Net ecosystem exchange and energy fluxes measured with the eddy covariance technique in a western Siberian bog

Very few studies of ecosystem-atmosphere exchange involving eddy covariance data have been conducted in Siberia, with none in the western Siberian middle taiga. This work provides the first estimates of carbon dioxide (CO2) and energy budgets in a typical bog of the western Siberian middle taiga based on May-August measurements in 2015. The footprint of measured fluxes consisted of a homogeneous mixture of tree-covered ridges and hollows with the vegetation represented by typical sedges and shrubs. Generally, the surface exchange rates resembled those of pinecovered bogs elsewhere. The surface energy balance closure approached 100 %. Net CO2 uptake was comparatively high, summing up to CO2 gCm(-2) for the four measurement months, while the Bowen ratio was seasonally stable at 28 %. The ecosystem turned into a net CO2 source during several front passage events in June and July. The periods of heavy rain helped keep the water table at a sustainably high level, preventing a usual drawdown in summer. However, because of the cloudy and rainy weather, the observed fluxes might rather represent the special weather conditions of 2015 than their typical magnitudes.Peer reviewe

Variability in methane emissions from West Siberia's shallow boreal lakes on a regional scale and its environmental controls

Small lakes represent an important source of atmospheric CH4 from northern wetlands. However, spatiotemporal variations in flux magnitudes and the lack of knowledge about their main environmental controls contribute large uncertainty into the global CH4 budget. In this study, we measured methane fluxes from small lakes using chambers and bubble traps. Field investigations were carried out in July–August 2014 within the West Siberian middle and southern taiga zones. The average and median of measured methane chamber fluxes were 0.32 and 0.30 mgCH4 m−2 h−1 for middle taiga lakes and 8.6 and 4.1 mgCH4 m−2 h−1 for southern taiga lakes, respectively. Pronounced flux variability was found during measurements on individual lakes, between individual lakes and between zones. To analyze these differences and the influences of environmental controls, we developed a new dynamic process-based model. It shows good performance with emission rates from the southern taiga lakes and poor performance for individual lakes in the middle taiga region. The model shows that, in addition to wellknown controls such as temperature, pH and lake depth, there are significant variations in the maximal methane production potential between these climatic zones. In addition, the model shows that variations in gas-filled pore space in lake sediments are capable of controlling the total methane emissions from individual lakes. The CH4 emissions exhibited distinct zonal differences not only in absolute values but also in their probability density functions: the middle taiga lake fluxes were best described by a lognormal distribution while the southern taiga lakes followed a power-law distribution. The latter suggests applicability of self-organized criticality theory for methane emissions from the southern taiga zone, which could help to explain the strong variability within individual lakes

Mapping Onshore CH4 Seeps in Western Siberian Floodplains Using Convolutional Neural Network

Onshore seeps are recognized as strong sources of methane (CH4), the second most important greenhouse gas. Seeps actively emitting CH4 were recently found in floodplains of West Siberian rivers. Despite the origin of CH4 in these seeps is not fully understood, they can make substantial contribution in regional greenhouse gas emission. We used high-resolution satellite Sentinel-2 imagery to estimate seep areas at a regional scale. Convolutional neural network based on U-Net architecture was implemented to overcome difficulties with seep recognition. Ground-based field investigations and unmanned aerial vehicle footage were coupled to provide reliable training dataset. The seep areas were estimated at 2885 km2 or 1.5% of the studied region; most seep areas were found within the Ob’ river floodplain. The overall accuracy of the final map reached 86.1%. Our study demonstrates that seeps are widespread throughout the region and provides a basis to estimate seep CH4 flux in entire Western Siberia

Mapping Onshore CH₄ Seeps in Western Siberian Floodplains Using Convolutional Neural Network

Onshore seeps are recognized as strong sources of methane (CH4), the second most important greenhouse gas. Seeps actively emitting CH4 were recently found in floodplains of West Siberian rivers. Despite the origin of CH4 in these seeps is not fully understood, they can make substantial contribution in regional greenhouse gas emission. We used high-resolution satellite Sentinel-2 imagery to estimate seep areas at a regional scale. Convolutional neural network based on U-Net architecture was implemented to overcome difficulties with seep recognition. Ground-based field investigations and unmanned aerial vehicle footage were coupled to provide reliable training dataset. The seep areas were estimated at 2885 km2 or 1.5% of the studied region; most seep areas were found within the Ob’ river floodplain. The overall accuracy of the final map reached 86.1%. Our study demonstrates that seeps are widespread throughout the region and provides a basis to estimate seep CH4 flux in entire Western Siberia

Atmospheric Methane Consumption and Methanotroph Communities in West Siberian Boreal Upland Forest Ecosystems

Upland forest ecosystems are recognized as net sinks for atmospheric methane (CH4), one of the most impactful greenhouse gases. Biological methane uptake in these ecosystems occurs due to the activity of aerobic methanotrophic bacteria. Russia hosts one-fifth of the global forest area, with the most extensive forest landscapes located in West Siberia. Here, we report seasonal CH4 flux measurements conducted in 2018 in three types of stands in West Siberian middle taiga–Siberian pine, Aspen, and mixed forests. High rates of methane uptake of up to −0.184 mg CH4 m−2 h−1 were measured by a static chamber method, with an estimated total growing season consumption of 4.5 ± 0.5 kg CH4 ha−1. Forest type had little to no effect on methane fluxes within each season. Soil methane oxidation rate ranged from 0 to 8.1 ng CH4 gDW−1 h−1 and was negatively related to water-filled pore space. The microbial soil communities were dominated by the Alpha- and Gammaproteobacteria, Acidobacteriota and Actinobacteriota. The major group of 16S rRNA gene reads from methanotrophs belonged to uncultivated Beijerinckiaceae bacteria. Molecular identification of methanotrophs based on retrieval of the pmoA gene confirmed that Upland Soil Cluster Alpha was the major bacterial group responsible for CH4 oxidation

Variability in methane emissions from West Siberia\u27s shallow boreal lakes on a regional scale and its environmental controls

Small lakes represent an important source of atmospheric CH4 from northern wetlands. However, spatiotemporal variations in flux magnitudes and the lack of knowledge about their main environmental controls contribute large uncertainty into the global CH4 budget. In this study, we measured methane fluxes from small lakes using chambers and bubble traps. Field investigations were carried out in July–August 2014 within the West Siberian middle and southern taiga zones. The average and median of measured methane chamber fluxes were 0.32 and 0.30 mgCH4 m−2 h−1 for middle taiga lakes and 8.6 and 4.1 mgCH4 m−2 h−1 for southern taiga lakes, respectively. Pronounced flux variability was found during measurements on individual lakes, between individual lakes and between zones. To analyze these differences and the influences of environmental controls, we developed a new dynamic process-based model. It shows good performance with emission rates from the southern taiga lakes and poor performance for individual lakes in the middle taiga region. The model shows that, in addition to wellknown controls such as temperature, pH and lake depth, there are significant variations in the maximal methane production potential between these climatic zones. In addition, the model shows that variations in gas-filled pore space in lake sediments are capable of controlling the total methane emissions from individual lakes. The CH4 emissions exhibited distinct zonal differences not only in absolute values but also in their probability density functions: the middle taiga lake fluxes were best described by a lognormal distribution while the southern taiga lakes followed a power-law distribution. The latter suggests applicability of self-organized criticality theory for methane emissions from the southern taiga zone, which could help to explain the strong variability within individual lakes