Using Gigante Litter Manipulation to Assess the Impact of CH4 Oxidation Potentials on the Surface Temperature and Stocks of Tropical Forest
To examine the relative importance of CH4 uptake, we compared it to the C fluxes and stocks of forests. Although metrics such as global warming potential (GWP) have long been used, a recent consensus has developed that expressing CH4 emissions as CO2 equivalent emissions using GWP-100 overstates the effect of constant CH4 emissions on global surface temperature by a factor of 3–4 (ref. 52) while understating the effect of any new CH4 source or sink by a factor of 4–5 over the 20 years following the introduction of the new source (IPCC AR6). A more accurate indication of CO2-we emissions is to equate a constant 1 t yr−1 of CH4 source that is more than 20 years old with 8 t of CO2-we yr−1 but to account for the warming (or cooling) impact of a 1 t of CH4 yr−1 step-change in CH4 emission rate by adding (or subtracting) 120 t of CO2-we yr−1 over the 20 years following the change. The new constant source of CH4 introduced in year 1 equates to 128 tons of CO2 over the course of the next 20 years. We converted all CO2 values to C only for the direct comparisons.
The Gigante Litter Manipulation Project was carried out in five plots of tropical forest which were south of Barro Colorado Island, Panama,Central America. Refs give a full description of the experiment. 36,37. There is a strong dry season from December to April and a mean annual rains of over 2,400mm at the weather station on Barro Colorado Island.
Following stem flux measurements at the Skogaryd and Cuniã study sites, we assessed the CH4 oxidation potentials (both high affinity and low affinity) in the tree stems by extracting wood cores at 30 and 130 cm stem height from a subset of the trees (Cuniã, 80 trees; Skogaryd, 9 trees per species).
For global-scale extrapolation, we used a combination of satellite remote sensing datasets. This approach allowed us to estimate woody surface areas across the world’s ecosystems, integrating our allometric model with global forest cover data.
We used the EcoRegions map of The Nature Conservancy to calculate the extents of the forest and the global consensus land cover project. Version 6 Vegetation Continuous Fields (VCF49) 2019 product, as well as the 1 km consensus land cover map, to determine per-pixel forest cover. The global view of vegetation cover provided by the dataset was quantified on a continuous scale.
To account for climatic variations in our model, we used the ERA5 monthly climate dataset50. The mean monthly temperatures were given in the dataset. With the woody surface area in each pixel known (Extended Data Table 4), we then applied the CH4 uptake versus MAT regression across the globe (Extended Data Table 4).
