数字农科院2.0

Sensitivity of temperate vegetation to precipitation is higher in steppes than in deserts and forests

文献类型： 外文期刊

作者： Jia, Qi;Gao, Xiaotian;Jiang, Zhaolin;Li, Haoxin;Guo, Jingpeng;Lu, Xueyan;Li, Frank Yonghong

作者机构：

关键词： Vegetation sensitivity;Remote sensing;Trend analysis;Linear mixed-effects model;Random forest;Inner Mongolia;Ecosystems

期刊名称： ECOLOGICAL INDICATORS

ISSN： 1470-160X

年卷期： 2024 年 166 卷

页码：

收录情况： SCIE（2024版） ; ; EI（2024版）

摘要： Recognizing the sensitivity of vegetation to precipitation is fundamental to monitoring and assessing ecosystem health and predicting ecosystem response to climate change. However, there is a lack of detailed, large-scale assessment of the sensitivity of temperate vegetation to climate variability. We analyzed the spatiotemporal trends of NDVI in Inner Mongolia (IM) for the period from 2000 to 2020, evaluated the sensitivity of NDVI to precipitation by constructing a linear mixed-effects model, and assessed the relative importance of an array of biotic and abiotic factors in affecting the vegetation sensitivity to precipitation using random forest models. We found that (1) the NDVI in IM had a significant or slight increase in 80.86% of the region during the studied two decades, though it showed a large inter-annual fluctuation, and the areas with stable or decreasing NDVI were mainly in the desert areas. Precipitation and wind speed were the two major drivers for the NDVI changes. (2) The typical steppes demonstrated the highest sensitivity to precipitation, followed by desert steppes and forest steppes, broad-leaved forests, and deserts and coniferous forests. (3) The major factor affecting the vegetation sensitivity to precipitation varied with vegetation types; it is temperature in the coniferous forests, forest steppes and steppe deserts, but it is the sunshine hours in the deciduous broad-leaved forests, the typical steppes, and the desert steppes. The high sensitivity of the typical steppe vegetation to precipitation is related with its location on climate gradient, it has a high production potential but limited by precipitation under a semiarid climate. Our analysis deepens the understanding of the NDVI sensitivity to precipitation and its influencing factors in different vegetation regions, and is valuable for predicting vegetation changes and developing vegetation management strategies to adapt to climate changes.

分类号：

  • 相关文献

[1]Integration and Comparison of Multiple Two-Leaf Light Use Efficiency Models Across Global Flux Sites. Zhou, Haoqiang,Bao, Gang,Li, Fei,Chen, Jiquan,Tong, Siqin,Huang, Xiaojun,Guo, Enliang,Bao, Yuhai,Rina, Wendu. 2023

[2]Quantifying Grazing Intensity from Aboveground Biomass Differences Using Satellite Data and Machine Learning. Ritu Su,Yong Yang,Shujuan Chang,A. Gudamu,Xiangjun Yun,Xiangyang Song,Aijun Liu. 2025

[3]Comparing Machine Learning Algorithms for Pixel/Object-Based Classifications of Semi-Arid Grassland in Northern China Using Multisource Medium Resolution Imageries. Wu N.,Crusiol L.G.T.,Liu G.,Wuyun D.,Han G.. 2023

[4]Spatial-Temporal Characteristics and Driving Forces of Aboveground Biomass in Desert Steppes of Inner Mongolia, China in the Past 20 Years. Wu, Nitu,Liu, Guixiang,Wuyun, Deji,Yi, Bole,Du, Wala,Han, Guodong. 2023

[5]CatBoost Improves Inversion Accuracy of Plant Water Status in Winter Wheat Using Ratio Vegetation Index. Dong, Bingyan,Ma, Shouchen,Gao, Zhenhao,Qin, Anzhen. 2025

[6]Earthworms enhanced winter oilseed rape (Brassica napus L.) growth and nitrogen uptake. Zhang, Shujie,Chao, Ying,Zhang, Chunlei,Cheng, Jing,Li, Jun,Ma, Ni.

[7]The variability in sensitivity of vegetation greenness to climate change across Eurasia. Zhipeng Wang,Jianshuang Wu,Meng Li,Yanan Cao,Minyahel Tilahun,Ben Chen. 2024

[8]Dynamics of soil carbon to nitrogen ratio changes under long-term fertilizer addition in wheat-corn double cropping systems of China. Wang, X. J.,Cong, R. H.,Xu, M. G.,Zhang, W. J.,Xie, L. J.,Wang, B. R.,Cong, R. H.,Wang, X. J.,Huang, S. M..

[9]Will elevated CO2 enhance mineral bioavailability in wetland ecosystems? Evidence from a rice ecosystem. Zhang, Weijian,Guo, Jia,Guo, Jia,Zhang, Weijian,Zhang, Mingqian,Zhang, Li,Bian, Xinmin.

[10]Remote sensing of crop production in China by production efficiency models: models comparisons, estimates and uncertainties. Tao, FL,Yokozawa, M,Zhang, Z,Xu, YL,Hayashi, Y.

[11]An Analysis on Innovative Research Fronts for the Information-based Agriculture in China. Kong, Fan-tao,Zhang, Jian-hua,Han, Shu-qing,Wu, Jian-zhai. 2016

[12]Analysis of climate variability in the Manas River Valley, North-Western China (1956-2006). Zhang, Fenghua,Hua, Fan,Hanjra, Munir A.,Shu, Yunqiao,Hanjra, Munir A.,Hanjra, Munir A.,Li, Yuyi.

[13]Long-term variations of water quality and nutrient load inputs in a large shallow lake of Yellow River Basin: Implications for lake water quality improvements. Shengyue Yu,Xinzhong Du,Qiuliang Lei,Xue Wang,Shengcai Wu,Hongbin Liu. 2023

[14]The Dynamic Transcription Profiles of Proliferating Bovine Ovarian Granulosa When Exposed to Increased Levels of β-Hydroxybutyric Acid. Jianfei Gong,Shanjiang Zhao,Nuo Heng,Yi Wang,Zhihui Hu,Huan Wang,Huabin Zhu. 2022

[15]Synthesized remote sensing-based desertification index reveals ecological restoration and its driving forces in the northern sand-prevention belt of China. Ang Chen,Xiuchun Yang,Jian Guo,Xiaoyu Xing,Dong Yang,Bin Xu. 2021

[16]Multi-year trends and interannual variation in ecosystem resource use efficiencies in a young mixedwood plantation in northern China. Jin C.,Zha T.,Bourque C.P.-A.,Liu P.,Jia X.,Zhang F.,Yu H.,Tian Y.,Li X.,Kang X.,Guo X.,Wang N.. 2023

[17]The Spatiotemporal Dynamics of Vegetation Cover and Its Response to the Grain for Green Project in the Loess Plateau of China. Yinlan Huang,Yunxiang Jin,Shi Chen. 2024

[18]Global agricultural adaptation case database and trend analysis based on large language models. Zhong, Jing-Wen,Zhang, Xue-Yan,Ma, Xin. 2025

[19]Transfer Learning in Junction With a Light Use Efficiency Model for Estimating Grassland Gross Primary Production. Yu, Ruiyang,Yao, Yunjun,Tang, Qingxin,Zhang, Xueyi,Shao, Changliang,Fisher, Joshua B.,Chen, Jiquan,Zhang, Xiaotong,Li, Yufu,Xu, Jia,Liu, Lu,Xie, Zijing,Ning, Jing,Fan, Jiahui,Zhang, Luna. 2025

[20]Linking nutrient strategies with plant size along a grazing gradient: Evidence from Leymus chinensis in a natural pasture. Li Xi-liang,Liu Zhi-ying,Ren Wei-bo,Ding Yong,Ji Lei,Guo Feng-hui,Hou Xiang-yang. 2016

作者其他论文 更多>>