[M-IS05] Environmental, Socio-economic, and Climatic Changes in Northern Eurasia

[MIS05-P15] Temporal variability of carbon dioxide, sensible and latent heat fluxes in forest and peatland ecosystems of North-Central Siberia

Elizaveta Gorbarenko^1,2,3、Viacheslav Zyrianov⁴、Artem Gorbarenko⁵、Anatoly Prokushkin⁴、Alexey Panov⁴、*Alexander Olchev^1,3 (1.Department of Meteorology and Climatology, Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia、2.A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Science, Moscow, Russia、3.Institute of Geography, Russian Academy of Science, Moscow, Russia、4.V.N. Sukachev Institute of Forest, Siberian Branch of Russian Academy of Science, Krasnoyarsk, Russia、5.Applied AI Center, Skolkovo Institute of Science and Technology, Moscow, Russia)

キーワード：carbon dioxide fluxes, latent and sensible heat fluxes, eddy covariance, subarctic palsa mire, larch forest, forest-tundra ecosystem

Climate change is occurring more rapidly at high latitudes than in other regions. Polar ecosystems are highly vulnerable to and significantly affected by such changes. The response of plants to changing environmental conditions is primarily manifested in changes in ecosystem and plant functioning, resulting in changes in water vapor (H2O) and carbon dioxide (CO2) fluxes. The main objective of the study was to analyze the long-term seasonal variability of net ecosystem exchange (NEE) of CO2, sensible (H) and latent (LE) heat fluxes in a subarctic palsa mire and a northern taiga mature larch forest in north-central Siberia, as well as to assess the response of fluxes in these ecosystems to changes in atmospheric conditions. The new experimental data were obtained using the eddy covariance method from 2019 to 2023. Data post-processing was performed according to generally accepted recommendations for eddy covariance data analysis. The CO2, H and LE fluxes were calculated from the raw data at 30 min time intervals using the EddyPro data processing software (LI-COR, USA), which performed all necessary statistical tests and corrections (de-spiking, coordinate rotation, correction for time delays, de-trending, correction for frequency response and air density, etc.). Gaps in the flux data were filled using a machine learning model based on the gradient boosting method.
The results showed that both ecosystems consistently served as net sinks for atmospheric CO2, regardless of significant year-to-year variations in meteorological conditions. The NEE during the 2019-2023 growing season varied from -62.9 to -120.2 gC m-2 in the palsa mire, and from -63.5 to -83.6 gC m-2 in the larch forest. The maximum CO2 uptake for the three summer months was observed at the Igarka station in 2022 (-120.62 gC m-2) and at the Tura station in 2023 (-83.61 gC m-2). Minimum CO2 uptake was recorded at the Igarka station in 2019 (-62.93 gC m-2) and at the Tura station in 2021 (-63.55 gC m-2). These years are also characterized by minimal Gross Primary Production (GPP) and Ecosystem Respiration (ER) in both ecosystems. A stronger interannual variation of accumulated summer NEE was observed in the palsa mire.
H and LE fluxes also showed significant interannual variations, mainly determined by incoming solar radiation, temperature and precipitation variations. Comparison of the integral H and LE fluxes calculated for the whole summer period (from June to August) showed that the highest H values were observed in 2019 in both the palsa mire and the larch forest, amounting to 637 MJ m-2 and 379 MJ m-2, respectively, due to precipitation deficit at rather high summer temperatures. The lowest H values were recorded in 2020 in both ecosystems. At the Igarka station, the integral summer LE fluxes showed little variation between years due to the high-water content of the upper soil horizon throughout the observation period from 2019 to 2023. At the Tura station, the opposite effect was observed: the maximum integral LE flux occurred in the year with the maximum precipitation.

The study was supported by grant of the Ministry of Science and Higher Education of the Russian Federation (agreement № 075-15-2024-554 of 24.04.2024).