Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract

Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

“…In contrast to TD models, BU model estimates are not constrained by atmospheric CH 4 concentration data and attempt to directly represent wetland CH 4 fluxes and underlying flux processes with varying complexity (Riley et al, 2011;Ueyama et al, 2023). For the same decade (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017), the GCP's 13-member BU model ensemble estimated emissions of 102-182 (mean 149) TgCH 4 yr −1 , ∼20% lower than the TD ensemble mean (Saunois et al, 2020).…”

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

“…Using daily data, as opposed to monthly or annual, as input to our model allowed us to train the ML model on a wider range of values (including extremes) for the independent variables. Based on conceptual knowledge and previous evaluations of FCH 4 predictors at these sites (Knox et al., 2021; Ueyama et al., 2023), we selected the six following predictors from the MERRA‐2 dataset: Mean daily surface air temperature (Tair; °C), daily precipitation (prec; mm/day), longwave (LW) radiation fluxes (lwrd; W/m 2 ), incoming shortwave (SW) radiation fluxes (swrd; W/m 2 ), wind speed (computed from 2‐meter eastward wind ( Ugrd ) and 2‐meter northward wind ( Vgrd ); m/s), and atmospheric surface pressure (pres; PA). Wind speed ( WS ) was computed as:$$$$ WS=\sqrt{Ugrd^2+{Vgrd}^2.}$$…”

Cold‐Season Methane Fluxes Simulated by GCP‐CH4 Models

“…Although the models captured the seasonal cycle of emissions seen in observations, their quantitative accuracy was low, as revealed by the model intercomparison analyses. The models differed in the temperature responsiveness of emissions at temperatures around freezing, likely because of their different soil structure and physical and biogeochemical parameterizations (Ueyama et al, 2023). For example, several models assumed threshold temperatures for CH 4 production and emission, but it should be examined against the observed temperature-flux relationships (Figure S8 and Text S1 in Supporting Information S1).…”