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  • 标题:Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle
  • 本地全文:下载
  • 作者:Juhua Ding ; Qiuan Zhu ; Hanwei Li
  • 期刊名称:Land
  • 印刷版ISSN:2073-445X
  • 出版年度:2022
  • 卷号:11
  • 期号:6
  • 页码:778
  • DOI:10.3390/land11060778
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:Phosphorus (P) is a key and a limiting nutrient in ecosystems and plays an important role in many physiological and biochemical processes, affecting both terrestrial ecosystem productivity and soil carbon storage. However, only a few global land surface models have incorporated P cycle and used to investigate the interactions of C-N-P and its limitation on terrestrial ecosystems. The overall objective of this study was to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. In this study, key processes of the P cycle, including P pool sizes and fluxes in plant, litter, and soil were integrated into a new model framework, TRIPLEX-CNP. We also added dynamic P:C ratios for different ecosystems. Based on sensitivity analysis results, we identified the phosphorus resorption coefficient of leaf (rpleaf) as the most influential parameter to gross primary productivity (GPP) and biomass, and determined optimal coefficients for different plant functional types (PFTs). TRIPLEX-CNP was calibrated with 49 sites and validated against 116 sites across eight biomes globally. The results suggested that TRIPLEX-CNP performed well on simulating the global GPP and soil organic carbon (SOC) with respective R2 values of 0.85 and 0.78 (both p < 0.01) between simulated and observed values. The R2 of simulation and observation of total biomass are 0.67 (p < 0.01) by TRIPLEX-CNP. The overall model performance had been improved in global GPP, total biomass and SOC after adding the P cycle comparing with the earlier version. Our work represents the promising step toward new coupled ecosystem process models for improving the quantifications of land carbon cycle and reducing uncertainty.
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