Methane (CH₄) is one of the three most important greenhouse gases. To date, observations of ecosystem-scale methane (CH₄) fluxes in forests are currently lacking in the global CH₄ budget. The environmental factors controlling CH₄ flux dynamics remain poorly understood at the ecosystem scale. In this study, we used a state-of-the-art eddy covariance technique to continuously measure the CH₄ flux from 2016 to 2018 in a subtropical forest of Zhejiang Province in China, quantify the annual CH₄ budget and investigate its control factors. We found that the total annual CH₄ budget was 1.15 ± 0.28~4.79 ± 0.49 g CH₄ m⁻² year⁻¹ for 2017–2018. The daily CH₄ flux reached an emission peak of 0.145 g m⁻² d⁻¹ during winter and an uptake peak of −0.142 g m⁻² d⁻¹ in summer. During the whole study period, the studied forest region acted as a CH₄ source (78.65%) during winter and a sink (21.35%) in summer. Soil temperature had a negative relationship (p < 0.01; R² = 0.344) with CH₄ flux but had a positive relationship with soil moisture (p < 0.01; R² = 0.348). Our results showed that soil temperature and moisture were the most important factors controlling the ecosystem-scale CH₄ flux dynamics of subtropical forests in the Tianmu Mountain Nature Reserve in Zhejiang Province, China. Subtropical forest ecosystems in China acted as a net source of methane emissions from 2016 to 2018, providing positive feedback to global climate warming.

Tropical rainforest ecosystems are important when considering the global methane (CH₄) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH₄ fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH₄ flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH₄ uptake generally occurred in this tropical rainforest, where strong CH₄ uptake occurred in the daytime, and a weak CH₄ uptake occurred at night with a mean daily CH₄ flux of −4.5 nmol m⁻² s⁻¹. In this rainforest, the mean annual budget of CH₄ for the 3 years was −1260 mg CH₄ m⁻² year⁻¹. Furthermore, the daily averaged CH₄ flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH₄ flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (T_air), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (T_soil), although the linear correlation between the daily CH₄ flux and any of these individual variables was relatively low. This indicates that CH₄ uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH₄ sink during 2016–2018, helping to counteract global warming.

Understanding the impacts of nitrogen (N) addition on soil respiration (R_S) and its temperature sensitivity (Q₁₀) in tropical forests is very important for the global carbon cycle in a changing environment. Here, we investigated how R_S respond to N addition in a tropical montane rainforest in Southern China. Four levels of N treatments (0, 25, 50, and 100 kg N ha⁻¹ a⁻¹ as control (CK), low N (N25), moderate N (N50), and high N (N100), respectively) were established in September 2010. Based on a static chamber-gas chromatography method, R_S was measured from January 2015 to December 2018. R_S exhibited significant seasonal variability, with low R_S rates appeared in the dry season and high rates appeared in the wet season regardless of treatment. R_S was significantly related to the measured soil temperature and moisture. Our results showed that soil R_S increased after N additions, the mean annual R_S was 7% higher in N25 plots, 8% higher in N50 plots, and 11% higher in N100 plots than that in the CK plots. However, the overall impacts of N additions on R_S were statistically insignificant. For the entire study period, the CK, N25, N50, and N100 treatments yielded Q₁₀ values of 2.27, 3.45, 4.11, and 2.94, respectively. N addition increased the temperature sensitivity (Q₁₀) of R_S. Our results suggest that increasing atmospheric N deposition may have a large impact on the stimulation of soil CO₂ emissions from tropical rainforests in China.