Vol 13, No 3 (2022)

Cover Page

Full Issue

Theoretical works

What is the maximal possible soil methane uptake?

Glagolev M.V., Suvorov G.G., Il’yasov D.V., Sabrekov A.F., Terentieva I.E.


The spread of published values of the rate of methane uptake by soils makes up several orders of magnitude from 0.0001 to 1 mg·m-2·h-1, which is comparable in magnitude to the spread of estimates of the release of CH4 out of waterlogged soils. The high values of CH4 emissions out of waterlogged soils are well explained, since with high methane production, it can be removed from the soil at almost any speed through a convective (most often bubble) transport mechanism. But when being absorbed by the soil, methane can penetrate in it only due to an apparently slow diffusion mechanism. Thus, the question arises of the maximum theoretically justified assessment of methane consumption by the soil. The aim of our work was to try to quantify the maximum possible amount of CH4 consumption by the soil relying on a strict basis of soil biokinetics and physics.

To estimate the maximum specific absorption flux of CH4 by the soil, we used the "mass conservation equation" [Walter et al., 1996; Zhuang et al., 2004; Глаголев, 2006, p. 316; 2010, p. 35-36]:


Ct = -¶Fz + Qebull + Qplant + Rprod + Roxid,


where C (mg/m3) is the concentration of methane at time t at depth z; F (mg·m-2·h-1) is the specific flux of methane due to diffusion; Qebull and Qplant (mg·m–3·h-1) are the rates of change in methane concentration at time t at depth z due to the formation of bubbles and drainage through the roots of plants, respectively; Rprod and Roxid (mg·m-3 · h-1) are the rates of formation and consumption of methane, respectively.

Since we going to estimate the flux of CH4 only at its maximum possible consumption, the equation is simplified, as far as its terms accounted for the formation and transport of methane (Rprod, Qebull, Qplant) will be equal to 0. Finally, we will consider the system in a steady state, i.e. Ct = 0. Thus:F(t,z)/¶z = Roxid(t,z).

Using Fick's first law to calculate the diffusion flux (used with a modified sign compared to its traditional form):


F(t,z) = D(z)·¶Cz,


where D(z) is the diffusion coefficient [Zhuang et al., 2004]; and the modified Michaelis-Menten equation for calculating methane oxidation is:Roxid(t,z) = -Vmax·(CTh)/(KM + C - CTh), where CTh (mg·m-3) is the threshold concentration [Panikov, 1995, p. 151]; Vmax (mg·m-3·h-1) is the maximum specific consumption rate; KM (mg·m-3) is the half–saturation constant, and also under assumptions, (i) the concentration of CH4 is approximately equal to atmospheric (CA = 1.29 mg/m3) at the upper boundary (soil/atmosphere); (ii) the flux of CH4 can be assumed to be zero at an infinitely great depth [Born et al., 1990]; (iii) D, Vmax and KM >> (C- CTh) do not change with depth. Therefore, the absolute value of the specific flux from the atmosphere to the soil is:


|F(0)| = (CA-CTh)·(Vmax·D/KM)½.


The maximum value of the diffusion coefficient can be estimated by the Penman equation: D = D o·Pa·0.66, where Do is the diffusion coefficient in air; Pa is the porosity of aeration [Смагин, 2005, p. 165]. Since we are going to estimate the maximum value of diffusion, we will take the limit value of porosity, which is 1, but as far as the proportion of pores of stable aeration accounts for half of the total pore volume [Растворова, 1983, p. 52], then for further calculations we will take Pa = 0.5, hence D = D o·0.33. According to [Arah and Stephen, 1998], for CH4


Do = 1.9·10-5∙(T/273)1.82 m2/s = 6.8·10-2∙(T/273)1.82 m2/h,


where T is temperature (K). When solving our diffusion problem, we assumed that the temperature is the same throughout the soil profile, and is 293 K. then D = 6.8·10-2∙(293/273)1.82·0.33 = 2.55·10-2 m2/h.

The maximum rate of CH4 oxidation by soil was experimentally estimated in [Bender and Conrad, 1992] and was 57.3 mg/(h·m3), which is in good agreement with the value of Vmax = 47 mg/(h·m3) obtained at T = 32 °C according to the temperature dependence for automorphic soils of boreal forests Vmax = 1.5(T ‑5.4)/10 mmol/(h·L), given in the work of Zhuang et al. [2004].

The half–saturation constant is the concentration of the substrate, at which the specific growth rate of microorganisms takes a value equal to a half of the maximum.  Summaries of the values KM have been repeatedly published (see, for example, [King, 1992, Tab. II; Segers, 1998, Tab. 4; Глаголев, 2006, pp. 324-325]). For our purposes, we should take the KM obtained directly in the experiments with substrate concentrations (CH4) closest to those found in natural conditions. The minimum value (3·10-8 mol/L) is given in [Bender and Conrad, 1992]. This value corresponds to the methane concentration in the air of about 20 ppm (14.3 mg/m3). This КМ value will be taken for further calculations.

The threshold concentration of CH4 for methanotrophs in the upper soil layer, given in the scientific literature, varies from 0.1 to 3.5 ppm [Crill, 1991; Bender and Conrad, 1992; Kravchenko et al., 2010]. Since we are interested in the minimum value of this indicator, we will bring it to the minimum temperature (273 K or 0 °C): CTh = 0.0714 mg/m3.

Now, having all the necessary numerical values, we can estimate the maximum intensity of methane consumption by natural soils:

|F(0)| = 1.2186·(57.3·2.55·10-2/14.3)½ ≈ 0.39 mg/(m2·h).


Thus, for a certain "ideal" soil (evenly warmed throughout the profile, perfectly aerated, and at the same time containing enough moisture to create optimal living conditions for methanotrophs, which, by the way, are extremely numerous in the soil, and their methane half–saturation constant is very low, etc.) we obtained an absorption intensity of CH4 of about 0.39 mg/(m2·h). Since the combination of optimal values of all factors affecting methane consumption is very unlikely (or, rather, even improbable) in real soils, the resulting value can be considered extremely possible. And in view of this, the empirical generalization made in [Crill, 1991] becomes clear: "From the Amazon floodplain to the Arctic, the most rapid rates rarely exceed 6 mgCH4·m-2·d-1" i.e. 0.25 mg/(m2·h).

Conclusion. So, we considered the absorption of methane as a biochemical process (following the Michaelis-Menten law with certain kinetic parameters), limited by diffusion in porous medium (soil). Based on this theoretical analysis, we came to the conclusion that the extremely large values of the specific absorption flux of CH4 (about 0.4 mg·m-2·h-1 and more), which are sometimes found in the literature, are unrealistic, if we are talking about the soils, which are always under methane concentrations no greater than atmospheric – 1.8 ppmv. This applies to the vast majority of soils – almost all, except for wetlands and soils covering landfills, underground gas storage facilities or other powerful sources of methane.

Environmental Dynamics and Global Climate Change. 2022;13(3):123-141
pages 123-141 views

Experimental works

Hot spots of methane emission in West Siberian middle taiga wetlands disturbed by petroleum extraction activities

Sabrekov A.F., Filippov I.V., Dyukarev E.A., Zarov E.A., Kaverin A.A., Glagolev M.V., Terentieva I.E., Lapshina E.D.


Introduction. The concentration of methane in the Earth's atmosphere, the second most potent greenhouse gas, continues to rise since 2007 [Canadell et al., 2021]. The need to significantly reduce the anthropogenic emission of methane into the atmosphere in order to limit the increase in global temperature by 2100 within 2°C relative to the period from 1850 to 1900 is recognized by both the scientific community [IPCC, 2021] and the leadership of most countries of the world, including Russia, who signed and ratified the Paris Agreement, adopted following the results of the 21st Conference of the UN Framework Convention on Climate Change [Climate Agenda of Russia, 2021]. Reduction of methane emissions and control over it throughout the territory of managed ecosystems will require huge resources and investments, development of new climate-smart technologies. A reasonable compromise may be to identify the most important sources of methane within managed ecosystems (also called “hot spots”) and to introduce changes in their land-use in accordance with the principles of sustainable development and science-based environmental management.

The major type of economic activity in the taiga natural zone of West Siberia is oil production [Koleva, 2007; Volkova, 2010]. Since 35-40% of the West Siberian middle taiga area is covered with waterlogged ecosystems - wetlands and floodplains [Peregon et al., 2009; Terentieva et al., 2016], a significant part of this infrastructure is located in wetland ecosystems and has a strong impact on them. In this paper, we made the first attempt to understand, how the most common types of disturbances by oil production (road, pipeline and electric power transmission line construction) can affect methane emissions from the most common disturbed waterlogged ecosystems in the region (oligotrophic raised bogs on a terrace or watershed) and eutrophic lowland swamps in the floodplain). We measured methane emission from the surface of disturbed wetland ecosystems, physicochemical and biological factors influencing it, to identify which ecosystems are hot spots of methane emission.

Objects. The study area was located 50 km southeast of the city of Khanty-Mansiysk, on the right bank of the Irtysh River, in the natural zone of the middle taiga. The climate of this region is subarctic (Dfc according to Köppen). In the floodplain of the Irtysh the most common types of wetlands are sedge-grass open swamps and sogras (treed sedge-grass wetlands), on terraces and the watershed - pine-shrub-sphagnum ecosystems (ryams) and ridge-hollow complexes [Liss et al., 2001]. The thickness of the peat layer in raised bogs on the terrace and watershed varied from 2 to 3 m; in sogra – from 3.5 to 4 m; in open floodplain swamps thickness of organic-rich horizon never exceeded 0.4 m. For floodplain ecosystems we investigated influence of a four-lane access road on changing the hydrological functioning of open swamps (points OO and OK), as well as the effect of cross-cut in a sogra (SP) compared to an undisturbed sogra (SE). For raised bogs on the terrace and watershed, we study the influence of asphalt two-lane roads which act as dams, preventing the flow of water from one side of the road to the other resulting in flooding to upstream areas (GMKO1 and GMKO2) and drying in downstream areas (GMKS) in ridge-hollow complexes. In ryams and ridge-hollow complexes The effect of cross-cutting on methane emission in ryams (RP1 and RP2) as well as pipeline installation in ryam (RTO1) and ridge-hollow complex (RTO2) were also studied. During a cross-cut tree layer was destroyed, the vegetation and moss cover was compacted (RP1) or mostly destroyed (RP2 and SP). Access roads were constructed 3 (four-lane) and 10-15 (asphalt two-lane) years ago. Pipelines were installed 2-3 years ago.

Methods. Methane flux was measured using the static chamber method [Hutchinson and Mosier, 1981]. In the course of one flux measurement four syringes were taken from the chamber on the interval of 10 min. Total duration of one flux measurement was 30 minutes. Three consecutive replicates of the flux measurements were carried out on each of the three collars per each investigated ecosystem. Interval between two consecutive flux measurements was 10 min. Water were sampled from the depth of 20 cm below water table level (WTL) in two replicates to determine dissolved organic carbon (DOC) content at the points GMKO2, GMKS, RTO1, RTO2, RP2, as well as in an undisturbed ryam ecosystem 50 m away from the points RTO1 and RP2. The concentration of DOC was measured by a Flash 2000 elemental analyzer using an AS1310 automatic liquid sampler (both Thermo Fisher Scientific, USA). In each studied ecosystem for each collar the values of WTL (cm, positive water is below the level of the moss surface), pH and electrical conductivity (μS·cm-1) of water were measured. All calculations were carried out in the MATLAB software environment R2022a (MathWorks, USA).

Results and discussion. Methane emission varied from 0.005 to 41.7 mg·m-2·h-1 with a median of 2.1 mg·m‑2·h‑1. Fluxes were not distributed normally (p < 0.0001, N = 33), but could be described by the lognormal distribution (p = 0.15) and the Weibull distribution (p = 0.22). Such a significant distribution asymmetry indicates that changes of land-use practice in several ecosystems with the highest methane emission could help to reduce methane emission significantly without substantial modifications of the whole landscape. The dependence of the methane flux on WTL differs depending on both disturbance and ecosystem types. Within one ecosystem, the maximum emission values can be observed both in most flooded sites (RP2, GMKS), in sites with intermediate WTL values (GMKO1, RTO2, OK), and in sites with the highest WTL (RTO1). One of the markers of methane emission hot spots is the appearance of ruderal plants Eriophorum vaginatum and Trichophorum cespitosum in different ecosystems and on disturbances of different types. Eriophorum vaginatum is one of the first species to settle on bare peat in cross-cuts (RTO1 and RTO2) and footprints after heavy equipment (RP2) in raised bogs, as well as on seismic survey lines in sogra (SP). Trichophorum cespitosum was found in the upstream area of the road, where a zone of excessive moisture has formed resulting in degradation of the moss and vegetation cover and peat decomposition (GMKO1). In all these five ecosystems, methane flux from sites covered with Eriophorum vaginatum and Trichophorum cespitosum was 2 or more times higher compared to the surrounding sites where these species were absent.

The maximum values of methane emission among all studied ecosystems are in the WTL range from -2 to 8 cm (see Fig. 1). In studied raised bogs, the emission from the flooded upstream areas (GMKO1 and GMKO2) was significantly lower (p = 0.0082, N = 8) than from the dried downstream areas (GMKS), if we exclude the point with Trichophorum cespitosum, where high methane emission is attributed, presumably, to the influence of the plant community and not with to the different WTL, as described in the section above. In contrast, for floodplain wetlands, emission from the open sedge bog in the drying area (OO) was significantly lower (p = 0.02, N = 6) than from the flooded open swamp with Phalaris arundinacea (OC). This difference could be explained by changes in local ecohydrology and hydrochemistry after the road construction. Methane emission from ridges in GMKO1 and GMKO2 ecosystems (median 1.5 mg·m-2·h-1) exceeds by an order of magnitude the median of methane emission from middle taiga ridges Western Siberia (0.13 mg·m-2·h-1 according to [Kleptsova et al., 2010]). Due to flooding in the upstream area of the roads, WTL in ridges decreased compared to values typical for these ecosystems (mean ± standard deviation is 35 ± 14 cm according to [Kleptsova et al., 2010]). However, the grass-moss layer of the ridges did not degrade, and the methane emission from them turned out to be comparable with the emission from undisturbed ridges with the same WTL values (Fig. 2).

Methane emission from temperate and subarctic swamps is typically characterized by a lower optimal WTL value (ranging from -20 cm to -5 cm) compared to bogs [Bao et al., 2021]. Therefore, flooding of the Phalaris arundinacea swamp (OK) resulted in optimal conditions for methanogenesis in all three studied sites of this ecosystem with WTL ranging from -12 to 3 cm. The methane emission in each site of the Phalaris arundinacea swamp was higher than the third quartile for the entire sample obtained in this study. The open sedge bog (OO) separated from the rest of the floodplain by the road was characterized by a higher WTL (from -5 to 12 cm), far from optimal. In addition, the soil temperature in these ecosystems, located at a distance of 600 meters from each other, differed by 9-11°C in a peat layer from 0 to 20 cm. The same pattern was observed in sogra wetland, where temperature of the upper 20 cm in cross-cut bare peat was 6-8°C higher than in undisturbed site, separated from floodplain by access road. Thus, both the temperature and hydrological regimes contribute to the fact that the methane emission from the flooded floodplain open swamp (OK) is significantly higher than from the floodplain bog in the drying area (OO point). A similar pattern was observed for the treed floodplain swamp (SP and SE points, respectively).

The concentration of DOC in the water of natural and disturbed ecosystems of the low ryam was significantly higher than in the hollow of the ridge-hollow complex (p < 0.01, N = 5). The same pattern was observed for Canadian wetlands and was explained by the fact that DOC production occurs mainly in the aeration zone above the WTL. Since in ryams and ridges WTL it is higher than in hollows, the rate of plant litter decomposition is twice as high as in hollows (Moore, 2009). The higher rate of decomposition can explain both the higher EC (faster mineralization) and the lower pH (higher acidogenesis) in the low ryam. It is noteworthy that during the disturbance and subsequent recovery of the vegetation in the ryam, the concentration of DOC in the peat pore water increased by almost one and a half times, while in the hollow of the ridge-hollow complex it did not change considerably compared to the value in undisturbed wetland ecosystem.

Conclusion. Measurements of methane emission from wetlands of the West Siberian middle taiga disturbed during oil production and its physicochemical and biological factors showed that several of these ecosystems are intensive sources of this greenhouse gas. Although this is only a snapshot taken at the end of June 2021, and it is necessary to study the seasonal dynamics of the methane flux for more reliable conclusions, several indicators of methane emission hot spots could be suggested. Presence of ruderal plants such as Eriophorum vaginatum and Trichophorum cespitosum marks such a hot spots throughout different ecosystems. Ecosystem-specific range of WTL optimal for methane emission could also be a reliable indicator of these hot spots. Response of methane emission to the construction of roads depends on type of wetland ecosystems. In raised bogs, hollows in the upstream area emit less methane than undisturbed ecosystems, while in the downstream area emission is higher. Emission from ridges in flooded ridge-hollow complexes increases with the decrease of the WTL in them, similarly to natural undisturbed ridges. Nutrient-rich floodplain swamps response differently to changes in the hydrological regime. The emission of methane from open and forested swamps in the drying area is lower than from flooding area. This is explained not only by different WTL optimums for methane emission between bogs and swamps but also differences in temperature (6-11°С) of the surface organic-rich layers of floodplain wetlands in the flooding area compared to drying area. The methane emission from heavy vehicle tracks in low ryam is driven by the change in WTL relative to its optimum for methane emission from raised bogs.

Environmental Dynamics and Global Climate Change. 2022;13(3):142-155
pages 142-155 views

Estimation of carbon fluxes in agrolandscapes of Central Chernozem zone by simulation modelling

Suhoveeva O.E., Karelin D.V.


Две имитационные модели углеродного цикла в пахотных почвах – DNDC и RothC – верифицированы по данным длительного мониторинга дыхания почвы на Курской биосферной станции. Они применены для воспроизведения динамики органического углерода в почве, ее дыхания и чистого экосистемного обмена в агроландшафтах Курской области за 1990-2021 гг. По результатам модельных экспериментов получено, что пахотные черноземы теряют 241-423 кг С га-1 год-1 органического углерода, их дыхание в зависимости от возделываемой культуры варьирует от 3386 до 8434 кг С га-1 год-1, кроме того агроэкосистемы способны поглотить 487-1312 кг С га-1 год-1 за счет накопления в фитомассе. Результаты RothC обусловлены климатическими факторами, преимущественно температурой, тогда как выходные данные DNDC отличаются видоспецифичностью для каждой культуры.

Environmental Dynamics and Global Climate Change. 2022;13(3):156-170
pages 156-170 views


Monitoring of protected fungi species by methods of modern information technologies

Svetasheva T.Y.



The emergence of smart Internet resources and the improvement of electronic mobile devices have proved to be very useful for performing various scientific applied tasks, for example, for documenting biological observations in nature.The most significant are open access online platforms that accumulate information about biodiversity and provide it to everyone, for example: Global Biodiversity Information Facility, The Biodiversity Heritage Library, the multifunctional network storage of biological material National Depository Bank of Live Systems"Noah's Ark" etc. Of particular interest are resources that combine, on the one hand, a platform for collecting scientific data on biodiversity, and, on the other hand, a means of communication between people who collect and analyze this data, including projects that are often presented as "citizen science", for example: Mushroom Observer [Wilson, Hollinger et al. 2006-present], iNaturalist [iNaturalist, 2022]. The most popular resource among nature lovers is iNaturalist [iNaturalist, 2022], which is based on the concept of mapping and sharing observations of biodiversity around the world.At the moment, iNaturalist cannot be considered as a good mobile tool for identifying fungi in the field as well as a reliable way to determination based on photographs with the help of experts, since in most cases many different characters (including microstructures) are needed for accurate identification, and photographs of fruit bodies are clearly insufficient.Nevertheless, the program can be successfully used for the certain tasks in the study of fungi[Filippova et al., 2022; Sheehan, 2021].


  1. Photodocumentation and mapping of finds. In general, it is suitable for any find of fungal species. However, the implementation of this task is most appropriate in the case of working with rare and well-recognized species from photographs.
  2. Accumulation of observations of a designated group of species in any designated area, using filters or organizing special project inside iNaturalist, for example Funga of Tula Oblast [Funga…, 2021], FunDiS West Coast Rare Fungi Challenge [FunDis, 2021].
  3. Revealing of new species localities through the activities of amateur naturalists, as well as by involving students, schoolchildren and their parents in posting data and discussing findings.
  4. Organizing the specimen collection based on the obtained coordinates of the finds.Thanks to the data on new locations, it is easy to organize special expeditions with students or schoolchildren to "hot spots", or to involve amateurs to collection of specimens.
  5. Use as a database of finds, excursion routes, geobotanical descriptions of sample plots, as well as a kind of repository of "voucher" photographs
  6. Monitoring the appearance of fruiting bodies (phenology) of species confidently identified from photographs



  1. Number of photographic observations of rare species.
  2. Total number of observed rare species.
  3. The level of "observability-recognition" of various species in the field and at the photographs (and the possibility of monitoring).
  4. Spatial distribution of populations in the region.
  5. Abundance of fruiting bodies.
  6. Phenology of fruiting.
  7. The ecology of the finds and the state of habitats (the latter can be assessed indirectly, by the remoteness and surroundings of collection points; for example, if the point is located deep in a hard-to-reach forest area, then there is a high probability that the population of the species will be preserved good [Aurantiporus…, 2022].
  8. Number of observers, including permanent and enthusiastic ones, who can be involved in the registration of finds of protected species.

For an example of how this works, here are the results of monitoring protected species in the Tula Oblast using iNaturalist during vegetation season in 2021: 1) about 130 photographic observations of protected mushroom species were received; 2) the total number of observed species listed in the Red Data Book of the Tula Oblast [2010] is 31. Information about most of them was included in the GBIF; 3) new locations were found for 18 protected species; 4) new information about the habitats of rare species has been obtained; 5) rare species not previously recorded in the region were found–they are candidates for the next edition of the Red Data Book (for example, Lycoperdonmammiforme Pers. [Lycoperdon…, 2022], Holwayamucida (Schulzer) Korf &Abawi [Holwaya…, 2022]; 6) 26 observers recorded findings of rare mushroom species.Special project “Red Data Book – Fungi of Tula Oblast” was organized based on iNaturalist-platform.


The use of the iNaturalist intellectual online platform as a modern tool for studying the fungal biodiversity shows that it can help to solve a number of important tasks in the accumulation of photographic, cartographic, phenological and ecological data, as well as to attract a wide range of amateurs to learn and investigate fungi. Based on the first experience, it can be certainty said that the most significant and reliable data obtained due to monitoring of rare and protected fungal species, carried out as a part of project “Red Data Book - Fungi of the Tula Oblast” [2021], organized on the iNaturalist platform. During one season in 2021 preceded the release of the second edition of the Red Data Book of the Tula Oblast: lichens and fungi [2021], more than 130 photographic observations of 31 protected species of fungi were obtained, new locations were discovered for 18 species, some rare species were revealed as “new” for the region, new information about ecology and phenology was obtained. All data were considered in the released second edition of the Red Data Book. The results of the work continued in 2022 and also planned for the future will be taken into account in the next third edition of the book.

To achieve better results, it is necessary to organize a systematic approach to monitoring in iNaturalist, providing the active involvement of amateurs and biologists in photo documentation and identification of fungi finds, as well as the development of special methods for obtaining the most informative photo observations. All this, together with traditional methods of biodiversity research, will contribute to displaying an adequate picture of the distribution and occurrence of rare fungal species in the region.

Environmental Dynamics and Global Climate Change. 2022;13(3):171-178
pages 171-178 views

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies