Temporal and spatial dynamics of Net Primary Productivity and prediction of wetland carbon sequestration potential on the Tibetan Plateau

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🔬研究者:Provides a methodology combining BPNN and CASA for predicting NPP and carbon sequestration, useful for ecologists and climate modelers.

🏛政策担当者:Offers evidence for the importance of Tibetan Plateau wetlands as carbon sinks, relevant for national climate commitments and conservation planning.

Background Investigating the carbon sequestration potential of wetlands and the dynamics of net primary productivity (NPP) on the Tibetan Plateau of China enhances understanding of their contributions to global carbon emission reduction and their role in maintaining biodiversity and ecosystem stability. Vegetation NPP is a key indicator of carbon sequestration; however, existing research has largely focused on historical dynamics, with limited studies projecting future trends. This gap impedes proactive conservation and climate mitigation strategies. Methods Here, we predicted the spatial distribution of normalized difference vegetation index (NDVI) on the Tibetan Plateau for 2025–2030, employing a backpropagation neural network and Kriging interpolation fitting. We estimated spatial and temporal dynamics of NPP and wetland carbon sequestration potentials during the same period using the Carnegie-Ames-Stanford Approach model. Furthermore, we investigated the effects of land use and climate on NPP. Results Key findings were: (1) NDVI distribution was higher in the southeast than in the northwest, with temperature influencing its value. (2) Spatial distribution of NPP on the Tibetan Plateau exhibits a typical landscape pattern of “patch-corridor-matrix.” The maximum NPP of vegetation was 1,112.82 gC ⋅ m−2 ⋅ a−1 for 2025–2030. Projections of NPP for 2025–2030 suggest an increase of approximately 50% relative to current levels by 2045, indicating a substantial enhancement of the carbon sink potential over the coming two decades. (3) Carbon sequestration potential of wetlands on the Plateau ranges from 0 to 100 gC ⋅ m−2 ⋅ a−1, with high carbon sink potential concentrated near Palong Tsangpo, the largest tributary of the Yarlung Tsangpo River. (4) Woodland NPP has the highest mean value and rate of change. Furthermore, analysis of 2025 land use data shows that forestland and grassland are the dominant land cover types in the Yunnan, Sichuan, and Southeastern Xizang Sections of the Qinghai-Tibet Plateau. Their high proportions correspond significantly to high regional NDVI values, indicating the spatial heterogeneity of NDVI distribution is driven by land cover changes rather than directional factors. (5) Correlation analysis indicated strong positive correlations between precipitation and solar radiation with NPP. NPP does not increase or decrease with increasing temperature; instead, it tends to increase within suitable temperature ranges.

• semanticscholar https://doi.org/10.7717/peerj.20758first seen 2026-07-24 06:55:59