Spatiotemporal patterns of winter wheat carbon sinks in the North China plain simulated by an improved VPRM with phenology-based parameterization during 2002–2021
Understanding the spatiotemporal dynamics of carbon fluxes in agricultural regions is crucial for ensuring food security and achieving carbon neutrality. This study developed an improved Vegetation Photosynthesis and Respiration Model (VPRM) by integrating the more detailed Remote Sensing Model for Re (ReRSM) for ecosystem respiration simulation and implementing phenology-based parameterization through precise growth stage division. The improved VPRM model was applied to simulate the net ecosystem productivity (NEP) of winter wheat in the North China Plain (NCP) from 2002 to 2021. Validation against flux observations from three NCP sites demonstrated significantly improved performance, with R 2 increasing from 0.72 to 0.82 and RMSE decreasing from 2.08 to 1.50 gC m −2 d −1 compared to the original VPRM. Our findings indicate that the NCP winter wheat ecosystem sustained its function as a carbon sink over the 20-year study period, with a multi-year mean NEP of 438.97 ± 88.64 gC m −2 per growing season. Spatially, the carbon sequestration capacity displayed marked regional differences, showing stronger sink intensity in southeastern areas relative to northern and peripheral regions. Temporally, the NEP exhibited a statistically significant increasing trend throughout the study period, with interannual variations ranging between 270.87 and 613.92 gC m −2 across seasons. This enhancement of carbon sequestration appears to be driven by climate warming effects combined with the extensive implementation of well-facilitated farmland infrastructure. This research provides a robust methodological framework for accurately quantifying cropland carbon fluxes and offers scientific support for developing targeted agricultural management strategies to enhance carbon sinks in major grain production regions.
Authors
- Zhongyi Sun (ORCID: https://orcid.org/0000-0002-5099-5363)
- Fadong Li (ORCID: https://orcid.org/0000-0002-6930-3419)
- Decheng Zhou (ORCID: https://orcid.org/0000-0003-0947-0853)
- Yunfeng Qiao
- Xiaonan Guo (ORCID: https://orcid.org/0000-0003-3374-6944)
- Guowei Zhong
- Yucui Zhang (ORCID: https://orcid.org/0000-0003-3659-9142)
- Chuan Jin
- Siyuan Zhou
- Shuai Hao
- Li Zhou
- Liangxia Zhang
- Zhongmin Hu
- Jinjian Geng
Institutions
- Inner Mongolia Agricultural University (CN)
- China Meteorological Administration (CN)
- Hainan University (CN)
- Institute of Genetics and Developmental Biology (CN)
- Chinese Academy of Meteorological Sciences (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
Publication Details
- Journal
- Ecological Indicators
- Published
- 2026-08-27
- DOI
- https://doi.org/10.1016/j.ecolind.2026.115365
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China