Pre-Season Precipitation and Temperature Have a Larger Influence on Vegetation Productivity than That of the Growing Season in the Agro-Pastoral Ecotone in Northern China

Yuanyuan Zhang, Qingtao Wang (), Xueyuan Zhang, Zecheng Guo, Xiaonan Guo, Changhui Ma, Baocheng Wei and Lei He
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Yuanyuan Zhang: School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056000, China
Qingtao Wang: School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056000, China
Xueyuan Zhang: College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Zecheng Guo: Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730000, China
Xiaonan Guo: School of Land Science and Space Planning, Hebei International Joint Research Center for Remote Sensing of Agricultural Drought Monitoring, Hebei GEO University, Shijiazhuang 050031, China
Changhui Ma: State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Baocheng Wei: College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
Lei He: State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Agriculture, 2025, vol. 15, issue 2, 1-22

Abstract: Climate change and human activities are reshaping the structure and function of terrestrial ecosystems, particularly in vulnerable regions such as agro-pastoral ecotones. However, the extent to which climate change impacts vegetation growth in these areas remains poorly understood, largely due to the modifying effects of human-induced land cover changes on vegetation sensitivity to climatic variations. This study utilizes satellite-derived vegetation indices, land cover datasets, and climate data to investigate the influence of both land cover and climate changes on vegetation growth in the agro-pastoral ecotone of northern China (APENC) from 2001 to 2022. The results reveal that the sensitivity of vegetation productivity, as indicated by the kernel Normalized Difference Vegetation Index (kNDVI), varies depending on the land cover type to climate change in the APENC. Moreover, ridge regression modeling shows that pre-season climate conditions (i.e., pre-season precipitation and temperature) have a stronger positive impact on growing-season vegetation productivity than growing season precipitation and temperature, while the effect of vapor pressure deficit (VPD) is negative. Notably, the kNDVI exhibits significant positive sensitivity ( p < 0.05) to precipitation in 34.12% of the region and significant negative sensitivity ( p < 0.05) to VPD in 38.80%. The ridge regression model explained 89.10% of the total variation (R 2 = 0.891). These findings not only emphasize the critical role of both historical and contemporary climate conditions in shaping vegetation growth but also provide valuable insights into how to adjust agricultural and animal husbandry management strategies to improve regional climate adaptation based on climate information from previous seasons in fragile regions.

Keywords: vegetation productivity; climate change; land cover change; precipitation patterns; pre-season climate; APENC (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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