Methane fluxes mediated by plants: Magnitude and drivers

Methane (CH4) emissions from tropical wetlands remain the largest uncertainty in the global CH4 cycle, and due to the high global warming potential of CH4 (84 times that of CO2 over a 20-year timescale), changes inemissions can disproportionately influence the climate over the coming decades. Methane has a short atmospheric life span, therefore reducing CH4 emissions could be key to meeting the Paris agreement temperature targets. To achieve this, it is essential to improve our understanding of regional CH4 emissions, especially from tropical areas, the largest natural sources but where field observations remain scarce. Although plant CH4 emissions can be regionally important in the tropics, in some cases contributing up to 81 % of total ecosystem level fluxes, they are neglected in global methane budgets. Peatlands, a type of wetland where waterlogged conditions result in accumulation of organic matter and anoxic conditions in the soil, most likely play an important but uncertain role in CH4 release (40 to 80% of tropical CH4 emissions). The large uncertainties in plant mediated CH4 emissions in tropical peatlands occur due to insufficient long-term field experiments to capture seasonal and interannual variability in CH4 fluxes and lack of information about plant species-specific emissions patterns and their drivers. To fill this gap, we are measuring plant trunk/stem CH4 fluxes across seasons in four tropical peatlands in Africa and South America with contrasting vegetation types: 1) a papyrus swamp (herbaceous, Mpologoma, Uganda) 2) a hardwood swamp forest (Bomboma, Democratic Republic of Congo) 3) a Montrichardia swamp (herbaceous, Leticia, Colombia) and 4) a hardwood swamp forest (Inirida, Colombia). We hypothesize that the magnitude and temporal dynamics of CH4 is intimately linked to environmental variables (e.g., water table level, temperature, etc) and plant growth cycles. By identifying the magnitude and main drivers behind CH4 emissions through plants it will be possible to reduce uncertainties in modelling future emissions and hence future climate projections.