The increased frequency of forest fires decreases both the ability of forests to store C and the degree of permafrost recovery (Hoy et al. 2016). Therefore, effects of fire on SOM quality, microbial activity and permafrost thaw could have a significant effect on greenhouse gas emissions during fire intervals. Our results indicated that the proportional sizes of the most soluble fractions (water and ethanol) in the surface soil (5 cm depth) were in general smaller after fire and increased with time. However, changes were not consistent in the two deepest layers. It may be that the effects of fire do not reach to depths of 30 and 50 cm, although fire has clearly changed the active layer depth (Köster et al. 2017), exposing previously frozen soil at 50 cm to thaw. Also study by Shibata et al. (2003) noted that fire did not affect the water-extractable C in the mineral soil.
The different SOM fractions can be thought to represent different SOM pools with differing turnover times. These SOM pools are decomposing with different rates in the soil and can be roughly divided from fast to slow in following order: sugars, starches, simple proteins, crude proteins, hemicellulose, cellulose, fats, waxes, resins and lignins (Osman 2013). Also decomposition models, such as Yasso and CENTURY, often divide SOM into pools, based on their turnover times. Yasso divides decomposing material to extractives, celluloses, lignin-like materials, humus 1 and humus 2 (Liski et al. 2005). In these pools the water-and ethanol extractable SOM could be though to belong to the extractives pool with a decomposition rate of 0.48 year−1 (rates for conifer litter). The decomposition rate for cellulose is 0.30 year−1 and lignin-like compounds 0.22 year−1, while humus 1 pool has a decomposition rate of 0.012 year−1 and humus 2 pool 0.0012 year−1 (Liski et al. 2005). In CENTURY the pools are divided to active pool (turnover time of months to few years), slow pool (turnover time of 20–50 years) and stable pool (turnover time of 400–2000 years) (Century manual). For example, Bot and Benites (2005) have allocated different SOM groups to three pools: sugars, as easily decomposing, could be placed in the active cycling pool, while fats, waxes and cellulose represent the slow pool. Lignins, as resistant compounds, form the stable SOM pool (Bot and Benites 2005; Kutsch et al. 2009). Though these pools may not be straightforwardly comparable to the pools used in CENTURY, it can be deduced that there is a vast difference in the decomposition rates of these different SOM pools. Further, the degradability of a compound is affected by its molecular weight and structure: material with low molecular weight (e.g. sugars, aminoacids, phenols) is easier to decompose than material with high molecular weight (e.g. cellulose, lignin, cutin) (Cotrufo et al. 2013). SOM that is most readily available is characterised by its solubility to water (Marschner and Kalbitz 2003).
We observed no significant changes with time after fire in the insoluble fraction. In case of fire chronosequences, in an early succession forest (recently burnt) there may be a higher proportion of recalcitrant (charred) SOM (González-Pérez et al. 2004; Wardle et al. 2008) as the organic layer may have been at least partially burnt. In late succession stage forests, on the other hand, incoming plant material, such as evergreen needles and woody material, is generally less easily decomposable (Brassard and Chen 2006). In our previous study, conducted in the same areas as this study, we observed that the organic layer depth continued to increase several decades after fire (Köster et al. 2017). Also the vegetation cover, both biomass and species composition, was affected by time since fire (Table S2, Online Resource). The youngest fire area had visible ashy, bare patches of ground, no living trees, less mosses and ground vegetation mostly consisting of Equisetum sylvaticum L. The older areas FIRE46 and FIRE100 (Table S2, Online Resource) had more lichen, mosses (Sphagnum sp., Pleurozium sp), shrubs (Ledum groenlandicum Oeder, Vaccinium vitis-idaea L., V. Uliginosum and some Rubus camaemorus L.) and mature trees (Köster et al. 2017). The area FIRE25 was similar to these, but with some remaining unvegetated patches and Cladonia and Cladina lichens. These changes in vegetation cover affect the quality of incoming organic matter to soil, thus affecting also the different proportions of SOM fractions. This is because different species have differing decomposition rates. Such shrubs as Vaccinium vitis-idaea and Rubus camaemorus L. decompose relatively slowly (Nilsson and Wardle 2005), while Equisetum sp species might decompose faster (Marsh et al. 2000). Further, though mosses decompose slowly, they have been observed to advance decomposition of other species by keeping up moisture levels in the litter layer (Wardle et al. 2003). Thus, in both recently burnt and late succession stage forests, there are possibly more sources for recalcitrant SOM than in mid-succession forests, perhaps explaining why we observed no significant changes with time in the insoluble fraction. We detected a trend (at 5 cm depth) of increasing proportions of recalcitrant SOM in younger, more recently burnt areas, indicating a strong effect of fire on SOM quality. Thus, charred SOM could have a noticeable role at some point in time. However, in an early succession forest, the input of resistant material may also be counteracted by the easily decomposable plant material deriving from the herbaceous plant species in the early succession stage (Chen and Shrestha 2012) or perhaps from the decomposing root material.
In the labile fractions (water and ethanol) the most obvious changes were observed at 5 cm soil depth. FIRE3 and FIRE100 did not show differences in the size of the water-soluble fraction, but the middle-aged fire areas had higher fractions of water-soluble SOM. The similarity between FIRE3 and FIRE100 is probably related to the previously mentioned succession dynamics. Alternatively, there could be greater leaching, or loss as run-off, of water-soluble SOM in these areas compared to FIRE25 and FIRE46. In area FIRE3 there was probably less evapotranspiration than in older fire areas due to smaller transpiring leaf biomass. This could mean that a proportionally larger amount of water is moving down in the soil profile compared to the older forests, where vertical movement is also limited by the higher permafrost surface. Further, some pyrogenic compounds are actually water-soluble (Norwood et al. 2013) and might show in the water-soluble fraction in addition to sugars. However, this trend was different in the ethanol soluble fraction. Both FIRE3 and FIRE25 had smaller ethanol-soluble fractions than FIRE46 and FIRE100, meaning that waxes and fats form a greater proportion of SOM during the later succession. This is probably also related to changes in vegetation during the succession. In the later stage of forest succession, there is an increased biomass of coniferous trees and shrubs, with large amount of waxes in their cuticula, (Dickinson 1974; Brassard and Chen 2006), thus producing litter which increases the amount of fat and waxes in the SOM.
The fraction of insoluble SOM was higher in the 30 and 50 cm soil layers, which could be expected as deeper soils typically contains less readily decomposable SOM (Trumbore 2014). In addition, studies on black carbon have shown it to be easily translocated vertically in the soil and therefore it may have accumulated into subsoils (Dai et al. 2005; Rumpel et al. 2009). On the other hand, the ratios of SOM fractions are not only dependent on the formation of resistant compounds but are greatly affected by decomposers. Fungal species have an important role in degrading lignin (Waldrop et al. 2010). It has been found that if the fungal community becomes wiped out or reduced during the fire, the degradation of lignin will decrease (Waldrop et al. 2010), meaning that it could reside in the soil for a longer period. This could be apparent in the size of the insoluble SOM fraction for some time after the fire as Klason lignin found here is included in the recalcitrant fraction. For example, it takes several decades for the fungal biomass to recover after fire (Köster et al. 2016; Zhou et al. 2018). Yet we found that the length of time after fire had only a tendential, but insignificant, effect on the amount of insoluble and acid-soluble SOM, and can thus only speculate here about the role of fungi.
Our results show that the effects of fire on SOM are most prominent at the soil surface. The SOM fractions and isotopes showed very small, or no, differences between fire ages at 50 cm depth. This was further supported by the mixed effects model, where none of the predicting factors seemed to be significant and the only variable surviving to the best model was C/N ratio. Contrastingly, at both 5 and 30 cm depths the best model included biomass (trees, shrubs, grasses, mosses and lichens), and both models were most sensitive to changes in biomass. As the biomass in the model included above ground (tree- and ground vegetation), it could be that changes in them reached the 5 and 30 cm depths but not 50 cm. The effect of biomass on the size of the insoluble SOM fraction might occur through at least two opposing processes: loss of biomass during the forest fire and, on the other hand, an increase of biomass and changes in litter quality with succession (Brassard and Chen 2006). At 5 cm, the effect of active layer depth on the insoluble SOM fraction was close to that of the biomass (Fig, S1, Online resource), which could be related to possible temperature changes caused by retreating/returning permafrost and the consequent effects on vegetation. At 30 cm depth the effect of the C/N ratio was also close to that of biomass, possibly linking these two together as C/N ratio is also an indicator of incoming litter quality (Johnson and Wedin 1997). Both biomass and C/N ratio correlated negatively with the size of the insoluble SOM fraction. Still, the lack of explaining factors at 50 cm is perhaps connected to the proximity of permafrost or high soil water content.
The mixed effects model analysis further showed that microbial biomass is, amongst the SOM fractions, best predicted by the size of the insoluble fraction (at 5 and 30 cm depth). Moreover, microbial biomass and insoluble fraction size appear to correlate negatively, so that when the size of the insoluble fraction is high, the microbial biomass is low. This indicates that SOM quality is more important than SOM quantity in northern boreal ecosystem, as microbes usually prefer labile SOM fractions as a C source (Rinkes et al. 2011). Microbial biomass at 50 cm depth, on the other hand, is probably limited by factor other than the availability of labile SOM, such as soil temperature, the presence of permafrost and anoxic conditions due to a high ground water table on top of the permafrost (Hobbie et al. 2000b).
We discovered an age-related trend for δ15N, with the most recently burnt area having a more enriched surface soil than area FIRE100. During a fire, the 15N depleted litter layer may burn almost completely, rendering the burnt area with material enriched with 15N (Högberg 1997). For example, leaf litter of conifer trees seems to commonly be 15N depleted (Hobbie et al. 2000a; Sah and Ilvesniemi 2007). Usually plants that do not fix N2 have higher δ15N values than plants fixing N2 (He et al. 2009) and differences in leaf δ15N values are caused by discrimination against heavier isotopes in N uptake and transfer from mycorrhiza to plant (Hobbie and Hobbie 2006, 2008). The discrimination is also affected by the type of mycorrhiza (Michelsen et al. 1998), which might become apparent after such disturbances, as fire, where microbial species compositions are possibly altered. A change in the species composition was discovered also in this same fire chronosequence by Zhou et al. (2018). Previous studies have also noted that burning of the depleted litter is not necessarily the most dominating reason for enrichment with heavier isotopes. Instead, the enrichment may be attributed to volatilisation processes, which discriminate against heavier isotopes (Cook 2001; Boeckx et al. 2005) and root activity (Pumpanen et al. 2017). Forest fires generally also increase N leaching (Lamontagne et al. 2000), especially the leaching of 15N depleted NO3- (Pardo et al. 2002), which may have contributed to 15N enrichment in the FIRE3 area. On the other hand, water-soluble pyrogenic compounds might also be enriched with 15N and translocating down the soil profile. The soil 15N enrichment tends to increase with soil depth (Högberg 1997), as a result of microbial degradation of SOM (ammonification, nitrification and denitrification processes), where enriched material is accumulating in the residues (Makarov 2009; Girona-García et al. 2018). Fire has also been shown to decrease the differences in 15N enrichment along the soil profile, by causing enrichment in the upper 20 cm (Boeckx et al. 2005); a trend that was also somewhat apparent in our results. 15N was enriched throughout the soil profile in area FIRE3, while older fire areas were slightly depleted at the surface and enriched in the two deepest layers. However, as these differences were so small that they were not statistically significant, it is not possible to make conclusions based on them.
A similar trend as for 15N was also found for 13C abundance, with the two most recently burnt fire areas having less depleted values in the surface soil (5 cm) than in areas FIRE100 and FIRE46. Here we also noticed a trend where the 13C enrichment increased with depth, which has been detected quite commonly across ecosystems (Brüggemann et al. 2011). Typically, higher δ13C values indicate the presence of 13C enriched compounds, such as polysaccharides and amino acids, whereas 13C depletion could be caused by the existence of depleted materials, such as lignin and lipids (Rumpel and Kögel-Knabner 2011). The leaf isotopic values of C3 plants generally average around − 27 mUr (Brodribb and Hill 1998; Cernusak et al. 2009; Orchard et al. 2010), whereas lipids and lignin tend to be − 2 mUr to − 3 mUr more depleted compared to average leaf isotope value (Ehleringer et al. 2000). Cellulose tends to have similar, or slightly higher (Loader et al. 2003), values as lignin (Hobbie and Werner 2004). Some studies have found that during fire, cellulose is lost more than lignin and lipids, leading to lower δ 13C values in the heat modified OM (Alexis et al. 2010). On the other hand, post-fire litter of standing vegetation has been found to have higher δ 13C values than pre-fire litter, with post-fire litter forming much of the pyrogenic material (Alexis et al. 2010). Both of these factors may have contributed to the changes observed in the δ 13C values in this study. For example, in the top 5 cm, older fire areas had larger ethanol-soluble fraction (lipids etc.) and were more depleted. These findings seem to support each other and indicate that as succession proceeds after the fire, the size of the relatively labile SOM fraction increases.
In depth-wise comparison of the bulk soil the surface (5 cm) was more depleted of 13C than the deeper layers (30 and 50 cm), which seems to be the norm with 13C in forest soils (Balesdent et al. 1993; Krull et al. 2002; Boström et al. 2007). The slight enrichment along the depth profile is also supported by fractionation results, where deeper layers had greater recalcitrant SOM fractions. The 13C enrichment with depth in forest soils has been connected to four different hypotheses: the Suess effect, microbial fractionation, microbial preference and soil mixing (Ehleringer et al. 2000). The Suess effect, depletion of atmospheric CO2 of 13C caused by the burning of depleted fossil fuels (Balesdent et al. 1990; Trolier et al. 1996), could lead to older/deeper soil layers having less depleted 13C values corresponding to atmospheric 13CO2 values of that time (Ehleringer et al. 2000). On the other hand, microbial fractionation prefers lighter isotopes, leading to enrichment in the residual SOM (Natelhoffer and Fry 1988; Ehleringer et al. 2000), while microbial preference is related to which kind of substrates the microbes favor (Ehleringer et al. 2000). Finally, C mixing suggests that during a loss of soil C there is mixing between fresh and old SOM, therefore causing changes in 13C values. In addition to these, the SOM 13C values are much dependent on the origins of the material, such as type of litter (Benner et al. 1987). Regardless of the reason, in our results, the differences in 13C values between the surface and deeper layers were not very large, which could be at least partly explained by possible enrichment at the surface after the fire. At the same time, in the two oldest fire areas the deepest (50 cm) samples were below the permafrost, seemingly indicating that permafrost SOM in this area is relatively recalcitrant.
Our results indicated that fires do decrease the quality of SOM in the surface layer, but that the effect of fire on soil at the permafrost surface is more indirect and happens through changes in soil temperature and deepening of the active layer. In the oldest fire areas, FIRE46 and FIRE100, the 50 cm (also 30 cm for FIRE100) sampling depth was below the permafrost surface, showing that the permafrost soils in these areas were mostly very recalcitrant SOM and generally did not differ from the non-permafrost samples of the younger fire areas. While other studies have found somewhat differing results for the quality of permafrost SOM (Dutta et al. 2006; Waldrop et al. 2010; Moni et al. 2015), direct comparisons are difficult to make since there are differences between study sites, sampling depths and methods. As we did not sample the deep permafrost soils, some caution also needs to be taken while interpreting the results. However, our results indicated that, while in our study areas the permafrost may thaw, most of the permafrost SOM will possibly reside in the soil for a long period, due to its recalcitrant nature. Moreover, based on the sensitivity analyses, the permafrost/permafrost-affected soil does not seem to be very sensitive to changes, as the size of the recalcitrant fraction did not change significantly even if the factors affecting decomposition were changed in the sensitivity analysis of our linear mixed effect models. Despite this, it is possible that some of this recalcitrant SOM could decompose, as the input of fresh, easily decomposable C caused by fire could have a priming effect (Fontaine et al. 2007). Recalcitrant SOM may also be more temperature sensitive (Davidson and Janssens 2006; Karhu et al. 2010), unless protected by physical protection (Gillabel et al. 2010), meaning that the possible warming of soil, if the insulating organic layer is burnt and permafrost starts to thaw, may cause C emissions. Indeed, deeper active layer was found at the more recently burnt areas, which hints in that direction. Still, the formation of recalcitrant SOM by fire may act as a counter-affecting process. Possible C losses from these upland mineral forest soils are then largely dependent on whether in the warming climate the permafrost, lost after the fire, will continue to return as succession proceeds, and whether some following process will be able to degrade the potentially very resistant permafrost SOM.
Based on our results the effect of fires on SOM quality seems to be mostly on the surface soil. Initially after fire, the surface soil SOM quality is reduced and, as succession proceeds, the ratios of the SOM fractions revert towards pre-fire status. The SOM in permafrost soils in these forest areas seem to be mostly recalcitrant. These indicate that even if permafrost thaws, the scale and rate of C emissions from the upland mineral permafrost soils could be limited. However, further research is needed for quantifying the amount of SOM in different fractions and assessing the SOM quality of deep permafrost soils.
We conclude that a consequence of changing climate is that fire intervals become shorter and the forest rotation time is decreased, leading to less C being stored in the soil (Kaipainen et al. 2004; Hoy et al. 2016). While labile C is lost in fires, pyrogenic C is accumulated to the soil. At the same time, the pioneer species in vegetation might prosper relatively longer times compared to late succession species, which affects the quality of SOM via incoming litter. These factors may be seen in a proportional decrease in the size of the labile SOM fraction and increase in the size of recalcitrant fraction: while labile C is lost in fire, pyrogenic C is stored. This might lead to decrease in CO2 emissions to the atmosphere from post-fire soil decomposition. At the same time, the permafrost has less time to recover and reach original depths (Hoy et al. 2016), meaning that the permafrost SOM, though possibly recalcitrant, will be vulnerable to decomposition for longer periods of time. The effect of these counteracting processes on permafrost C pools require further studies.