IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v291y2024ics0378377423004900.html
   My bibliography  Save this article

Response of vegetation to SPI and driving factors in Chinese mainland

Author

Listed:
  • Zhang, Siyao
  • Li, Jianzhu
  • Zhang, Ting
  • Feng, Ping
  • Liu, Weilin

Abstract

Considering the sensitivity and vulnerability of vegetation to precipitation changes, exploring the response of vegetation to standardized precipitation index (SPI) is essential for ecosystem stability. Based on observed data from 624 stations and Moderate Resolution Imaging Spectroradiometer (MODIS) dataset from 2000 to 2018, Spearman's rank correlation coefficient (rs) of SPI and vegetation condition index (VCI) in Chinese mainland was analysed, response time of vegetation to SPI was investigated, and random forest models were constructed to explore the drivers of vegetation response. The results revealed that: (1) SPI and VCI exhibit a loop distribution. The correlation between VCI and 1-month SPI is mostly positive, accounting for 77.58% of the total; rs shows an increasing-decreasing distribution pattern, and the response time of VCI to 1-month SPI indicates an overall decreasing-increasing-decreasing trend. (2) Precipitation, temperature, altitude, vegetation, land use, landform and soil types all have influence on the correlation between 1-month SPI and VCI. Under various factors, rs is concentrated in the range of -0.1 ∼ 0.2, and the response time of VCI to SPI under various factors primarily falls into the ranges of 0 ∼ 1 month and 6 ∼ 9 months. Meanwhile, rs generally decreases with the increasing latitude, ranging between -0.1 and 0.2, whereas the mean response time increases with latitude, within a 0 ∼ 6 months range. (3) Precipitation, temperature and altitude are the top three important factors that affect both maximum rs of VCI and 1-month SPI and response time of VCI to 1-month SPI. The rs is positive in areas with low precipitation, high temperature and low altitude, whereas response time is generally long in areas with low precipitation, low temperature and high altitude. This study is significant for better understanding the interactions between vegetation and SPI changes, and provides reference for vegetation irrigation and vegetation management.

Suggested Citation

  • Zhang, Siyao & Li, Jianzhu & Zhang, Ting & Feng, Ping & Liu, Weilin, 2024. "Response of vegetation to SPI and driving factors in Chinese mainland," Agricultural Water Management, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:agiwat:v:291:y:2024:i:c:s0378377423004900
    DOI: 10.1016/j.agwat.2023.108625
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377423004900
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2023.108625?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xu, Zhenheng & Sun, Hao & Zhang, Tian & Xu, Huanyu & Wu, Dan & Gao, JinHua, 2023. "Evaluating established deep learning methods in constructing integrated remote sensing drought index: A case study in China," Agricultural Water Management, Elsevier, vol. 286(C).
    2. Zhou, Keke & Li, Jianzhu & Zhang, Ting & Kang, Aiqing, 2021. "The use of combined soil moisture data to characterize agricultural drought conditions and the relationship among different drought types in China," Agricultural Water Management, Elsevier, vol. 243(C).
    3. Cao, Meng & Chen, Min & Liu, Ji & Liu, Yanli, 2022. "Assessing the performance of satellite soil moisture on agricultural drought monitoring in the North China Plain," Agricultural Water Management, Elsevier, vol. 263(C).
    4. Cheng, Minghan & Li, Binbin & Jiao, Xiyun & Huang, Xiao & Fan, Haiyan & Lin, Rencai & Liu, Kaihua, 2022. "Using multimodal remote sensing data to estimate regional-scale soil moisture content: A case study of Beijing, China," Agricultural Water Management, Elsevier, vol. 260(C).
    5. Chen, Xinguo & Li, Yi & Yao, Ning & Liu, De Li & Javed, Tehseen & Liu, Chuncheng & Liu, Fenggui, 2020. "Impacts of multi-timescale SPEI and SMDI variations on winter wheat yields," Agricultural Systems, Elsevier, vol. 185(C).
    6. Hodges, Blade & Tagert, Mary Love & Paz, Joel O. & Meng, Qingmin, 2023. "Assessing in-field soil moisture variability in the active root zone using granular matrix sensors," Agricultural Water Management, Elsevier, vol. 282(C).
    7. Xinxia Liu & Zhixiu Tian & Anbing Zhang & Anzhou Zhao & Haixin Liu, 2019. "Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China," Sustainability, MDPI, vol. 11(3), pages 1-22, February.
    8. Dong He & Xianglin Huang & Qingjiu Tian & Zhichao Zhang, 2020. "Changes in Vegetation Growth Dynamics and Relations with Climate in Inner Mongolia under More Strict Multiple Pre-Processing (2000–2018)," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Cong & Li, Kaiwei & Zhang, Jiquan & Guga, Suri & Wang, Rui & Liu, Xingpeng & Tong, Zhijun, 2023. "Dynamic risk assessment of waterlogging disaster to spring peanut (Arachis hypogaea L.) in Henan Province, China," Agricultural Water Management, Elsevier, vol. 277(C).
    2. Chhanda Ruj & Aloke Majumdar & Somnath Ghosal, 2022. "Political ecology and hydrosocial relation: a study on drought and associated migration in a semi-arid district of West Bengal, India," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 709-734, December.
    3. Tailin Li & Massimiliano Schiavo & David Zumr, . "Seasonal variations of vegetative indices and their correlation with evapotranspiration and soil water storage in a small agricultural catchment," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 0.
    4. Li, Na & Li, Yi & Yang, Qiliang & Biswas, Asim & Dong, Hezhong, 2024. "Simulating climate change impacts on cotton using AquaCrop model in China," Agricultural Systems, Elsevier, vol. 216(C).
    5. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Hao, Fanghua, 2022. "Changes and driving factors of compound agricultural droughts and hot events in eastern China," Agricultural Water Management, Elsevier, vol. 263(C).
    6. Zhang, Ziya & Li, Yi & Chen, Xinguo & Wang, Yanzi & Niu, Ben & Liu, De Li & He, Jianqiang & Pulatov, Bakhtiyor & Hassan, Ishtiaq & Meng, Qingtao, 2023. "Impact of climate change and planting date shifts on growth and yields of double cropping rice in southeastern China in future," Agricultural Systems, Elsevier, vol. 205(C).
    7. Cui, Yi & Zhou, Yuliang & Jin, Juliang & Jiang, Shangming & Wu, Chengguo & Ning, Shaowei, 2023. "Spatiotemporal characteristics and obstacle factors identification of agricultural drought disaster risk: A case study across Anhui Province, China," Agricultural Water Management, Elsevier, vol. 289(C).
    8. Yang, Cuiping & Liu, Changhong & Liu, Yanxin & Gao, Yunhe & Xing, Xuguang & Ma, Xiaoyi, 2024. "Prediction of drought trigger thresholds for future winter wheat yield losses in China based on the DSSAT-CERES-Wheat model and Copula conditional probabilities," Agricultural Water Management, Elsevier, vol. 299(C).
    9. Zhichao Xue & Martin Kappas & Daniel Wyss, 2021. "Spatio-Temporal Grassland Development in Inner Mongolia after Implementation of the First Comprehensive Nation-Wide Grassland Conservation Program," Land, MDPI, vol. 10(1), pages 1-16, January.
    10. Yao, Ning & Li, Yi & Liu, Qingzhu & Zhang, Siyuan & Chen, Xinguo & Ji, Yadong & Liu, Fenggui & Pulatov, Alim & Feng, Puyu, 2022. "Response of wheat and maize growth-yields to meteorological and agricultural droughts based on standardized precipitation evapotranspiration indexes and soil moisture deficit indexes," Agricultural Water Management, Elsevier, vol. 266(C).
    11. Zhangxin Liu & Haoran Ju & Qiyun Ma & Chengming Sun & Yuping Lv & Kaihua Liu & Tianao Wu & Minghan Cheng, 2024. "Rice Yield Estimation Using Multi-Temporal Remote Sensing Data and Machine Learning: A Case Study of Jiangsu, China," Agriculture, MDPI, vol. 14(4), pages 1-15, April.
    12. Li, Yifei & Huang, Shengzhi & Wang, Hanye & Zheng, Xudong & Huang, Qiang & Deng, Mingjiang & Peng, Jian, 2022. "High-resolution propagation time from meteorological to agricultural drought at multiple levels and spatiotemporal scales," Agricultural Water Management, Elsevier, vol. 262(C).
    13. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).
    14. Yanqin Xu & Shuai Han & Chunxiang Shi & Rui Tao & Jiaojiao Zhang & Yu Zhang & Zheng Wang, 2023. "Comparative Analysis of Three Near-Surface Air Temperature Reanalysis Datasets in Inner Mongolia Region," Sustainability, MDPI, vol. 15(17), pages 1-21, August.
    15. Dang, Yongcai & Qin, Lijie & Huang, Lirong & Wang, Jianqin & Li, Bo & He, Hongshi, 2022. "Water footprint of rain-fed maize in different growth stages and associated climatic driving forces in Northeast China," Agricultural Water Management, Elsevier, vol. 263(C).
    16. Cheng, Minghan & Jiao, Xiyun & Liu, Yadong & Shao, Mingchao & Yu, Xun & Bai, Yi & Wang, Zixu & Wang, Siyu & Tuohuti, Nuremanguli & Liu, Shuaibing & Shi, Lei & Yin, Dameng & Huang, Xiao & Nie, Chenwei , 2022. "Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning," Agricultural Water Management, Elsevier, vol. 264(C).
    17. Huaijun Wang & Zhi Li & Lei Cao & Ru Feng & Yingping Pan, 2021. "Response of NDVI of Natural Vegetation to Climate Changes and Drought in China," Land, MDPI, vol. 10(9), pages 1-24, September.
    18. Zhifang Pei & Shibo Fang & Wunian Yang & Lei Wang & Mingyan Wu & Qifei Zhang & Wei Han & Dao Nguyen Khoi, 2019. "The Relationship between NDVI and Climate Factors at Different Monthly Time Scales: A Case Study of Grasslands in Inner Mongolia, China (1982–2015)," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    19. Ma, Chunfeng & Johansen, Kasper & McCabe, Matthew F., 2022. "Combining Sentinel-2 data with an optical-trapezoid approach to infer within-field soil moisture variability and monitor agricultural production stages," Agricultural Water Management, Elsevier, vol. 274(C).
    20. Fengzhu Wang & Jizhong Wang & Yuxi Ji & Bo Zhao & Yangchun Liu & Hanlu Jiang & Wenhua Mao, 2023. "Research on the Measurement Method of Feeding Rate in Silage Harvester Based on Components Power Data," Agriculture, MDPI, vol. 13(2), pages 1-15, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:291:y:2024:i:c:s0378377423004900. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.