Quantification of Ecosystem-Scale Methane Sinks Observed in a Tropical Rainforest in Hainan, China

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.

Automated summary

The CH4 flux in a tropical rainforest in Hainan Island, China, showed diurnal variations with strong uptake during the day and weak uptake at night, resulting in an average daily CH4 flux of -4.5 nmol m(-2) s(-1). The mean annual CH4 budget for three years was -1260 mg CH4 m(-2) year(-1). The CH4 flux did not vary significantly between the dry season and wet season. Artificial neural network (ANN) modeling showed that 69% of the total variance in the daily CH4 flux could be explained by a combination of air temperature, latent heat flux, soil volumetric water content, atmospheric pressure, and soil temperature. This study suggests that tropical rainforests in China act as a CH4 sink, contributing to global warming mitigation.