during the vegetation growth season to climate variations, analyzing it on a grid by grid basis within the research region. Studies have found that: (1) the NDVI’s responsiveness to temperature and precipitation during the peak growth season exhibited a certain delay; A temperature response lag showed one or two months, while a precipitation response lag showed one or three months.(2) Partial correlation analysis demonstrated that NDVI was negatively correlated with temperature, while NDVI was positively correlated precipitation. Moreover, during the growing season, NDVI across various vegetation types revealed a stronger association with precipitation compared to temperature.(3) The cultivated vegetation, coniferous forest, and swamp vegetation exhibit significant responses to climatic changes.(4) When accounting for time-lag effects, it has increased by 128.98% for the capacity of climate variables to interpret vegetation dynamics compared to simultaneous assessments.

Data availability

Data are contained within the article.

References

  1. Zheng, Y., Zhou, G., Zhang, X., Yang, D., Xia, L. Sensitivity of China’s terrestrial ecosystems to global change. Acta Botanica Sinica 1997, 837–840+891–892.

  2. Loehle, C. & LeBlanc, D. Model-based assessments of climate change effects on forests: A critical review. Ecol. Modell. 90, 1–31 (1996).

    Google Scholar 

  3. Melillo, J. M. et al. Global climate change and terrestrial net primary production. Nature 363, 234–240 (1993).

    Google Scholar 

  4. Liang, Z., Sun, R. & Duan, Q. The spatiotemporal variation characteristics and driving factors of vegetation NDVI in the Yellow River water source conservation area. Prog. Geograph. Sci. 42, 1717–1732 (2023).

    Google Scholar 

  5. Liu, J. et al. Analysis of vegetation spatiotemporal variation characteristics and response to meteorological factors in the growing Season in Yalong River basin. Ecol. Environ. Sci. 30, 512–522. https://doi.org/10.16258/j.cnki.1674-5906.2021.03.009 (2021).

    Google Scholar 

  6. He, B., Ding, J., Li, H., Liu, B. & Chen, W. Spatiotemporal variation of vegetation phenology in Xinjiang from 2001 to 2016. Acta Ecol. Sinica 38, 2139–2155 (2018).

    Google Scholar 

  7. Tong, L., Zeng, B. & Wang, X. Phenological changes of different vegetation types in Shanxi Province from 2000 to 2012 and their response to climate change. Res. Soil Water Conserv. 23, 7 (2016).

    Google Scholar 

  8. Zhang, Y. et al. Spatiotemporal variations of vegetation greenness in the forest belt of Northeast China during 1982–2020. Acta Ecol. Sin. 43, 6670–6681 (2023).

    Google Scholar 

  9. Cao, L. et al. Spatiotemporal variation characteristics and impact factors of NDVI in Jiangsu Province. Bull. Soil Water Conserv. 35, 151–154 (2015).

    Google Scholar 

  10. Liu, H., Jiang, L., Liu, B., Liu, R. & Xiao, Z. Characteristics of drought in China and its effect on vegetation change in recent 40 years. Acta Ecol. Sin. 43, 7936–7949 (2023).

    Google Scholar 

  11. Zhou, W., LIU, Z., Wang, K., Zou, S., Zhong, H., Chen, F. Spatio-temporal changes of drought features and their impacts on the gross primary production in farming-pastoral ecotone of Northern China. Acta Ecologica Sinica.

  12. Yan, D., Wu, X., Wang, B. & Hao, H. Characteristics and driving forces of changes in vegetation coverage on the Loess Plateau,1982-2015. Acta Ecol. Sin. 43, 9794–9804 (2023).

    Google Scholar 

  13. Zhu, W., Mao, F., Xu, Z., Zheng, J. & Song, L. Analysis on response of vegetation index to climate change and its prediction in the Three-Rivers-Source Region. Plateau Meteorol. 38, 693–704. https://doi.org/10.7522/j.issn.1000-0534.2018.00105 (2019).

    Google Scholar 

  14. Fu, S. et al. Variations in the NDVI characteristics during the summer and the climatic factor responses in the Qinling-Daba Mountains. Arid Zone Res. 40, 1563–1574. https://doi.org/10.13866/j.azr.2023.10.03 (2023).

    Google Scholar 

  15. Ouyang, X., Dong, X., Wei, R., Long, C. & Wu, H. Analysis of spatiotemporal variation of NDVl in thevegetation growing season and responses to climaticfactors in Qinghai-Tibet Plateau. Res. Soil Water Conserv. 30, 220–229. https://doi.org/10.13869/j.cnki.rswc.2023.02.047 (2023).

    Google Scholar 

  16. Tian, W., Liu, M., Zhang, Z., Zhang, X. & Wang, Q. Attribution analysis of NDVI evolution in mountainous area of Hebei Province considering climatedelay effect. South-to-North Water Trans. Water Sci. Technol. 21, 962–971. https://doi.org/10.13476/j.cnki.nsbdqk.2023.0092 (2023).

    Google Scholar 

  17. Wang, H. et al. Dynamic pattern of vegetation in Xinjiang and its time-lag effect on climate. Trans. Chinese Soc. Agric. Eng, 39, 137–145. https://doi.org/10.11975/j.issn.1002-6819.202303033 (2023).

    Google Scholar 

  18. Zhu, Y. et al. Performance evaluation of GIMMS NDVI based on MODIS NDVI and SPOT NDVI data. Chin. J. Appl. Ecol. 30, 536–544. https://doi.org/10.13287/j.1001-9332.201902.016 (2019).

    Google Scholar 

  19. Gu, C. et al. Evaluation of consistency among four NDVI datasets applied to Three River Source Region, Qinghai province China. Geograph. Res. 42(05), 1378–1392 (2023).

    Google Scholar 

  20. Liu, L., Liu, L. & Hu, Y. Comparative analysis of global vegetation phenology based on AVHRR and MODIS. Remote Sens. Technol. Appl. 27, 754–762. https://doi.org/10.11873/j.issn.1004-0323.2012.5.754 (2012).

    Google Scholar 

  21. Zhang, Y., Sun, M., Xin, Y., Yang, C. Trend and influencing factors of vegetation NDVI in Eastern Sichuan from 2000 to 2020. Res. Soil Water Conserv.

  22. Wu, D. et al. Time-lag effects of global vegetation responses to climate change. Glob. Chang. Biol. 21, 3520–3531. https://doi.org/10.1111/gcb.12945 (2015).

    Google Scholar 

  23. Liao, R., Qi, S., Lai, J., Tang, Y., Li, P. Spatial-temporal variation and driving mechanism of water erosion in southwest alpine-canyon area of China. Rese. Soil Water Conserv.

  24. Yang, T., Rao, S. & Chen, D. Analysis of temperature and precipitation changes in the Yellow River Basin since 1951. Yellow River 31, 76–77 (2009).

    Google Scholar 

  25. Zhao, Q. et al. Plant species diversity and its response to environmental factors in typical river riparian zone in the middle and lower reaches of Yellow River. Chin. J. Ecol. 34, 1325–1331 (2015).

    Google Scholar 

  26. Xu, Y., Yang, Y. A 5 km resolution dataset of monthly NDVI product of China. China Sci. Data 2022, 007.

  27. Cheng, C. Spatio-temporal Changes of Vegetation Cover and Their Influencing Factors in the Yellow River Basin from 1982 to 2015. (2020).

  28. Xie, H. et al. Changes of NDVI and EVI and their responses to climatic variables in the Yellow River Basin during the growing season of 2000-2018. Acta Ecol. Sin. 42, 4536–4549 (2022).

    Google Scholar 

  29. Tian, Z., Ren, Z., Wei, H. Driving mechanism of the spatiotemporal evolution of vegetation in the yellow river basin from 2000 to 2020. Environ. Sci.

  30. Zhang, B. Study on the response of vegetation cover to climate change under different geological and landform backgrounds. (2020).

  31. Fan, P., Wang, J., Ye, H. & Zahng, K. Study on vegetation changes and climate factors in a karst region of southwest China. Ecol. Environ. Sci. 28, 1080–1091. https://doi.org/10.16258/j.cnki.1674-5906.2019.06.002 (2019).

    Google Scholar 

  32. Bao, C. & Chen, H. On time-lag response of vegetation cover to climate change in Northeast Plain. Stand. Surv. Mapp. 36, 14–20 (2020).

    Google Scholar 

  33. Fu, M. et al. Erosional changes and climatic evolution of the Lake Dayeze in the Lower Yellow River. Trans. Oceanol. Limnol. 43, 8–16. https://doi.org/10.13984/j.cnki.cn37-1141.2021.03.002 (2021).

    Google Scholar 

  34. Fu, H., Wang, R., Wang, X. Analysis of spatiotemporal variations and driving forces of NDVI in the Yellow River basin during 1999—2018. Res. Soil Water Conserv.

  35. Chen, T., de Jeu, R. A. M., Liu, Y., van der Werf, G. R. & Dolman, A. J. Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia. Remote Sens. Environ. 140, 330–338 (2014).

    Google Scholar 

  36. Zhan, C. et al. Drought-related cumulative and time-lag effects on vegetation dynamics across the Yellow River Basin, China. Ecol. Indic. 143, 109409 (2022).

    Google Scholar 

  37. Kong, D., Miao, C., Wu, J., Zheng, H. & Wu, S. Time lag of vegetation growth on the Loess Plateau in response to climate factors: Estimation, distribution, and influence. Sci. Total Environ. 744, 140726 (2020).

    Google Scholar 

  38. Cui, L., Shi, J., Yang, Y. & Fan, W. Ten-day Response of vegetation NDVI to the Variations of Temperature and Precipitation in Eastern China. Acta Geograph. Sinica. 64(7), 850–860 (2009).

    Google Scholar 

  39. Deng, Z., Zhang, J., Yu, M. & Xu, Q. Spatio-temporal change of land use in South Mountain of Jinan. J. Cap. Normal Univ. (Nat. Sci. Ed.) 31, 69–73+79. https://doi.org/10.19789/j.1004-9398.2010.01.016 (2010).

    Google Scholar 

  40. Braswell, B. H., Schimel, D. S., Linder, E. & Moore, B. The response of global terrestrial ecosystems to interannual temperature variability. Science 278, 870–873. https://doi.org/10.1126/science.278.5339.870 (1997).

    Google Scholar 

  41. Wang, M., Zhao, H., Wu, X., Chen, Z., Jiang, S. Vegetation dynamics and its Driving force in the Irtysh River Basin considering climatic temporal effects. Acta Ecologica Sinica.

  42. Jobbágy, E. G. S., Osvaldo E., Paruelo, J. M. Patterns and controls of primary production in the Patagonian steppe. A remote sensing approach.

  43. Zuo, D. et al. Time-lag effects of climatic change and drought on vegetation dynamics in an alpine river basin of the Tibet Plateau, China. J. Hydrol. 600, 126532 (2021).

    Google Scholar 

  44. Jiao, T., Williams., C. A., Kauwe., M. G. D., Schwalm., C. R. & Medlyn., B. E. Patterns of post-drought recovery are strongly influenced by drought duration, frequency, post-drought wetness, and bioclimatic setting. Glob. Change Biol. https://doi.org/10.1111/gcb.15788 (2021).

    Google Scholar 

  45. A, D., Zhao, W., Qu, X., Jing, R. & Xiong, K. Spatio-temporal variation of vegetation coverage and its response to climate change in North China plain in the last 33 years. Int. J. Appl. Earth Obs. Geoinf. 53, 103–117 (2016).

    Google Scholar 

  46. Huang, K. et al. The influences of climate change and human activities on vegetation dynamics in the Qinghai-Tibet Plateau. Remote Sens. 8, 876 (2016).

    Google Scholar 

  47. Zhang, Y., Fan, X., Wang, M. & Sun, L. Spatiotemporal Variations of Vegetation Coverage and Its Relationships with Climate Factors in Chifeng City. J. Inner Mongolia Normal Univ. (Nat. Sci. Ed.). 53, 471–477 (2024).

    Google Scholar 

  48. Tao, J., Zhang, J., Guo, J., Wang, J., Xue, H. Spatiotemporal change and driving factors of water conservation in Sanjiangyuan National Park. Acta Ecologica Sinica.

  49. Zheng, J. Inversion of Soil Organic Matter in Taihang MountainsBased on Hyperspectral Remote Sensing. 硕士, (2022).

  50. Ding, Y., Li, Z. & Peng, S. Global analysis of time-lag and -accumulation effects of climate on vegetation growth. Int. J. Appl. Earth Obs. Geoinf. 92, 102179-102179. https://doi.org/10.1016/j.jag.2020.102179 (2020).

    Google Scholar 

  51. Peng, J., Wu, C., Zhang, X., Wang, X. & Gonsamo, A. Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere. Glob. Chang. Biol. 25, 2174–2188. https://doi.org/10.1111/gcb.14627 (2019).

    Google Scholar 

  52. Xu, H., Zhao, C. & Wang, X. Spatiotemporal differentiation of the terrestrial gross primary production response to climate constraints in a dryland mountain ecosystem of northwestern China. Agric. For. Meteorol. 276–277, 107628 (2019).

    Google Scholar 

  53. Li, L. et al. Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai-Tibet Plateau. Sci. Total Environ. 678, 21–29 (2019).

    Google Scholar 

  54. Bala, G. et al. Combined climate and carbon-cycle effects of large-scale deforestation. Proc. Natl. Acad. Sci. U. S. A. 104, 6550–6555. https://doi.org/10.1073/pnas.0608998104 (2007).

    Google Scholar 

  55. Malhi, Y. et al. Climate change, deforestation, and the fate of the Amazon. Science 319, 169–172. https://doi.org/10.1126/science.1146961 (2008).

    Google Scholar 

  56. Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755. https://doi.org/10.1038/nature11688 (2012).

    Google Scholar 

  57. Sterling, S. M., Ducharne, A. & Polcher, J. The impact of global land-cover change on the terrestrial water cycle. Nat. Clim. Chang. 3, 385–390. https://doi.org/10.1038/nclimate1690 (2013).

    Google Scholar 

  58. Paulo, M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl. Acad. Sci. https://doi.org/10.1073/pnas.1305499111 (2014).

    Google Scholar 

  59. Zhang, Y., Liang, S. Changes in forest biomass and linkage to climate and forest disturbances over Northeastern China. Glob. Ch. Biol..

  60. Bryan, B. A. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193–204. https://doi.org/10.1038/s41586-018-0280-2 (2018).

    Google Scholar 

  61. Jiang, L., Jiapaer, G., Bao, A., Guo, H. & Ndayisaba, F. Vegetation dynamics and responses to climate change and human activities in Central Asia. Sci. Total Environ. 599, 967–980 (2017).

    Google Scholar 

  62. Sun, B. et al. Identification and assessment of the factors driving vegetation degradation/regeneration in drylands using synthetic high spatiotemporal remote sensing data—A case study in Zhenglanqi, Inner Mongolia, China. Ecol. Indic. 107, 105614 (2019).

    Google Scholar 

  63. Liu, L., Meng, W., Cai, C., Li, Y., Yuan, Y., Wang, X., Zhang, X., Hou, X. Analysis of Spatio-temporal dynamics and driving forceof vegetation cover in Fujian Province section of TingjiangRiver basin based on geographical detector. Bull. Soiland Water Conserv. 44, 236–246,382.

Download references

Acknowledgements

The authors would like to thank the Editors and the anonymous reviewers for their crucial comments, which improved the quality of this paper.

Funding

The project was supported by the Natural Science Foundation of Shandong province of China (ZR2021MD110).

Author information

Authors and Affiliations

  1. School of Geography and Environment, Liaocheng University, Liaocheng, 252000, China

    Xinying Lu, Yan Xiao, Yifang Duan & Nianci Duan

  2. School of Ecology and Environment, Tibet University, Lhasa, 850000, China

    Yan Xiao

Authors
  1. Xinying Lu
    View author publications

    Search author on:PubMed Google Scholar

  2. Yan Xiao
    View author publications

    Search author on:PubMed Google Scholar

  3. Yifang Duan
    View author publications

    Search author on:PubMed Google Scholar

  4. Nianci Duan
    View author publications

    Search author on:PubMed Google Scholar

Contributions

X.L., conceptualization, methodology, writing—original draft; Y.X., conceptualization, supervision; Y.D., writing—review and editing, investigation; N.D., software; visualization; All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Yan Xiao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, X., Xiao, Y., Duan, Y. et al. Identifying time-lag effects of temperature and precipitation on vegetation growth variation in the lower Yellow River of east China. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41853-0

Download citation

  • Received: 21 December 2024

  • Accepted: 23 February 2026

  • Published: 07 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-41853-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • The lower Yellow River
  • MODIS NDVI
  • Vegetation type
  • Climate change
  • Time-lagged effect
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Anthropocene