## 5 Conclusions
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/atmos14061046/s1](https://www.mdpi.com/article/10.3390/atmos14061046/s1)]([https://www.mdpi.com/article/10.3390/atmos14061046/s1](https://www.mdpi.com/article/10.3390/atmos14061046/s1)), Figure S1: Scatter plot of calculated versus measured monthly sums of GPP in Qianyanzhou subtropical coiferous plantation under atmospheric conditions S/Q \(\geq\) 0.5, using the 3-factor (left) and 2-factor (right) EMGPP models; Figure S2: Observed and calculated monthly sums of GPP using the 3-factor and 2-factor EMGPP models (GPP\({}_{\text{obs}}\), GPP\({}_{\text{cal\,3F}}\) and GPP\({}_{\text{cal\,2F}}\), respectively) with error bars showing 2 times standard deviations of the observed GPPs during 2013-2016 (S/Q = 0-1); Figure S3: Scatter plot of calculated versus measured monthly sums of GPP in Qianyanzhou subtropical coniferous plantation under all-sky conditions (S/Q = 0-1), using the 3-factor (left) and 2-factor (right) EMGPP models; Figure S4: GPP change rates (%) with the change in one factor and other factors kept at their original levels under realistic atmospheric conditions. a and b represent the change rates that respond to each influencing factor for S/Q! 0.5 and S/Q \(\geq\) 0.5, respectively; Figure S5: Linear (left) and nonlinear (right) relationships between BVOCs/NEE and latitude for the forests. The lines are linear and nonlinear fits to the data for BVOCs/NEE and latitude; Figure S6; Table S1: Same as Table 9 but for annual sums of GPP simulations (mg CO\({}_{2}\) m\({}^{-2}\)) (S/Q \(\geq\) 0.5); Table S2: Same as Table 7 and for hourly GPP (mg CO\({}_{2}\) m\({}^{-2}\)) simulations (S/Q = 0-1) using a 3-factor model; Table S3: Same as Table S2 and for hourly GPP (mg CO\({}_{2}\) m\({}^{-2}\)) simulations (S/Q = 0-1) using a 2-factor model; Table S4: Same as Table 9 and for simulations of monthly sums of GPP (mg CO\({}_{2}\) m\({}^{-2}\)) (S/Q = 0-1); Table S5: Same as Table 9 but for annual sums of GPP simulations (mg CO\({}_{2}\) m\({}^{-2}\)) (S/Q = 0-1); Table S6: GPP change rates (%) for S/Q! 0.5 and S/Q \(\geq\) 0.5 due to the change of one factor (%), while keeping all other factors at their original value. The averages of PAR, E, S/Q and air temperature (PAR\({}_{\text{avg}}\), E\({}_{\text{avg}}\), (S/Q)\({}_{\text{avg}}\), T\({}_{\text{avg}}\)) in different time periods for S/Q! 0.5 and S/Q \(\geq\) 0.5 are also given; Table S7: Isoprene and monoterepne emission changing rates (Iso REA and MT REA, %) for using relaxed eddy accumulation technique (REA) caused by the change of one factor (%), while keeping all other factors at their original value [27]. Conceptualization, J.B.; Methodology, J.B.; Data curation, F.Y., H.W. and M.X. ; Writing--original draft, J.B.; Writing--review & editing, F.Y., H.W. and M.X. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the National Key R&D Program grant number [No. 2021 YFE0118000], ESA-MOST China Dragon Cooperation, Dragon 4 and 5 projects grant number [ID 32771, ID 59013] and National Natural Science Foundation of China grant number [No. 41275137]. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The datasets [GENERATED/ANALYZED] for this study can be found in a Big Earth Data Platform for Three Poles, [[http://poles.tpdc.ac.cn/zh-hans/](http://poles.tpdc.ac.cn/zh-hans/)]([http://poles.tpdc.ac.cn/zh-hans/](http://poles.tpdc.ac.cn/zh-hans/)), accessed on 1 May 2023. **Acknowledgments:** The authors thank all reviewers for their beneficial comments and suggestions, which contributed to the improvement of the manuscript.