Estimating the dynamics and driving factors of gross primary productivity over the Chinese Loess Plateau by the modified vegetation photosynthesis model
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引用次数: 0
Abstract
Gross primary productivity (GPP) is a key parameter in research on the global carbon cycle and changes. Understanding the spatiotemporal dynamics and influencing factors of GPP on the Loess Plateau (LP) helps identify the health status of ecosystems, thereby enabling the implementation of effective conservation and restoration measures. In this study, we used a modified vegetation photosynthesis model (VPM) to simulate a long-term series of GPP in the LP from 2001 to 2022, and the impacts of different land-use patterns and meteorological factors on GPP were investigated using a transition matrix, linear regression, and partial correlation analyses. The findings suggested that the modified simulation yielded a more reliable performance (coefficient of determination (R2) = 0.89, root mean square error (RMSE) = 143.47 gC·m−2·yr−1) and was suitable for further research endeavors. (1) The GPP on the LP significantly increased by 232.65 TgC from 2001 to 2022. The southeastern region contributed more than the northwestern region, and the GPP exhibited higher multi-year averages and growth rates below 1000 m elevation. (2) Forests in the southeastern region of the LP, characterized by a heightened growth rate, will influence future spatial variations in GPP increases across the LP. Despite the decline in grassland and cultivated land areas, substantial land coverage has significantly contributed to the overall GPP growth. Urbanization encroaching on cultivated land has emerged as a key contributor to the decline in GPP in low-altitude regions. (3) Air temperature was the main physical driving force for GPP change in the LP. Additionally, the GPP in forested regions exhibited a negative correlation with rainfall, whereas the GPP in areas undergoing the return of cropland to forest–grassland and cropland reclamation correlated negatively with solar radiation. (4) The attribution analysis indicated that the surge in vegetation GPP on the LP was collectively driven by human activities and meteorological changes, with human activities dominating these changes by 61.41 %. This study deepens the understanding of terrestrial ecology in semi-humid regions and provides scientific insights for implementing ecological governance strategies in the LP.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.