## 4 Discussion
### Uncertainty Analysis of Simulation Results  
Previous studies found that the annual carbon assimilations from swamp or peatland in the regions of Hing'an Mountains were mostly attributable to the uptakes during the growing seasons, particularly from June to August [53; 62; 68]. The net carbon assimilation by plants during the growing seasons was generally higher than the carbon emitted during the non-growing seasons [76]. Climate warming extends or alters the growing season [67], enhances the warmth of summer, and increases the carbon sink capacity of vegetation. However, it should be noted that it is still unknown whether the carbon released by the permafrost ecosystem and the carbon absorbed by summer plant growth can be completely offset. There may be more uncertainties in the process of the model prediction with the continuous change of climate in the future, as well as a series of problems such as the internal structure of the model and the uncertainty of key input parameters, which eventually affect the simulation results of carbon sources/sinks in ecosystems to some extent. For example, with climate change, the effect of fertilization driven by the increase in CO\({}_{2}\) concentration is also likely to increase the peatland carbon sink through increases in primary productivity. Recent field experiments suggest that permafrost thawing might promote deeper rooting of some plant species [77; 78] that attempt to exploit plant-available nutrients at the permafrost thaw front [79; 80].  
Soil has high spatial variability, slow change rate, and many processes affecting its decomposition rate. Therefore, variations in soil and its characteristics will lead to uncertainties because most C is stored in soil. In addition, if the water content remains unchanged and the vegetation changes, increased woody vegetation will promote C accumulation [81]. Increases in shrubs and trees have also been shown to increase the pools of phenolic compounds and decrease the loss of peat carbon to the atmosphere [82]. The additional rhizosphere effect also deserves further attention. A previous study suggested that additional rhizodeposition with climate warming will promote carbon decomposition [83]. Higher temperatures and reduced rainfall have negative effects on productivity by increasing evapotranspiration and decreasing soil moisture [84; 85; 86; 87].  
The different definitions of vegetation types between the initial input data and CoupModel could also introduce uncertainties in the model simulation. Research relying only on individual model simulations still have inherent limitations. However, the strength of this feedback is highly uncertain; indeed, it is now one of the largest uncertainties in future climate predictions [88]. In addition, because changes in the active layer of frozen soil affect the measurements, our simulation results contain some inevitable errors. Nevertheless, our results are expected to complement early detection of changes in the role of the peatland as a source or sink. In future efforts, we will attempt to reduce these errors as much as possible. Our model projections also did not incorporate all changes expected under future climates, such as changes in permafrost distribution, delayed seasonal freeze-up, increased fire frequency, landscape-level hydrologic changes, mycorrhizal type, and mycorrhizal dis  
Figure 9: Correlation diagram between simulation results and meteorological elements.  
tribution. Therefore, we hope that the above factors can be taken into account in subsequent applications.