Preprints
https://doi.org/10.5194/bg-2023-61
https://doi.org/10.5194/bg-2023-61
31 Mar 2023
 | 31 Mar 2023
Status: a revised version of this preprint was accepted for the journal BG and is expected to appear here in due course.

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

Anna-Maria Virkkala, Pekka Niittynen, Julia Kemppinen, Maija E. Marushchak, Carolina Voigt, Geert Hensgens, Johanna Kerttula, Konsta Happonen, Vilna Tyystjärvi, Christina Biasi, Jenni Hultman, Janne Rinne, and Miska Luoto

Abstract. Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) 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) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km2). We used these field data together with high-resolution remote sensing data to develop machine learning models to predict (i.e., upscale) 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 CO2 uptake, it also revealed small but widespread CH4 uptake in upland vegetation types, shifting this region to an average net CH4 sink at the landscape scale during growing season, despite the presence of high-emitting wetlands. Average N2O fluxes were negligible. CO2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH4 fluxes by soil moisture (increases net emissions) and vegetation type, and N2O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modelling of GHG fluxes in the Arctic. They also reveal the dominant role of CO2 fluxes across the tundra landscape, but suggest that CH4 uptake might play a significant role in the regional GHG budget.

Anna-Maria Virkkala et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-61', Ludda Ludwig, 25 Apr 2023
  • RC2: 'Comment on bg-2023-61', June Skeeter, 22 May 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-61', Ludda Ludwig, 25 Apr 2023
  • RC2: 'Comment on bg-2023-61', June Skeeter, 22 May 2023

Anna-Maria Virkkala et al.

Anna-Maria Virkkala et al.

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Latest update: 24 Nov 2023
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Co-editor-in-chief
Arctic greenhouse gas fluxes are key for climate feedback but the Arctic greenhouse gas balance is poorly constrained due to a limited understanding of the spatial variation in these fluxes. This study combines extensive chamber-based flux measurements and remote sensing data to develop a machine-learning model to predict greenhouse gas fluxes across a tundra landscape in Finland. The analysis revealed that the system was a net greenhouse gas sink and showed widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale.
Short summary
We mapped and modelled the distribution of greenhouse gas flux hotspots in sub-Arctic Finland. Our results show that this tundra region was on average a daytime net greenhouse gas sink during the growing season. We also observed widespread methane uptake. Our results indicate that modeling greenhouse gas fluxes at high spatial resolutions is possible, providing important support for future studies aiming to understand and predict the rapidly changing Arctic environments.
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