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  • Title: Spatio-temporal dynamics of net primary productivity and the economic value of Spartina alterniflora in the coastal regions of China.
    Author: Wei S, Zhu Z, Wang S.
    Journal: Sci Total Environ; 2024 Nov 25; 953():176099. PubMed ID: 39260496.
    Abstract:
    This study employs an improved Carnegie-Ames-Stanford Approach (CASA) model to calculate the Net Primary Productivity (NPP) of Spartina alterniflora (SA) and various other land use/land cover types (LULC) across coastal China over multiple years. The research aims to provide significant theoretical and practical insights into carbon sink research in coastal zones, sustainable development, and resource management. Key findings include identifying the first εmax value of 2.219 g C/MJ for SA, addressing a critical data gap in CASA modeling research on invasive plants. SA's NPP exhibited higher values in Shanghai and Zhejiang due to factors such as genetic diversity, invasion duration, and tidal dynamics. In contrast, other LULC exhibited higher NPP values in southern and inland regions, characterized by greater vegetation cover and favorable growing conditions. In 2020, SA and other LULC sequestered 16.352 kt C and 0.821*106 kt C, respectively. From 2000 to 2020, the average annual NPP and total carbon storage of SA and other LULC increased significantly, primarily driven by Shanghai and deciduous needleleaf forests, respectively. Seasonal NPP trends followed summer> spring> autumn> winter, influenced by climate conditions and plant life activities. Economic assessments in 2020 estimated SA's carbon storage value at RMB0.409 billion (Market Value method) or RMB5.562 billion (Carbon Tax method), with RMB2.054 billion attributed to oxygen release values, underscoring its economic and ecological potential. Among other LULC, evergreen broadleaf forests showed the highest carbon storage value (RMB183.463 billion). The study emphasizes the critical role of all LULC in carbon storage and oxygen release, advocating for targeted conservation and land management strategies. It suggests that managing SA should balance stringent control in high-risk areas, lenient measures in low-risk areas, eradication of scattered populations, and maximizing ecological benefits in retention areas, with continuous monitoring and adaptive management strategies to balance conservation and development efforts.
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