4.1. Main Drivers of CO2 Emission Rates
We identified dead wood tree species, wood temperature, fungal species richness and wood density as the main drivers of CO2 emission rates in the initial phase of dead wood decomposition. Additional variables such as region, forest management intensity, and wood properties (water content, and C and N concentrations) had no significant influences on CO2 emission rates in the best-fit global model.
To our knowledge, this is the first study where CO2
emission rates of such a large number of temperate European tree species were analyzed at the same time and in a coherent design. Tree species identity was by far the most important variable in the best-fit global model. The effect size for tree species within the best-fit global model was largely similar to their original value of CO2
emission rates. This indicates that wood temperature; wood density and fungal species richness had comparable effects on each tree species. Also, for decomposition rates of freshly logged and natural dead wood in neotropical forests, tree species identity was found to be the most prominent driver [32
]. It has been proposed previously that wood trait variations are responsible for the dominating influence of tree species identity on decomposition rates [35
]. Wood traits such as N-concentration, phosphorus-concentration, C:N ratio were found to correlate with decomposition rates of angiosperms, whereas gymnosperm wood generally decomposes slower than angiosperm wood [11
]. Our study corroborates the statement on gymnosperms with Picea
being the only exception. The wood traits (density, and C and N concentrations) determined in our study were measured three years after the onset of the decomposition process and therefore not comparable with original wood traits as discussed in Weedon et al.
]. Up to now, dead wood CO2
emission and decomposition rates have been estimated only for the most abundant temperate European tree species. Those findings are quite similar to our study results. Higher respirational C loss of beech compared to spruce and pine has been shown by Herrmann and Bauhus (2012) [19
]. An order of decomposition rates with beech > spruce = pine > oak has been suggested by Rock et al.
], which does not totally coincide with our results that yield an order of CO2
emission rates with beech > spruce > oak > pine. In contrast to Rock et al.
(2008) who looked at decomposition rates over the whole course of decomposition, our study shows CO2
emission rates in the initial phase of decomposition. Possibly caused by interspecific differences in the initial lag phase [36
emission rates show a slightly different picture than decomposition rates.
As expected, CO2
emission rates increased with wood temperature. The effect size for wood temperature was similar to the original correlation between wood temperature and CO2
emission rates, meaning that the effect of wood temperature is largely independent of tree species identity, wood density and fungal species richness. The increase of CO2
emission rates by 2–3 times for every 10 °C wood temperature increase (Q10) has been shown in several laboratory and field based studies [3
]. It is a remarkable finding of our study, that the independent contribution of wood temperature explained only 14% of our total best-fit global model variation. This could be caused by measurements at rather low temperatures (5.8 °C to 18.4 °C), although Chen et al.
] showed that temperature sensitivity (Q10) was highest between 5 °C and 10 °C. And it could also be caused by the rather low gradient in temperature of 12.6 K. A larger gradient could possibly increase the independent contribution of temperature on CO2
emission rates. Furthermore, we strongly believe that the seasonal variation in temperature would affect wood temperature and thus CO2
emission rates. But the sampling design (one measurement per log in autumn 2012) limited the observed temperature range.
Within the best-fit global model CO2
emission rates decreased with increasing wood density. This is noteworthy since originally (Figure 5
) no significant linear correlation between wood density and CO2
emission rates was found. With our approach to base CO2
emission rates on volume we could even expect a positive relationship between CO2
emission rates and wood density. But the opposite is true. We assume that the CO2
emission rate–wood density relationship changes during progressive wood decomposition. In the lag and initial phase of decomposition, a negative relationship between CO2
emission rates and wood density exists, because wood with higher density is in an earlier successional stage and exhibits a lower activity of fungal decomposers while wood with lower density is in a later successional stage, already partially decayed and exhibits higher activity of fungal decomposers [16
]. In the final stage of decomposition, a positive relationship between CO2
emission rates and wood density can be expected since fungal decomposer activity should decrease after a certain mass loss in substrate.
As hypothesized, CO2
emission rates were positively affected by fungal species richness. To our knowledge, this is the first field study that shows a positive fungal species richness–CO2
emission rate relationship for dead wood. This result agrees with a lab study that proved a positive biodiversity–ecosystem process relationship for fungi and dead wood decomposition [28
]. The effect size of fungal species richness was much lower than to be expected from the correlation between the raw data (Figure 4
). This was caused by the hidden correlation between fungal species richness and tree species. Fungal species richness is known to be a function of dead wood tree species identity [21
] and successional stage [54
]. In our study, tree species with high fungal species richness also tended to have higher CO2
emission rates (Figure 4
). In the initial and early phase of decomposition, as a result of progressing colonization and fungal succession species richness, fungal growth and activity (CO2
emission rates) are increasing. Tree species identity seems to determine the speed of initial fungal succession and therefore initial CO2
emission rates. Although a large part of the correlation between fungal species richness and CO2
emission rates was obviously explained by tree species identity, the independent contribution of fungal species richness to the best-fit global model was still 12%. This is almost as high as the independent contribution of temperature (14%) and underlines the importance of fungal species richness in our study. The observed importance of fungal species richness was not mirrored in the separate models for each tree species. Only for Prunus avium
a significant positive effect was found.
4.2. Drivers of CO2 Emission Rates in Dead Wood Tree Species
Wood temperature was the predominant driver of CO2 emission rates in tree species-specific models, except for Acer, Fagus and Fraxinus where none of the explanatory variables explained any variance in CO2 emission rates. This reflects the results of the best-fit global model, where temperature was the second most important driver of CO2 emission rates after tree species.
Previous forest management intensity might influence dead wood decomposition through a different forest microclimate [56
] or through different stocks of coarse woody debris that act as a reservoir for wood-decaying fungi. In our study, forest management intensity had a negative effect on decomposition only for Tilia
, meaning that in forests with lower management intensity a higher CO2
emission rate was found. On the other hand, Betula
had higher CO2
emission rates in more intensively managed forests. Taking into account that CO2
emission rates in nine out 13 tree species were independent of forest management intensity, it appears that overall management does not have a considerable effect. As for the forest management intensity, the regional aspect plays an almost negligible role. Only Betula
show significant regional differences with a tendency to higher CO2
emission rates in the exploratory Hainich Dün.
In the best-fit global model, wood density had a negative effect on CO2 emission rates, but at the species-level this effect appeared only in Carpinus, Picea and Tilia. It seems that for these tree species a range of logs in different successional stages exist. In reference to the fungal succession we assume, that most of the tree species are in an initial phase of decomposition (Hypoxylon fragiforme and Armiallaria mellea s.l. rhizomorph), whereas some transition into the optimal phase (Bjerkandera adusta, Stereum hirsutum, and Trametes spp.). This would result in logs with high density and low activity in contrast to logs with lower density and higher activity. The results for a negative correlation with water content in Picea and Pseudotsuga are difficult to interpret since water content is in both cases within the tolerance range of 30% to 160% (dry weight based) for Basidiomycota, which means that they should have optimal growth conditions. The negative correlation of CO2 emission rates with C-concentration for Betula and the positive correlation with N-concentration for Populus cannot be explained.
As mentioned before, except for Prunus, fungal species richness did not have an impact on CO2 emission rates in 12 out of 13 tree species. This could either mean that no positive effect exists for other tree species or that this effect is only detectable in later stages of decomposition. In addition, decomposition of dead wood may be carried out by an unknown number of fungal species that were not detectable as fruit bodies during the duration of this study. The overall importance of fungal species richness in the best-fit global model is not invalidated by this result. It just means that the significant effect of fungal species richness is only detectable with a larger number of tree species.
4.3. Fungal Identity and CO2 Emission Rates
Not tree species identity or any of the other variables are the main agents of decomposition, but the fungi whose wood decaying activity is driven by these variables. However, it is difficult to disentangle and quantify the direct effects of fungal decomposition and indirect effects of abiotic variables on CO2
emission rates. Moreover, not only the fungal identity but also the fungal community composition and abundance affect the decay process. It is therefore important to remember that the method used here only shows associations between high or low CO2
emission rates and the occurrence of certain fungal species (Figure 6
). This approach was purely descriptive and cannot claim to identify causal relationships.
The decision to capture fungal data on the basis of fruit body production is reasonable because this fungal trait indicates high physiological activity and wood decomposition processes, respectively. But, on the other hand, high physiological activity does not necessarily induce fruit body production. Therefore there is no guarantee that all active fungal species were gathered with the applied method. An additional fungal-specific characteristic is the hidden dimension of the mycelia within the substrate. Considering this, only presence-absence data were used. Because of the small-scale inventory (detailed study of 1 m of the log) this kind of data could be regarded as acceptable and meaningful.
Despite the mentioned constraints the results present strong evidence for the different wood decaying capacities of many macrofungi under field conditions (Figure 6
). For instance, observed fungal species such as Fomitopsis pinicola
and Bjerkandera adusta
, which were associated with high CO2
emission rates, are known as important dead wood decomposers [39
]. The degree of CO2
emission rates is not only determined by fungal identity and size of mycelia, but also by fungal community composition. For example, it is known for the observed genera Hypocrea
] and Ascocoryne
] that they are able to produce antibiotics that obstruct the colonization with wood decaying fungi and therefore slow down wood decomposition. In our study, only for Ascocoryne
an association with low CO2
emission rates was found in Fraxinus
Owing to random processes in fungal colonization of dead wood and later facilitative or competitive processes between fungal species, the fungal community is practically unique for each log [59
]. In addition, wood-inhabiting fungi show a wide variety of strategies to gain and hold territories in wood, defined not least by their mode of dispersal and establishment, and by individual adaptation to the various disturbance and stress factors influencing life in decaying wood [60
]. Nevertheless, the shown associations between fungal species and CO2
emission rates can be used to search for species that inhibit or accelerate dead wood decomposition.