| 07 Aug 2025
Dynamics and environmental drivers of methane and nitrous oxide fluxes at the soil and ecosystem levels in a wet tropical forest
Abstract. Tropical forests are critical for maintaining the global carbon balance and mitigating climate change, yet their exchange of greenhouse gases with the atmosphere remains understudied, particularly for methane (CH4) and nitrous oxide (N2O). This study reports on continuous measurements of CH4 and N2O fluxes at the ecosystem and soil levels, respectively through eddy covariance and an automated chamber technique, in a wet tropical forest in French Guiana over a period of 26 months. We studied the magnitude of CH4 and N2O fluxes and their drivers (climatic variables) during two extreme periods, the driest and wettest seasons. Seasonal ecosystem fluxes showed near-zero net CH4 uptake during the driest season and emissions occurring during the wettest season that were larger in magnitude than the uptake. Meanwhile, N2O emissions were of similar magnitudes in both seasons. Some upland soils within the footprint of the eddy covariance tower emitted N2O in both seasons, although these fluxes were particularly small. None of the measured climatic variables could explain this soil N2O flux variation. In contrast, the upland soils were characterised by CH4 uptake. Overall, seasonal ecosystem CH4 and N2O fluxes, as well as seasonal upland soil CH4 fluxes, were partially explained by seasonal variations in soil water content and global radiation. In addition to the upland soil fluxes studied, the magnitude and sign of the net ecosystem fluxes of CH4 and N2O were likely due to outgassing from aboveground biomass and the presence of seasonally flooded areas within the footprint of the eddy covariance system. Further studies of other ecosystem compartments in different forest habitats are needed to better understand the temporal variations in CH4 and N2O fluxes in wet tropical forests.
Overall, this paper is a useful addition to the literature. Better characterizing greenhouse gas fluxes from tropical soils, and identifying drivers, is a timely and important research question. The combination of automated chambers and eddy-flux, especially for N2O, is very novel for tropical forests. Overall, given the well-known spatial and temporal heterogeneity of N2O fluxes even in much more homogenous ecosystems, I am not surprised that fluxes were not well explained by simple environmental variables, even with the data density of this paper. This is a dataset that will certainly be of interest to many people. Several of the methodological lessons learned (such as lack of storage of N2O and Ch4 under the canopy, revealed by vertical profile measurements) are also likely to be of use to other researchers.
I have one significant concern that I think merits serious consideration- the choice to exclude high fluxes from analysis (and indeed not to present them at all, making it very difficult to judge how important they might be). Specifically, the authors did not present (or include in analysis) any fluxes outside the 5th-95th percentile (per line 248), even after rigorous data cleaning steps that should have weeded out any anonymously high fluxes that were methodological artifacts. I realize that it is very difficult to scale rare, high fluxes without very good estimates of their probability. However, I do not thing that dismissing them entirely makes any sense, and no specific rationale or citation was given for the choice. Rare, very high N2O fluxes are not at all uncommon in tropical forests in my personal experience, but rarely do we have the data density (as we do here!) to judge their potential importance. These excluded fluxes- depending on their magnitude, could be potentially important for net ecosystem emissions, especially because they’re probably quite skewed- extreme production events could be somewhat common but extreme consumption events likely are not.
To summarize- I am not necessarily suggesting that all data needs to incorporated into scaling, but I would strongly suggest 1) presenting the relative magnitude of the excluded fluxes compared to the data that was included. Were they common and somewhat high? Or more rare and extremely high? 2) At least conducting some sort of sensitivity of means, medians etc to the inclusion or exclusion of these omitted values (including perhaps making a range of assumptions about their probability, in the case of very high outliers). I also would hazard, and add caveats, against comparisons with any other rate fluxes from tropical sites that may indeed have included hot spots and hot moments in their scaling efforts. Overall it seems counterintuitive to highlight the heterogeneity of soil GHG fluxes and then ignore a potential large fraction of the variation.
Finally, data should be posted in an accessible database online in keeping with the specifications of this journal (rather than ‘on request’).