Although rice paddy fields are one of the world’s largest anthropogenic sources of methane CH4, the budget of ecosystem CH4 and its’ controls in rice paddies remain unclear. Here, we analyze seasonal dynamics of direct ecosystem-scale measurements of CH4 flux in a rice-wheat rotation agroecosystem over 3 consecutive years. Results showed that the averaged CO2 uptakes and CH4 emissions in rice seasons were 2.2 and 20.9 folds of the wheat seasons, respectively. In sum, the wheat-rice rotation agroecosystem acted as a large net C sink (averaged 460.79 g C m−2) and a GHG (averaged 174.38 g CO2eq m−2) source except for a GHG sink in one year (2016) with a very high rice seeding density. While the linear correlation between daily CH4 fluxes and gross ecosystem productivity (GEP) was not significant for the whole rice season, daily CH4 fluxes were significantly correlated to daily GEP both before (R2: 0.52–0.83) and after the mid-season drainage (R2: 0.71–0.79). Furthermore, the F partial test showed that GEP was much greater than that of any other variable including soil temperature for the rice season in each year. Meanwhile, the parameters of the best-fit functions between daily CH4 fluxes and GEP shifted between rice growth stages. This study highlights that GEP is a good predictor of daily CH4 fluxes in rice paddies.
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 (Tair), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (Tsoil), 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.
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