Predicting Methane Formation Rates of Freshwater Sediments in Different Biogeographic Regions

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Abstract

Freshwater lakes and reservoirs cover a small fraction of the Earth, however their emission of the greenhouse gas methane (CH4) from the sediment to the atmosphere is disproportionately high. Currently, there is still a limited understanding of the links between sediment characteristics and CH4 formation. Earlier studies have indicated that sediment age and nitrogen content are related to sediment CH4 formation rates, but it is uncertain such relationships are valid across gradients of sediment characteristics. We therefore measured potential CH4 formation rates in multiple layers of sediment sampled from nine lakes situated in the temperate, boreal and alpine biogeographic regions of Sweden, thus differing in productivity, catchment and climate properties. Potential CH4 formation varied over 3 orders of magnitude, and was broadly related to the quantity and reactivity of organic matter, and generally decreased with sediment depth. Sediment age and total nitrogen content were found to be the key controlling factors of potential CH4 formation rates, together explaining 62% of its variability. Moreover, the model developed from the Swedish lake sediment data was able to successfully predict the potential CH4 formation rates in reservoirs situated in different biogeographic regions of Brazil (R2 = 0.62). Therefore, potential CH4 formation rates in sediments of highly contrasting lakes and reservoirs, from Amazonia to alpine tundra, could be accurately predicted using one common model (RMSE = 1.6 in ln-units). Our model provides a valuable tool to improve estimates of CH4 emission from lakes and reservoirs, and illustrates the fundamental regulation of microbial CH4 formation by organic matter characteristics.

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Moras, S., Zellmer, U. R., Hiltunen, E., Grasset, C., & Sobek, S. (2024). Predicting Methane Formation Rates of Freshwater Sediments in Different Biogeographic Regions. Journal of Geophysical Research: Biogeosciences, 129(1). https://doi.org/10.1029/2023JG007463

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