https://doi.org/10.3389/fenvs.2026.1838949

Hettinga, E. K., Rezanezhad, F., Persaud, B. D., Slowinski, S., Strack, M., Liu, H., Lennartz, B., Humphreys, E., Wu, J., Skeeter, J., Knox, S. H., Alcock, H., Sonnentag, O., Detto, M., & Van Cappellen, P. (2026). Comparing modeled and measured carbon dioxide data at five Canadian peatlands revealed highly variable non-growing season fluxes. Frontiers in Environmental Science, 14, Article 1838949. https://doi.org/10.3389/fenvs.2026.1838949

Peatlands hold up to one-third of the global organic carbon (C) stock and are considered a critical C sink. Climate models project that the rate of warming in northern peatlands will continue throughout the 21st century, with the greatest warming occurring during the non-growing season (NGS), which is poorly represented in current in-situ measurements. As a result, the contribution of NGS fluxes to annual peatland CO2 budgets remains uncertain. Remotely sensed and modeled data products offer a potential means to estimate year-round fluxes, but their performance in peatland ecosystems has not been fully evaluated. In this study, we used the remotely sensed and modeled Soil Moisture Active Passive Level 4 Global Daily EASE-Grid C NEE (SMAP-NEE) data product to acquire 9 years (2015–2023) of SMAP-NEE data for five peatlands. We compared these values to a subset of year-round eddy covariance NEE (EC-NEE) measurements within this time frame at each of the five peatland sites. The analyses showed that the SMAP-NEE data product reports a stronger growing season (GS) sink and a weaker NGS source than the EC-NEE measurements. Using the relationship between SMAP-NEE and EC-NEE, we produced a Corrected-SMAP-NEE dataset, which provided an estimate of seasonal and annual carbon dioxide (CO2) budgets. Our data analyses of the Corrected-SMAP-NEE dataset showed that NGS CO2 emissions represented a highly variable proportion (33%–256%) of the GS CO2 uptake, that reduced the annual CO2 sink strength proportionally. This work demonstrates the necessity of monitoring during the NGS and highlights the importance of incorporating peatland data into model training to improve CO2 flux estimates in these environments.

https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2026.1838949/pdf