Spatiotemporal Dynamics of NEP and Its Influencing Factors: Exploring the Impact Mechanisms Under Extreme Climate Conditions

Current research on net ecosystem productivity (NEP) still lacks sufficient attention to the impacts of extreme climate events, particularly in understanding the interactive response mechanisms of carbon sinks under extreme climate conditions. This study investigated the spatiotemporal dynamics of NEP and its interactive mechanisms in Dongying, China, from 2001 to 2023 under extreme climate conditions. Using trend slope estimation, geographical detector, and XGBoost methods, we systematically revealed the responses of NEP to the factors including climatic changes, human activities, vegetation growth status, and topographic features. The results indicated that NEP exhibited an overall fluctuating yet increasing trend during 2001–2023. The normalized difference vegetation index (NDVI, for vegetation growth status) and the digital elevation model (DEM, for terrain features) were identified as the dominant factors influencing the spatial heterogeneity of NEP. However, extreme precipitation and high temperature events significantly diminished the positive contribution of the NDVI to NEP, while simultaneously amplifying the negative influence of the DEM on NEP. These two concurrent changes superimposed on each other, especially after 2017, further constrained the potential for carbon sequestration. Furthermore, a lag effect was observed in the response mechanisms of NEP to factors under the influence of precipitation and high-temperature climates. These findings highlight the critical and complex role of extreme climate in reorganizing the contributions of factors and intensifying pressure on the carbon sequestration capacity of ecosystems.

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Publication Details

Journal
Remote Sensing
Published
2025-11-03
DOI
https://doi.org/10.3390/rs17213633
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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article

Spatiotemporal Dynamics of NEP and Its Influencing Factors: Exploring the Impact Mechanisms Under Extreme Climate Conditions

Wei Chen, N. K. Huang, Peng Yu, Wanjuan Song et al.
1 citations
Remote Sensing
Remote Sensing in Agriculture
1.72
article

Spatiotemporal Dynamics of NEP and Its Influencing Factors: Exploring the Impact Mechanisms Under Extreme Climate Conditions

Wei Chen, N. K. Huang, Peng Yu, Wanjuan Song, Guoxu Li, Xin Zhang, Li Wang, Yuelin Zhang, Zheng Niu
article en
1 citations

Abstract

Current research on net ecosystem productivity (NEP) still lacks sufficient attention to the impacts of extreme climate events, particularly in understanding the interactive response mechanisms of carbon sinks under extreme climate conditions. This study investigated the spatiotemporal dynamics of NEP and its interactive mechanisms in Dongying, China, from 2001 to 2023 under extreme climate conditions. Using trend slope estimation, geographical detector, and XGBoost methods, we systematically revealed the responses of NEP to the factors including climatic changes, human activities, vegetation growth status, and topographic features. The results indicated that NEP exhibited an overall fluctuating yet increasing trend during 2001–2023. The normalized difference vegetation index (NDVI, for vegetation growth status) and the digital elevation model (DEM, for terrain features) were identified as the dominant factors influencing the spatial heterogeneity of NEP. However, extreme precipitation and high temperature events significantly diminished the positive contribution of the NDVI to NEP, while simultaneously amplifying the negative influence of the DEM on NEP. These two concurrent changes superimposed on each other, especially after 2017, further constrained the potential for carbon sequestration. Furthermore, a lag effect was observed in the response mechanisms of NEP to factors under the influence of precipitation and high-temperature climates. These findings highlight the critical and complex role of extreme climate in reorganizing the contributions of factors and intensifying pressure on the carbon sequestration capacity of ecosystems.

Remote SensingVol. 17(21)
Chinese Academy of Sciences (CN), University of Jinan (CN), Aerospace Information Research Institute (CN), University of Chinese Academy of Sciences (CN)
Chinese Academy of Sciences
Openalex Percentile: Top 13%
Remote Sensing in Agriculture
1.72
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