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.