## 5 Discussion  
### Comparison with Previous Studies  
Forest carbon sinks exhibit distinct seasonal variations, with notable differences in carbon sequestration between the growing and non-growing seasons [48]. [PERSON] [29] estimated that respiration values for the dominant forest types (Pinus tabuliformis and Quercus aliena) in the Huoditang forest area of the Qinba Mountain region account for approximately 75% of the annual total, while the GPP during the growing season in the Huoditang forest area accounts for about 59% of the annual total (as shown in Table 9). From this, it can be inferred that the ecological carbon sinks during the growing season contributes roughly 67% of the annual ecological carbon sinks. Based on the results of this study, the estimated annual average carbon sinks value for the Qinba Mountain forest area from 2011 to 2018 is approximately 36.581 TgC/year, derived from the growing season carbon sinks values. By scaling the annual average carbon sinks values from other studies to the area proportion of the Qinba Mountain forest region and comparing these with the remote sensing carbon sinks inversion results obtained in this study (as shown in Table 10), it is evident that the results of this study are comparatively higher than those from previous studies. The variability in forest carbon sinks estimations can be attributed to the diverse methods employed across different studies. These methods include integrated analysis approaches [49], stock change methods, flux methods [50], and tree growth modeling techniques [51], each relying on distinct data sources. The inherent differences in these methods can introduce various errors and limitations. For example, the stock change method requires a comprehensive national forest inventory system and is primarily applicable to boreal and temperate forests; the flux method may not fully capture carbon stock changes due to land use changes; and tree growth modeling is influenced by factors such as model selection, sample size, and natural disturbances in forests. The choice of method and data source can result in significant differences in forest carbon sinks predictions across studies. These discrepancies stem from several factors, including the mechanisms emphasized by different models, the resolution and accuracy of data sources, the complexity and applicability of the models, and the simplification methods applied in each study. \begin{table}
\begin{tabular}{c c} \hline \hline
**Typical Literature** & **Annual Carbon Sinks Estimate (TgC\(\cdot\)a\({}^{-1}\))** \\ \hline Spatiotemporal dynamics of forest carbon sinks in China’s Qinba & \\ mountains: Insights from sun-induced chlorophyll fluorescence remote & 36.58 \\ sensing (this research) & \\ The current and potential carbon carbon & 19.53 \\ sink in forest ecosystems in China [49] & 14.88 \\ The enduring world forest carbon sink [50] & 21.92 \\ Forest carbon storage and sink estimates under different management & 21.80 \\ scenarios in China from 2020 to 2100 [51] & \\ Projections of China’s forest carbon storage and sequestration and & 21.80 \\ ways of their potential capacity enhancement [52] & 21.80 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparison of carbon sinks estimation results for Qinba Mountain forests with those from key literature sources. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Growing Season GPP** & **Annual GPP** & **Growing Season GPP** \\
**(gCm\({}^{-2}\) mon\({}^{-1}\))** & **(gCm\({}^{-2}\) mon\({}^{-1}\))** & **Proportion** \\ \hline
431.59 & 725.55 & 59.5\% \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Proportion of growing season GPP to total annual GPP. The higher results of this study compared to others may also stem from the fact that the linear correlation between SIF and GPP can vary significantly under different conditions, such as vegetation types [53], incident radiation, temperature, evaporative components [21], and seasons [54]. These variations can introduce errors when a simple linear model is used to relate SIF and GPP.