## 6 Conclusions  
This study had made a new attempt to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. This model accurately simulated GPP, total biomass, and SOC across large geographical ranges and different ecosystem types, based on a range of global datasets after determining and adjusting the most sensitive parameters (phosphorus resorption coefficient of leaf (rpleaf)). The model calibration and validation demonstrated that the TRIPLEX-CNP was able to simulate global GPP, total biomass, and SOC reasonably and the overall model performance had been improved after adding the P cycle comparing with the earlier version. Our results highlight the urgent need for observations and experiments on how climate change and elevated CO\({}_{2}\) affect the P cycle, and for global land surface models that more accurately represent P mineralization, sorption, partitioning, and stoichiometry, as well as C-N-P interactions. This study represents a promising approach to help predicting the P distribution and its effects on productivity of terrestrial ecosystem under phosphorus limitation and global climate change. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/land11060778/s1](https://www.mdpi.com/article/10.3390/land11060778/s1)]([https://www.mdpi.com/article/10.3390/land11060778/s1](https://www.mdpi.com/article/10.3390/land11060778/s1)), Table S1: Constants used to calculate the phosphorus cycle; Table S2: Percent change in GPP and in the amount of leaf phosphorus (pleaf) in response to changes in four meteorological factors, for different vegetation types; Table S3: Fitting of rpleaf at each site and for five biomes, and model performance for each biome (optimal parameter marked with #); Table S4: Data used to validate model simulation of gross primary productivity (GPP) and soil organic carbon (SOC); Table S5: Data on total biomass taken from global 933 sites and used to validate model performance. **Author Contributions:** Conceptualization, C.P. and Q.Z. ; methodology, J.D. and Q.Z. ; validation, J.D. and Q.Z. ; formal analysis, J.D. ; investigation, X.Z. ; resources, C.P. and Q.Z. ; data curation, Q.Z. and H.L. ; writing-original draft preparation, J.D. ; writing-review and editing, J.D., C.P., Q.Z., X.Z., H.L. and W.L. ; supervision, W.L. All authors have read and agreed to the published version of the manuscript. **Funding:** This study was funded by the National Key R&D Program of China (2016 YFC0500203) and a Natural Sciences and Engineering Research Council of Canada Discovery Grant. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Soil data were obtained from the FAO/UNESCO Soil Map of the World. Available online: [[http://www.fao.org/geonetmork/srv/en/metadata.show?id514116](http://www.fao.org/geonetmork/srv/en/metadata.show?id514116)]([http://www.fao.org/geonetmork/srv/en/metadata.show?id514116](http://www.fao.org/geonetmork/srv/en/metadata.show?id514116)) (accessed on 21 May 2022), and it was classified according to the Digital Soil Map of the World, conjoined to the FAO/UNESCO Soil Map of the World. Available online: [[http://www.fao.org/geonetmork/srv/en/metadata.show?id514116](http://www.fao.org/geonetmork/srv/en/metadata.show?id514116)]([http://www.fao.org/geonetmork/srv/en/metadata.show?id514116](http://www.fao.org/geonetmork/srv/en/metadata.show?id514116)) (accessed on 21 May 2022) Global soil dataset: IGBP-DIS. Available online: [[https://daac.ornl.gov/SOILS/guides/igbp.html](https://daac.ornl.gov/SOILS/guides/igbp.html)]([https://daac.ornl.gov/SOILS/guides/igbp.html](https://daac.ornl.gov/SOILS/guides/igbp.html)) (accessed on 21 May 2022). Topographic data were extracted from the global digital elevation model GTOPO30.