The stable carbon isotope signature of methane produced by saprotrophic fungi

Methane (CH₄) is the most abundant organic compound in the atmosphere and is emitted from many biotic and abiotic sources. Recent studies have shown that CH₄ production occurs under aerobic conditions in eukaryotes, such as plants, animals, algae, and saprotrophic fungi. Saprotrophic fungi play an important role in nutrient recycling in terrestrial ecosystems via the decomposition of plant litter. Although CH₄ production by saprotrophic fungi has been reported, no data on the stable carbon isotope values of the emitted CH₄ (δ¹³C-CH₄ values) are currently available. In this study, we measured the δ¹³C values of CH₄ and carbon dioxide (δ¹³C-CO₂ values) emitted by two saprotrophic fungi, Pleurotus sapidus (oyster mushroom) and Laetiporus sulphureus (sulphur shelf), cultivated on three different substrates, pine wood (Pinus sylvestris), grass (mixture of Lolium perenne, Poa pratensis, and Festuca rubra), and corn (Zea mays), which reflect both C₃ and C₄ plants with distinguished bulk δ¹³C values. Applying Keeling plots, we found that the δ¹³C source values of CH₄ emitted from fungi cover a wide range from −40 to −69 mUr depending on the growth substrate and fungal species. Whilst little apparent carbon isotopic fractionation (in the range from −0.3 to 4.6 mUr) was calculated for the δ¹³C values of CO₂ released from P. sapidus and L. sulphureus relative to the bulk δ¹³C values of the growth substrates, much larger carbon isotopic fractionations (ranging from −22 to −42 mUr) were observed for the formation of CH₄. Although the two fungal species showed similar δ¹³CH₄ source values when grown on pine wood, δ¹³CH₄ source values differed substantially between the two fungal species when they were grown on grass or corn. We found that the source values of δ¹³CH₄ emitted by saprotrophic fungi are highly dependent on the fungal species and the metabolized substrate. The source values of δ¹³CH₄ cover a broad range and overlap with values reported for methanogenic archaea, the thermogenic degradation of organic matter, and other eukaryotes.

1 Introduction

Methane (CH₄) is an important greenhouse gas that is emitted by several abiotic sources (e.g. fossil fuel, biomass burning, and geological processes) and biotic sources (e.g. wetlands, agriculture and waste, and fresh waters) to the atmosphere (Kirschke et al., 2013; Saunois et al., 2016, 2020). In the past, biotic CH₄ production has been attributed exclusively to strictly anaerobic microorganisms, such as methanogens, that are ubiquitous in wetlands, rice paddies, landfills, and the intestines of termites and ruminants (Kirschke et al., 2013). The discovery of CH₄ emissions from dead and living plants under oxic conditions (Keppler et al., 2006, 2009) paved the way for the search for new biogenic CH₄ sources. Since then, several previously unknown CH₄ sources have been discovered, including the endothelial cells of rat liver (Boros and Keppler, 2019; Ghyczy et al., 2008), plant cell cultures (Wishkerman et al., 2011), marine algae (Klintzsch et al., 2019; Lenhart et al., 2016), marine and terrestrial cyanobacteria (Bižić et al., 2020), humans (Keppler et al., 2016), and saprotrophic fungi (Lenhart et al., 2012).

Fungi play a central role in ecosystems by decomposing organic matter, thereby recycling formerly bound carbon and nutrients (Grinhut et al., 2007). This process is especially important in forests where fungi are essential for wood decay and have a great impact on the carbon and nitrogen cycles (Ralph and Catcheside, 2002). White rot fungi (e.g. Trametes versicolor or Pleurotus ostreatus) are able to decompose the chemically complex structural component lignin, whereas brown rot fungi (e.g. Serpula lacrymans or Gloeophyllum trabeum) mainly metabolize cellulose and hemicellulose (Ten Have and Teunissen, 2001; Leonowicz et al., 1999; Valášková and Baldrian, 2006). Fungi have already been determined to be involved in the synthesis of CH₄ during wood decay (Beckmann et al., 2011; Mukhin and Voronin, 2007, 2008) via the breakdown of large macromolecules to smaller molecules, thereby providing bacteria and archaea with essential substrate. Elevated levels of CH₄ were found in fungus-infected wood stems with oxygen concentrations ranging from 1 % to 14 % (Hietala et al., 2015). Here, CH₄ production was associated with anoxic microsites in the xylem, indicating that at least part of the CH₄ was produced by methanogenic archaea. Nevertheless, Lenhart et al., 2012 demonstrated that basidiomycetes are able to produce CH₄ under aerobic conditions without the presence of methanogenic archaea. Therefore, fungi might be an underestimated source of CH₄ in the global CH₄ cycle.

Stable carbon isotopes (expressed as δ¹³C values) have often been used to investigate sources and sinks of CH₄ on the global scale (Whiticar, 1993). As different CH₄ sources have characteristic δ¹³C values, δ¹³C-CH₄ values might be used to quantify the individual contributions of various sources regionally and/or globally (Dlugokencky et al., 2011; Hein et al., 1997; Nisbet et al., 2016; Quay et al., 1999; Tyler, 1986; Whiticar, 1999). The short lifetime of CH₄ in the atmosphere (from 9.7±1.5 to 11.2±1.3 years; Naik et al., 2013; Prather et al., 2012; Voulgarakis et al., 2013) assures that global isotopic δ¹³C-CH₄ patterns represent the average of recent inputs by various sources and allows for the quantification of respective source strengths (Mikaloff Fletcher et al., 2004a, b).

Additionally, stable isotopes provide information about the formation processes of CH₄. Traditionally, three formation categories of δ¹³C-CH₄ values have been identified: biogenic, with typical δ¹³C-CH₄ values ranging from $\sim -\mathrm{55}$ to −70 mUr; thermogenic, with typical δ¹³C-CH₄ values ranging from $\sim -\mathrm{25}$ to −55 mUr; and pyrogenic, with typical δ¹³C-CH₄ values ranging from $\sim -\mathrm{13}$ to −25 mUr (Kirschke et al., 2013). However, stable isotope values of recently identified CH₄ sources, i.e. human CH₄ emissions (−56 to −95 mUr; Keppler et al., 2016), plant-derived CH₄ (−52 to −69 mUr; Keppler et al., 2006), and abiotic UV-induced CH₄ formation by plants (−52 to −67 mUr; Vigano et al., 2009) also need to be considered.

In this study, we investigated the stable carbon isotope source signatures of CH₄ and CO₂ released by the two basidiomycetes Pleurotus sapidus (white rot fungus) and Laetiporus sulphureus (brown rot fungus). Both fungi were cultivated under sterile conditions on three different substrates (pine wood, grass, and corn) with varying bulk δ¹³C values. We examined the influence of fungal species and growth substrate on δ¹³C-CH₄ and δ¹³C-CO₂ values and compared the δ¹³C-CH₄ values from the two fungal species with those of other known sources reported in the literature.

2 Material and methods

2.1 Selected fungi

P. sapidus (Pleurotaceae, DSMZ 8266) and L. sulphureus (Polyporacaeae, DSMZ 1014) were chosen for this experiment because of their capability to emit CH₄ (Lenhart et al., 2012), their ecological and physiological characteristics (P. sapidus is a white rot fungus and L. sulphureus is a brown rot fungus), and their well-established practical handling under laboratory conditions.

2.2 Cultivation of fungi and incubation experiments

Pine wood (Pinus sylvestris), grass (mixture of Lolium perenne, Poa pratensis, and Festuca rubra) and corn (Zea mays) were selected as growth substrates. Pine wood was chosen to investigate if white rot and brown rot fungi differ with respect to the δ¹³C-CH₄ and δ¹³C-CO₂ values released during wood decay. Therefore, dead pine wood branches were collected from the forest floor and shredded to small wood chips with a length of about 5 cm (Natura 1800L; Gloria, Witten, Germany). The wood chips were dried at 60 ^∘C for 48 h and stored in a flask (WECK GmbH, Hanau, Germany). Grass (C₃ plant) and corn (C₄ plant) were selected because of their different stable isotope values. As the metabolic pathway for carbon fixation is biochemically different in C₃ and C₄ plants, plant biomass differs with respect to δ¹³C values, which, in turn, might lead to different δ¹³C values of CH₄ and CO₂ released by fungi. Therefore, typical garden lawn was manually cut, dried at 70 ^∘C, and stored in a flask. The corn substrate consisted of conventional corn flour.

The substrates were autoclaved, filled into 2.7 L flasks (WECK GmbH, Hanau, Germany), and inoculated with pure fungal submerged cultures under sterile conditions following Lenhart et al. (2012). After the addition of the fungi, the flasks were closed with lids and a rubber band sealing. To allow gas exchange during the fungal growth period (about 2 weeks), a hole in the centre of every lid was fitted with a cotton stopper. Before the start of the incubation experiments, the flasks were aerated under sterile conditions in order to start the incubation at atmospheric CH₄ mixing ratios. Additionally, to create an airtight seal, the flask's cotton stoppers were replaced by sterile silicone stoppers (Saint-Gobain Performance Plastics, Charny, France).

For the incubation experiments, P. sapidus and L. sulphureus were incubated on the three substrates, while uninoculated substrates were also incubated as control treatments. Before the incubation experiments, the substrates were sterilized by autoclaving at 121 ^∘C and 2 bar pressure for 20 min. The incubation experiments were conducted using three replicates per treatment. The duration of the incubation accounted for up to 40 h. All incubations were conducted at room temperature (23±1.5 ^∘C). At every sampling point, 40 mL of air was taken from the flasks for gas concentration measurements and an additional 40 mL was taken for δ¹³C-CH₄ stable isotope ratio mass spectrometry (IRMS) analysis. The gas samples were taken with airtight 60 mL PE syringes (Plastipak, BD, Franklin Lakes, USA) and transferred into 12 mL evacuated Exetainer vials (Labco, High Wycombe, UK). Subsequently, a volume of atmospheric air equivalent to the volume of the removed sample was added into each flask directly after sampling. Mixing ratios and stable isotope values of CH₄ were corrected according to the dilution.

When calculating the fungal CH₄ and CO₂ production rates, we subtracted substrate-derived CH₄ and CO₂ production rates (determined using the control treatments) from the respective fungi-containing samples. Additionally, only sample points showing a linear increase in CH₄ and CO₂ were considered in the calculation of the fungal production rates.

To account for differences in the metabolic activity of the fungi, we additionally measured respiration rates, assuming that metabolic activity correlates with respiration and, therefore, the CO₂ emissions of the fungi. Hence, we related fungus-derived CH₄ emissions to respiration by calculating the CH₄:CO₂ emission ratio.

2.3 Analysis of CH₄ and CO₂ via gas chromatography

Samples were analysed using a gas chromatograph (GC, Bruker Greenhouse Gas Analyser 450-GC) equipped with a flame ionization detector (FID) and an electron capture detector (ECD) for the detection of CH₄ and CO₂ respectively. The detector temperatures were set at 300 ^∘C (FID) and 350 ^∘C (ECD). Five reference gases (Deuste Steininger GmbH) were used to calibrate the GC system. The reference gases were in the range from 1 ppmv (parts per million by volume) to 21 and from 304 to 40 000 ppmv for CH₄ and CO₂ respectively. Gas peaks were integrated using Galaxie software (Varian Inc., Palo Alto, CA, USA).

2.4 Definition of δ values and isotope apparent fractionation

In this paper, all stable carbon isotope ratios are expressed in the conventional “delta” (δ) notation, meaning the relative difference of the isotope ratio of a substance from the standard substance Vienna Peedee Belemnite (V-PDB):

$$\begin{array}{}\text{(1)}& {\mathit{\delta }}^{\mathrm{13}}\mathrm{C}={\displaystyle \frac{{\left(\frac{{}^{\mathrm{13}}\mathrm{C}}{{}^{\mathrm{12}}\mathrm{C}}\right)}_{\mathrm{sample}}}{{\left(\frac{{}^{\mathrm{13}}\mathrm{C}}{{}^{\mathrm{12}}\mathrm{C}}\right)}_{\text{V-PDB}}}}-\mathrm{1}\end{array}$$

The apparent fractionation (ε_app) between fungal δ¹³C-CH₄ or δ¹³C-CO₂ values and the δ¹³C values of the substrates was calculated according to Eq. (2):

$$\begin{array}{}\text{(2)}& {\mathit{\epsilon }}_{\mathrm{app}}{\mathrm{CH}}_{\mathrm{4}}\mathrm{or}{\mathrm{CO}}_{\mathrm{2}}={\displaystyle \frac{({\mathit{\delta }}^{\mathrm{13}}\mathrm{C}+\mathrm{1}{)}_{\mathrm{fungal}{\mathrm{CH}}_{\mathrm{4}}\mathrm{or}{\mathrm{CO}}_{\mathrm{2}}}}{({\mathit{\delta }}^{\mathrm{13}}\mathrm{C}+\mathrm{1}{)}_{\mathrm{substrate}}}}-\mathrm{1}\end{array}$$

We follow the proposal of Brand and Coplen (2012) and use the term “urey” (Ur) as the isotope delta unit, in order to conform with the guidelines for the International System of Units (SI). Hence, isotope delta values that were formerly given as −70 ‰ are expressed as −70 mUr.

2.5 Measurements of δ¹³CH₄ and δ¹³CO₂ values

Stable carbon isotope values of CH₄ and CO₂ were measured using a continuous flow isotope mass spectrometry system (CF-IRMS). A HP 6890N GC (Agilent, Santa Clara, USA) was linked to a pre-concentration unit for CH₄ measurements and an A200S autosampler (CTC Analytics, Zwingen, Switzerland) for CO₂ analysis. The GC was equipped with a CP-PoraPLOT Q capillary column (27.5 m×0.25 mm i.d., film thickness 8 µm; Varian, Palo Alto, USA). The GC was operated with an injector temperature of 200 ^∘C, an isothermal oven temperature of 30 ^∘C, split injection (10:1), and a constant carrier gas flow of 1.8 mL min⁻¹ (methane-free helium). The GC was coupled to a Delta^PLUSXL isotope ratio mass spectrometer (ThermoQuest Finnigan, Bremen, Germany) via an oxidation reactor and a GC Combustion III interface (ThermoQuest Finnigan, Bremen, Germany). The oxidation reactor was employed with the following properties: a ceramic tube (Al₂O₃; length 320 mm, 1.0 mm i.d.) with Ni∕Pt wires inside activated by oxygen and a reactor temperature of 960 ^∘C.

For CH₄ measurements with the pre-concentration unit, headspace gas samples were transferred to an evacuated 40 mL sample loop. Methane was trapped on HayeSep D, separated from other compounds by the GC, and then introduced into the IRMS system via an open split. The monitor gas was carbon dioxide of high purity (carbon dioxide 4.5, Messer Griesheim, Frankfurt, Germany) with a known δ¹³C value of −23.6 mUr (calibrated at the Max Planck Institute for Biogeochemistry in Jena, Germany). All δ¹³C values were corrected using two CH₄ reference standards (Isometric instruments, Victoria, Canada) with δ¹³C values of $-\mathrm{23.9}\pm \mathrm{0.2}$ and $-\mathrm{54.5}\pm \mathrm{0.2}$ mUr that were calibrated against International Atomic Energy Agency (IAEA) and National Institute of Standards and Technology (NIST) reference substances. The normalization of the sample values was carried out according to Paul et al. (2007).

2.6 Bulk isotope analysis of fungal substrates

Stable carbon isotope values of the bulk substrate were measured using an FlashEA 1112 elemental analyser (Thermo Fisher Scientific, Germany) coupled to a Delta V IRMS (Thermo Fisher Scientific, Germany). Therefore, 0.06 mg of the substrate was put into a tin cup and combusted in the elemental analyser. The resulting gases were separated in a GC by a CP-PoraPLOT Q capillary column (27.5 m×0.25 mm i.d., film thickness 8 µm; Varian, Palo Alto, USA) and then reached the Delta V IRMS via a Conflo IV universal continuous flow interface (Thermo Fisher Scientific, Germany). Isotope values were corrected using USGS 40 and USGS 41 standards.

2.7 Determination of isotopic source signature of CH₄ and CO₂ applying Keeling plots

For the determination of δ¹³C source values of CH₄ and CO₂, the Keeling plot method was used (Keeling, 1958; Pataki et al., 2003):

$$\begin{array}{}\text{(3)}& {{\mathit{\delta }}^{\mathrm{13}}\mathrm{C}}_{\mathrm{a}}=c_{\mathrm{b}}\left({{\mathit{\delta }}^{\mathrm{13}}\mathrm{C}}_{\mathrm{b}}-{{\mathit{\delta }}^{\mathrm{13}}\mathrm{C}}_{\mathrm{s}}\right)\left({\displaystyle \frac{\mathrm{1}}{c_{\mathrm{a}}}}\right)+{{\mathit{\delta }}^{\mathrm{13}}\mathrm{C}}_s,\end{array}$$

where c_a is the mixing ratio of CH₄∕CO₂ in the headspace, δ¹³C_a is the δ¹³C value of CH₄∕CO₂ in the headspace, c_b is the mixing ratio of background CH₄∕CO₂, δ¹³C_b is the δ¹³C value of background CH₄∕CO₂, and δ¹³C_s is the δ¹³C source value of the CH₄∕CO₂. For a more detailed description of the application of Keeling plots for the determination of the CH₄ source signature, we refer to the study by Keppler et al. (2016).

δ¹³C-CH₄ source signatures were calculated following the Keeling plot method for each flask. Results of the Keeling plots are then given as the arithmetic mean of the three individual flasks per treatment with their standard deviations (n=3).

The δ¹³C-CH₄ source signatures of each flask of P. sapidus and L. sulphureus grown on pine were corrected for CH₄ emissions and δ¹³C-CH₄ values of the “pine” control samples using the following mass balance approach:

$$\begin{array}{}\text{(4)}& \begin{array}{rl}& {\mathit{\delta }}^{\mathrm{13}}{\mathrm{C}}_{\mathrm{fungi}\mathrm{corrected}}=\\ & {\displaystyle \frac{\left(P{\left({\mathrm{CH}}_{\mathrm{4}}\right)}_{\mathrm{fungi}}\cdot {\mathit{\delta }}^{\mathrm{13}}{\mathrm{C}}_{\mathrm{fungi}}\right)-(P{\left({\mathrm{CH}}_{\mathrm{4}}\right)}_{\mathrm{pine}}\cdot {\mathit{\delta }}^{\mathrm{13}}{\mathrm{C}}_{\mathrm{pine}})}{(P{\left({\mathrm{CH}}_{\mathrm{4}}\right)}_{\mathrm{fungi}}-P{\left({\mathrm{CH}}_{\mathrm{4}}\right)}_{\mathrm{pine}})}},\end{array}\end{array}$$

where P(CH₄)_{fungi/pine wood} is the CH₄ emitted by the fungi or pine wood, and δ¹³C_{fungi/pinewood} is the δ¹³C-CH₄ source signature of the fungi or pine wood derived from the Keeling plots. Corrected δ¹³C-CH₄ source values for P. sapidus and L. sulphureus are given as the arithmetic mean of the three individual flasks per treatment with their standard deviations (n=3).

The determination coefficient (R²) of the Keeling plots showed values higher than 0.93 except for P. sapidus grown on grass (R²=0.51). The lower R² value for P. sapidus grown on grass is probably a result of the marginal changes in the δ¹³C-CH₄ values due to the small increase in the CH₄ mixing ratio compared with the background CH₄ mixing ratio. Therefore, the low R² does not necessarily indicate a weaker relationship between the CH₄ mixing ratio and the δ¹³C-CH₄ value.

2.8 Statistics

Mixing ratios and production rates of CH₄, CO₂, δ¹³C-CH₄ values, and δ¹³C-CO₂ values as well as δ¹³C source values are presented as the arithmetic mean of three independent replicates with their standard deviations (n=3). Linear regression analysis, the arithmetic means, and their standard deviations were calculated using Microsoft Excel (Microsoft Excel for Office 365 MSO). Two-way analysis of variance (ANOVA) tests (SigmaPlot 12.2.0.45, USA) were carried out to test for species- and substrate-related effects on the δ¹³C-CH₄ and δ¹³C-CO₂ source values for each treatment. Differences at the p<0.05 level were referred to as significant.

3 Results and discussion

In this section, we firstly present the results of CH₄ and CO₂ production from the two fungal species grown on the three different substrates. This includes emission rates of CH₄ and CO₂ from the control treatments of pine wood, grass, and corn as well as the molar ratio of CH₄ and CO₂. Secondly, we then present the respective stable isotope values measured for CH₄ and CO₂ during the incubation experiments and calculate the stable isotope source values of CH₄ and CO₂ released by the fungi applying Keeling plots. We then compare these values with stable carbon isotope values of the bulk organic matter by calculating the apparent fractionation. Finally, we compare δ¹³C source values of fungus-derived CH₄ with known values for other CH₄ sources from the literature.

Figure 1 Mixing ratios of CH₄ and CO₂ of P. sapidus (a, c) and L. sulphureus (b, d) grown on pine wood, grass, and corn. Mixing ratios are presented as mean values with their standard deviation (n=3).

3.1 Release of CH₄ and CO₂ from P. sapidus and L. sulphureus

All incubation experiments in which fungi were grown on different substrates showed a significant increase in CH₄ compared with the respective substrate control (Fig. 1a, c). Calculated emission rates for CH₄ and CO₂ are presented in Table 1. L. sulphureus grown on grass (7.5±1.3 nmol h⁻¹) showed the highest emission rate of CH₄, followed by L. sulphureus grown on pine (6.2±0.3 nmol h⁻¹), P. sapidus grown on corn (4.4±1.9 nmol h⁻¹), L. sulphureus grown on corn (2.6±0.1 nmol h⁻¹), P. sapidus grown on pine (2.5±0.2 nmol h⁻¹), and P. sapidus grown on grass (1.4±0.5 nmol h⁻¹). Please note that CH₄ and CO₂ emission rates are not related to fungal biomass. Therefore, differences in the emission rates might be due to varying fungal biomass of the subsamples. Instead, CH₄ production was related to CO₂ production by determining the molar emission ratio between CH₄ and CO₂ (µmol CH₄ : mol CO₂). Thus, CO₂ production reflects the amount of fungal biomass and is also an indicator of the metabolic activity of the fungi.

The control flasks did not show significant changes in their CH₄ and CO₂ mixing ratios over time, except for CH₄ in pine wood controls (1.3±0.1 nmol h⁻¹). However, small CH₄ emission rates of 0.25±0.01 nmol h⁻¹ were observed in the control flasks of corn, and the CH₄ mixing ratio slightly decreased over time in the grass control ($-\mathrm{0.05}\pm \mathrm{0.04}$ nmol h⁻¹). Whilst the pine wood and corn control flasks showed a small increase in the CH₄ mixing ratio, they did not show an increase in the CO₂ mixing ratios. These data rule out contamination by microbial heterotrophs, as this would cause a measurable CO₂ increase within the flasks. The CH₄ increase in the substrate controls might be attributed to CH₄ release by dead plant material, as was already shown by Keppler et al. (2006) and Vigano et al. (2009). Within the scope of these experiments, no analytic test for microbial contamination was conducted. Nevertheless, using three different methods (fluorescence in situ hybridization, FISH; confocal laser scanning microscopy, CLSM; and quantitative real-time polymerase chain reaction), Lenhart et al. (2012) clearly showed that no methanogenic archaea were present in the same method of cultivation of fungi and incubation experiments that were performed in this study. Furthermore, CH₄ and CO₂ release and the CH₄:CO₂ emission ratios in our incubations are similar to the experiments of Lenhart et al. (2012) and do not indicate microbial contamination. Therefore, we assume that no contamination with bacteria or methanogenic archaea was present in our investigations.

For P. sapidus grown on corn and L. sulphureus grown on grass, no further linear increase in CH₄ was observed after 22 and 10 h respectively. This might be due to the reduced decay of organic matter and slower fungal metabolism owing to higher CO₂ and lower O₂ mixing ratios.

A drastic increase in CO₂ mixing ratios relative to the controls was observed in all flasks containing fungi (Fig. 1b, d). The CO₂ emission rates are shown in Table 1. CO₂ production rates ranged from 176±4 to 2910±410 µmol h⁻¹ for P. sapidus grown on grass and P. sapidus grown on corn respectively. These highly variable CO₂ production rates might reflect different fungal biomass and metabolic activity (mineralization of organic matter). In the control treatments, tiny increases in the CO₂ mixing ratio were detected ranging from 0.64±0.12 to 0.91±0.14 µmol h⁻¹. Only one flask (corn control) showed a somewhat higher increase in CO₂ (7.76 µmol h⁻¹), which was most likely caused by microbial contamination of the flask. However, no increase in the CH₄ mixing ratio was detected (see Supplement). Therefore, this control flask was excluded from further calculations.

Mean CH₄ and CO₂ emission rates and CH₄:CO₂ emission ratios of all treatments are presented in Table 1. Higher ratios indicate a higher CH₄ production during decay of the substrates. Therefore, both fungal species and substrate affect the CH₄:CO₂ emission ratio (p<0.001). For P. sapidus, CH₄:CO₂ emission ratios are more variable (1.4 to 8.0 µmol CH₄/mol CO₂) compared with L. sulphureus (6.7–9.6 µmol CH₄/mol CO₂). This variation might be due to differences in the fungi's enzyme sets required for organic matter decay, as P. sapidus is a white rot fungus and L. sulphureus is a brown rot fungus. At present, the biochemical pathways that lead to CH₄ are still unknown, although compounds such as the sulfur-bound methyl-group of methionine and glucose have been identified to act as carbon precursors of fungus-derived CH₄ (Lenhart et al., 2012).

Lenhart et al., 2012 found CH₄ : CO₂ ratios of fungi that ranged between 8 µmol CH₄/mol CO₂ and 17 µmol CH₄/mol CO₂, which is in the same order of magnitude as the CH₄:CO₂ ratios determined in this study. It should be noted that, for better comparability, the CH₄:CO₂ ratios of Lenhart et al. (2012; given in ppbv CH₄ : % CO₂) were converted to fit the CH₄:CO₂ ratio units used in this study (µmol CH₄ : mol CO₂).

Table 1 CH₄ and CO₂ production rates and molar CH₄:CO₂ emission ratios of the fungi incubated on different substrates. Values are presented as mean values of three independent replicates with their standard deviation (n=3), except for the control “corn” (n=2).

Figure 2 Stable carbon isotope values of CH₄ and CO₂ of P. sapidus (a, c) and L. sulphureus (b, d) grown on pine, grass, and corn. Values are presented as mean values with their standard deviation (n=3), except for δ¹³CO₂ values of L. sulphureus grown on corn (n=2).

3.2 Stable carbon isotope values of CH₄ and CO₂

Stable carbon isotope values of CH₄ and CO₂ measured from the incubation experiments are presented in Fig. 2. All incubations show a trend towards more negative δ¹³C-CH₄ values (less ¹³C) with time except for P. sapidus grown on corn, where a tendency towards more positive δ¹³C-CH₄ values was observed (Fig. 2a, b). During the incubation, δ¹³C-CH₄ values changed from $-\mathrm{47.7}\pm \mathrm{0.1}$ mUr (for the incubation of P. sapidus grown on pine/grass) and $-\mathrm{48.2}\pm \mathrm{0.1}$ mUr (for the incubation of P. sapidus grown on corn and L. sulphureus grown on pine/grass/corn) to $-\mathrm{53.0}\pm \mathrm{0.7}$ mUr (for P. sapidus grown on pine), $-\mathrm{48.7}\pm \mathrm{0.3}$ mUr (for P. sapidus grown on grass), $-\mathrm{45.8}\pm \mathrm{1.2}$ mUr (for P. sapidus grown on corn), $-\mathrm{55.1}\pm \mathrm{0.4}$ mUr (for L. sulphureus grown on pine), $-\mathrm{55.4}\pm \mathrm{0.4}$ mUr (for L. sulphureus grown on grass), and $-\mathrm{49.9}\pm \mathrm{0.4}$ mUr (for L. sulphureus grown on corn). The controls showed no significant shift in δ¹³C-CH₄ values except for the pine control, where an increase in the CH₄ mixing ratio along with more negative values of δ¹³C-CH₄ values occurred over time. This was accounted for when calculating the δ¹³C-CH₄ source signatures for P. sapidus grown on pine and L. sulphureus grown on pine (see Sect. 2.7).

The δ¹³C-CO₂ values showed a trend towards more negative values within the first 3–4 h of incubation (Fig. 2c, d). After this time, only minor changes in the δ¹³C-CO₂ values occurred. Final δ¹³C-CO₂ values of the incubation were $-\mathrm{24.9}\pm \mathrm{0.6}$ mUr (for P. sapidus grown on pine), $-\mathrm{28.6}\pm \mathrm{0.9}$ mUr (for P. sapidus grown on grass), $-\mathrm{12.0}\pm \mathrm{0.3}$ mUr (for P. sapidus grown on corn), $-\mathrm{24.1}\pm \mathrm{0.1}$ mUr (for L. sulphureus grown on pine), $-\mathrm{27.7}\pm \mathrm{0.5}$ mUr (for L. sulphureus grown on grass), and $-\mathrm{13.0}\pm \mathrm{0.5}$ mUr (for L. sulphureus grown on corn).

Table 2 Calculated δ¹³C-CH₄ and δ¹³C-CO₂ source signatures, δ¹³C values of the substrates, and ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$ and ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CO}}_{\mathrm{2}}}$. Values are presented as mean values with their standard deviation (n=3).

3.3 δ¹³C-CH₄ and δ¹³C-CO₂ source signatures of fungi

The δ¹³C-CH₄ source signatures determined via a Keeling plot analysis (Fig. 3) that ranged from $-\mathrm{69.2}\pm \mathrm{1.9}$ mUr (for L. sulphureus grown on grass) to $-\mathrm{39.8}\pm \mathrm{2.0}$ mUr (for P. sapidus grown on corn) are presented in Table 2. Average δ¹³C-CH₄ source signatures for each fungal species, considering all three substrates, are −52.6 mUr for P. sapidus and −61.3 mUr for L. sulphureus. These results suggest that the fungal species significantly influence the isotopic values of the emitted CH₄ (p<0.001). A possible explanation for this observation could be the different enzyme sets of both fungi that decompose different components of the growth substrates, as P. sapidus belongs to white rot fungi and L. sulphureus is a brown rot fungus. However, detailed investigations of the metabolic pathways leading to CH₄ formation were beyond the scope of this study.

Furthermore, a significant effect of the growth substrate on δ¹³C-CH₄ source signatures was observed (p<0.001). δ¹³C-CH₄ source signatures from P. sapidus were more positive compared with those of L. sulphureus when grown on grass (Δ=16.3 mUr) and corn (Δ=13.6 mUr) (Fig. 4). When grown on pine wood, δ¹³C-CH₄ source signatures were similar, with P. sapidus showing slightly more negative values ($\mathrm{\Delta }=-\mathrm{3.9}$ mUr). Methane emitted by both fungi grown on corn was generally more enriched in ¹³C (less negative δ¹³C-CH₄ source values) compared with the fungi grown on pine wood and grass. This might be easily explained by the δ¹³C values of the corn growth substrates (−11.7 mUr, which is typical for C₄ plants) being roughly 20 mUr less negative in their δ¹³C values compared with the C₃ plants, pine wood (−28.0 mUr) and grass (−31.5 mUr).

Figure 3 Keeling plots shown for P. sapidus (a) and L. sulphureus (b) grown on the three substrates. Sample points in the graphs are given as the arithmetic mean of the δ¹³C-CH₄ or δ¹³C-CO₂ values with their standard deviation (n=3) on the y axis and the arithmetic mean of the inverted mixing ratio of CH₄ or CO₂ with their standard deviation (n=3) on the x axis.

Figure 4 Calculated source signatures of δ¹³C-CH₄ values (a) and δ¹³C-CO₂ values (b) from P. sapidus, L. sulphureus as well as the δ¹³C values of the substrate. The data points represent the mean values of the individual Keeling plots with their standard deviation (n=3).

The comparison of calculated δ¹³C-CH₄ source signatures with measured bulk δ¹³C values of the substrates shows that CH₄ emitted by both fungi is generally depleted in ¹³C compared with the respective substrates (Fig. 4a). Based on these data, we further calculated the apparent fractionation (${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$) between the δ¹³C-CH₄ source signatures and the bulk δ¹³C values of the growth substrates. The apparent fractionation was calculated as no metabolic pathway for the formation of CH₄ in fungi is presently known; therefore, only the initial δ¹³C signatures of the substrates and the calculated δ¹³C-CH₄ source signatures of the fungi can currently be compared. The values of ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$ that range from −21.8 mUr (for P. sapidus grown on grass) to −42.2 mUr (for L. sulphureus grown on corn) are presented in Table 2. When grown on pine wood, ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$ values are similar for P. sapidus ($-\mathrm{38.4}\pm \mathrm{1.2}$ mUr) and L. sulphureus ($-\mathrm{34.4}\pm \mathrm{0.6}$ mUr). The differences in ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$ values between both fungal species are distinct when grown on grass (P. sapidus: $-\mathrm{21.8}\pm \mathrm{1.7}$ mUr; L. sulphureus: $-\mathrm{38.6}\pm \mathrm{2.0}$ mUr) and corn (P. sapidus: $-\mathrm{28.5}\pm \mathrm{2.0}$ mUr; L. sulphureus: $-\mathrm{42.2}\pm \mathrm{1.1}$ mUr).

The calculated δ¹³C-CO₂ source signatures of both fungi (Table 2) range from $-\mathrm{29.0}\pm \mathrm{0.5}$ mUr (for L. sulphureus grown on grass) to $-\mathrm{12.0}\pm \mathrm{0.3}$ mUr (for P. sapidus grown on corn). δ¹³C-CO₂ source signatures are in a similar range for both fungi for all three substrates. However, CO₂ emitted by L. sulphureus is slightly more depleted in ¹³C for all three substrates compared with P. sapidus. Hence, the effect of fungal species on the stable carbon isotope values of CO₂ is significant (p=0.008). Moreover, the substrates used were found to influence δ¹³C-CO₂ values significantly (p<0.001).

The δ¹³C-CO₂ source signatures of the fungi show only small deviations from the bulk δ¹³C values of the respective substrates (Fig. 4b). However, for both fungi grown on pine wood and grass, δ¹³C-CO₂ values are slightly less negative (a few mUr) compared with the bulk substrate. This observation is rather unexpected, as δ¹³C-CO₂ values are usually more negative with respect to δ¹³C values of growth substrates due to fractionation during metabolism (Bowling et al., 2008). However, when grown on corn δ¹³C-CO₂ source signatures from both fungi are more negative compared with the substrate, and calculated ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CO}}_{\mathrm{2}}}$ values (Table 2) are $-\mathrm{1.1}\pm \mathrm{0.3}$ mUr and $+\mathrm{4.6}\pm \mathrm{1.3}$ mUr for L. sulphureus grown on corn and P. sapidus grown on grass respectively.

The results of the incubation experiments show that there are distinct differences in the δ¹³C-CH₄ and δ¹³C-CO₂ values released by both fungi. While the δ¹³C-CO₂ source signatures are similar to the δ¹³C values of the substrate (with ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CO}}_{\mathrm{2}}}$ values of up to 4.6 mUr), the δ¹³C-CH₄ source signatures deviate strongly from the respective substrate, with ${\mathit{\epsilon }}_{\mathrm{app}{\mathrm{CH}}_{\mathrm{4}}}$ values of up to −42.2 mUr. This either indicates that metabolic pathways leading to the formation of CH₄ and CO₂ have different fractionation and/or that fungal CH₄ and CO₂ are derived from different precursor compounds of the respective substrate. The growth substrates used for this study (pine wood, grass, and corn) contain distinct amounts of cellulose, hemicellulose, lignin, and other compounds in different proportions (in contrast to only using pure glucose or cellulose as the growth substrate). Hence, the δ¹³C-CH₄ and δ¹³C-CO₂ source signatures depend on the specific metabolic pathways used by the fungal species as well as the chemical composition of the growth substrate. The selected fungi and the growth substrates used provide a first solid basis for the potential range of δ¹³C-CH₄ values that might occur in nature.

3.4 Fungal δ¹³C-CH₄ values compared with known CH₄ sources

Figure 5 compares the δ¹³C-CH₄ values emitted by fungi in relation to other known CH₄ sources in the environment that have been reported in the literature. The red bars indicate typical biogenic (formerly only considered to be produced by archaea) CH₄ sources with emissions from wetlands, ruminants, landfills, and rice paddies where δ¹³C-CH₄ values usually range from −85 to −40 mUr. Abiotic CH₄ sources (including thermogenic or pyrolytic processes) stemming from natural gas, coal mining, and biomass burning are characterized by less negative δ¹³C values usually ranging from −55 to −20 mUr. In addition, gas hydrates, which might be formed by both microbial and abiotic processes, cover a wide range of δ¹³C values (−29 to −73 mUr) depending on their formation mechanisms (Kvenvolden, 1995). The δ¹³C source signatures of plant-derived CH₄ have been reported to be in the range of −72 to −45 mUr (Keppler et al., 2006; Vigano et al., 2009) depending on their photosynthetic pathways (C₃, C₄, or CAM). Furthermore, there was a tendency towards more negative δ¹³C-CH₄ values when the respective plant was treated with UV radiation (Vigano et al., 2009). δ¹³C-CH₄ source signatures of humans, which might include formation by microbes in the gut as well as formation by cellular processes, show a rather wide range with values between −95 and −56 mUr (Keppler et al., 2016). The results of our experiments conducted with two fungal species and three different growth substrates provide a range of δ¹³C-CH₄ source values from −69 to −40 mUr. This range overlaps with other eukaryotic sources, most microbial CH₄ sources, and even some abiotic CH₄ sources such as natural gas or emissions from coal mining.

Figure 5 The range of δ¹³C-CH₄ values of microbial CH₄ sources (red), abiotic CH₄ sources (grey), eukaryotic CH₄ sources (green), atmospheric CH₄ (blue), and fungal CH₄ from this study (orange). The red and grey dashed bar indicates a mixture of microbial and abiotic CH₄ formation processes for gas hydrates (Kvenvolden, 1995). Data were taken from Brownlow et al. (2017), Keppler et al. (2006, 2016), Kvenvolden (1995), Nisbet et al. (2016), Quay et al. (1999), and Vigano et al. (2009).

4 Conclusions

This study provided the first analysis of stable carbon isotope values of CH₄ emitted by two saprotrophic fungi that were grown on three different substrates. δ¹³C-CH₄ and δ¹³C-CO₂ source values were found to be dependent on the fungal species as well as the substrates decomposed by the fungi. δ¹³C-CH₄ source values of the fungi were found to be in the range of −69 to −40 mUr and, therefore, overlap with δ¹³C-CH₄ values reported for other CH₄ sources such as methanogenic archaea, eukaryotes, and from abiotic CH₄ sources (e.g. natural gas and coal mining). Stable carbon isotope values of CH₄ in combination with flux measurements are often applied for a better understanding of regional and global CH₄ cycling. However, in recent years it has become clear that many biogenic CH₄ sources include complex CH₄ formation processes, resulting in different isotopic fractionation patterns depending on several biochemical and abiotic factors. Thus, studying ecosystems in which more than one major CH₄ source has to be expected (e.g. methanogenic archaea, fungi, cyanobacteria, or plants) becomes increasingly complicated, as distinguishing between each individual source based solely on stable carbon isotope values might be highly challenging. Therefore, additional tools are needed to better identify the sources but also to disentangle sources and sinks. In future research, stable hydrogen isotopic values of CH₄ (δ²H-CH₄ values) or even applications of clumped isotopes might prove to be suitable tools to better distinguish between different CH₄ sources and, thus, to better constrain the global CH₄ budget.