## 5 Discussion
### Model Limitations, Uncertainty, Improvement, and Outlook  
Current C-N-P models exhibit large uncertainties in their estimates of pool sizes, fluxes, and turnover rates of nutrients due to a lack of consistent global observations on P mineralization, sorption, limitation, and the stoichiometric relationships of P with C and N. Fewer data exist on the P cycle than on C and N processes, in part due to the large spatial heterogeneities of the P cycle across terrestrial ecosystems. For example, many studies have analyzed N limitation, but not P limitation, in temperate and high-latitude ecosystems [110; 111]. Recently, studies have begun to examine P cycling and its interactions with C and N, such as the FACE experiment in an Amazon forest in Brazil [112] as well as a soil and understory forest warming experiment in Puerto Rico. Available online: [[http://www.forestwarming.org](http://www.forestwarming.org)]([http://www.forestwarming.org](http://www.forestwarming.org)) (accessed on 21 May 2022). In addition, the evaluation of the CNP model is also a great challenge. Since we are still lacking of key variable to validate the phosphorus cycle, and leaf C:P ratios. Although we have tried to eliminate the inconsistency caused by the scaling problem when processing the observed data, there is still a lot of uncertainty. Similarly, GPP, biomass and SOC observed data all have some errors due to poor quality or accuracy. There is also a global-scale project, Imbalance-P, focused on improving our understanding of P limitation. Available online: [[http://imbalancep-erc.creal.cat/](http://imbalancep-erc.creal.cat/)]([http://imbalancep-erc.creal.cat/](http://imbalancep-erc.creal.cat/)) (accessed on 21 May 2022). These projects will expand the database on the P cycle in regional and global networks, improving our ability to develop and validate more informative ecosystem models at multi-scales [113]. These efforts are all the more important given the recent realization that P limitation occurs not only in lowland tropical forest regions as traditionally thought [6; 7; 10], but also in other ecosystems [113; 114], including tundra regions [11; 12] and temperate region areas with strongly weathered soils [13; 14]. Our work here with TRIPLEX-CNP demonstrates the feasibility and usefulness of incorporating the P cycle into global land surface models [52; 54; 56; 57; 69]. For the model uncertainty, the observations of GPP used in this article were estimated from the FLUXNET data. However, this dataset can also be obtained through a series of processing, the data may have uncertainty caused by processing methods. For the SOC, in order to verify the consistency, we used the same point as the GPP coordinate, but the FLUXNET did not provide SOC data, and it is difficult for us to collect the corresponding single point data globally, so we used the HWSD SOC data for verification, this may also cause the uncertainty due to the data source. In addition to the uncertainty caused by the data, the low level of understanding of the phosphorus cycles processes (mineralization, sedimentation, microbial processes, etc.) also brings uncertainty to the model simulations. For the development of the model, there is still much work to be carried out, such as the assignments of P fraction to P pools are not consistent and often mix definitions by availability and speciation [115; 116]. The questino concerning how nutrients reallocation will be affected by phosphorus availability is still unclear [117]. In addition, the microbial process that affects the absorption of nutrients by vegetation is another bottleneck, since soil microbes release immobile forms of P to the soil solution and are also responsible for the immobilization of P [118], especially they are close to mycorrhizal fungi [119]. Further progress along this path will require improvements in the parameterization of the P cycle based on P mineralization, sorption, limitation, and stoichiometry.