High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra

Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial g...

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Bibliographic Details
Published in:Biogeosciences
Main Authors: Virkkala, Anna-Maria, Niittynen, Pekka, Kemppinen, Julia, Marushchak, Maija E., Voigt, Carolina, Hensgens, Geert, Kerttula, Johanna, Happonen, Konsta, Tyystjärvi, Vilna, Biasi, Christina, Hultman, Jenni, Rinne, Janne, Luoto, Miska
Format: Text
Language:English
Published: 2024
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Online Access:https://doi.org/10.5194/bg-21-335-2024
https://bg.copernicus.org/articles/21/335/2024/
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Summary:Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen ( C / N <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="a1fd226718b6fd2378e4d645ff1b8807"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-21-335-2024-ie00001.svg" width="24pt" height="14pt" src="bg-21-335-2024-ie00001.png"/></svg:svg> ) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km 2 ). We used these field data together with high-resolution remote sensing data to develop machine learning models for predicting (i.e., upscaling) daytime GHG fluxes across the landscape at 2 m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO 2 uptake, it also revealed small but widespread CH 4 uptake in upland vegetation types, almost surpassing the high wetland CH 4 emissions at the landscape scale. Average N 2 O fluxes were negligible. CO 2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH 4 fluxes by soil moisture (increases net emissions) and vegetation type, and N 2 O fluxes by soil C / N <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="14pt" class="svg-formula" ...