Methane fluxes measured by eddy covariance on Dutch peatlands

Rewetting peatlands is required to limit carbon dioxide (CO2) emissions,
however, raising the groundwater level (GWL) will strongly increase the
chance of methane (CH4) emissions which have a higher radiative forcing
than CO2. Datasets of CH4 from different rewetting strategies and natural
systems are scarce, and quantification and an understanding of the main
drivers of CH4 emissions are needed to make effective peatland rewetting
decisions. We present a large dataset of CH4 fluxes (FCH4) measured across
16 sites with eddy covariance on Dutch peatlands. Sites were classified
into six land uses, which also determined their vegetation and GWL range.
We investigated the principal drivers of emissions and gap-filled the data
using machine learning (ML) to derive annual totals. In addition, Shapley
values were used to understand the importance of drivers to ML model
predictions. The data showed the typical controls of FCH4 where
temperature and the GWL were the dominant factors, however, some
relationships were dependent on land use and the vegetation present. There
was a clear average increase in FCH4 with increasing GWLs, with the
highest emissions occurring at GWLs near the surface.  Soil
temperature was the single most important predictor for ML gapfilling but
the Shapley values revealed the multi-driver dependency of FCH4. Mean
annual FCH4 totals across all land uses ranged from 90±11 to 632±65 kg CH4
ha-1yr-1 and were on average highest for semi-natural land uses, followed
by paludiculture, lake, wet grassland, and pasture with water infiltration
system. The mean annual FCH4 was strongly correlated to the mean annual
GWL (R2 = 0.80). The greenhouse gas balance of our sites still needs to be
estimated to determine the net climate impact, however, our results
indicate that considerable rates of CO2 uptake and long-term
storage are required to fully offset the emissions of CH4 from land uses
with high GWLs.