Primary factors controlling variations in soil microbial
respiration at different scales
As our second hypothesis, in this study we found that factors
controlling Rm’s spatial variation and underlying mechanisms were
different at the different scales, and revealed that the relative
importance of climate, soil physicochemical and microbial properties in
driving Rm’s spatial variation varied with scales according to variance
partitioning results (Fig. 4), although they together affected the Rm’s
spatial patterns through their various impacts on microbial activities
(Colman & Schimel, 2013). We found that climate affected indirectly
Rm’s variation by changing different soil physicochemical and microbial
properties at different scales (Fig. 5), although some previous studies
demonstrated Rm was related to MAT and MAP at different scales (e.g., Li
et al., 2020). At the continental scale, climate affected indirectly Rm
by altering mainly LOC, fungal and gram-positive bacterial biomass (Fig.
5a), which was supported by the observation of Wang et al. (2018), while
in the latitude < 32.5°N region, the alteration of fungal and
gram-positive bacterial biomass by climate played a critical role in
Rm’s variation (Fig. 5b), and the changes in LOC and SOC caused by
climate controlled Rm’s variation in the latitude > 32.5°N
region (Fig. 5c). In comparison with climate and soil microbial
variables, the largest total (49.5%) and unique (13.6%) explanation of
soil physicochemical property for the spatial variation in Rm (Fig. 5a)
suggested that soil physicochemical property had the most importance in
regulating the Rm’s spatial variation across China forest ecosystems. As
some previous studies reported (Dai et al. 2017; Herbst et al. 2011;
Meyer et al. 2017), some physicochemical variables such as the quality
and quantity of the substrate as the direct factors of soil microbial
metabolisms exert a crucial role in determining the spatial patterns of
microbial activity. We further revealed that LOC was the most
significant explanatory variable among physicochemical factors in
regulating the Rm’s spatial variation based on boosted regression
analysis (Fig. 6a), which was supported by the positive relationship
between LOC content and Rm (Fig. S1b). This is because high LOC content
is usually associated with high microbial availability and C energy, and
preferentially utilized by soil microorganisms.
Soil microbial property had a unique explanation (6.13%) for the
spatial variation in Rm at the continental scale (Fig. 4a). Our results
provide a first direct experimental evidence that soil microbial
characteristics play a unique role in regulating Rm’s spatial variation
at the continental scale and suggest the relationships between microbial
community composition and Rm potentially linked to microbial life
strategies and functional capabilities (Takur et al., 2018; Trivedi et
al., 2016). Various microbial groups with different C use efficiency
(Austin et al., 2004; Waring et al., 2013) and preferences to soil
organic matter (Lehmann and Kleber, 2015; Ramirez et al., 2012) maybe
lead to this unique explanation of microbial variables to the Rm’s
spatial variation, which was in accord with recent studies suggesting
the significant role of soil microbial biomass and community in
controlling ecosystem multiple functions (Bradford et al. 2017;
Delgado-Baquerizo et al., 2016b; Liu et al., 2018b). We quantified the
importance of major microbial groups measured by PLFAs in predicting Rm
based on the boosted regression analysis and revealed fungi were the
most important drivers of the spatial variation in Rm (Fig. 6a),
supporting the growing literature that demonstrates the significance of
fungi in driving soil functions (de Boer et al., 2005; Dacal et al.,
2019; Delgado-Baquerizo et al., 2016b; Wagg et al., 2014). Together with
other results, we highlight the importance of including microbial
community composition in Earth system model to improve our ability to
predict C feedbacks in terrestrial ecosystems.
More importantly, we found an interesting result that microbial
variables had larger unique explanations for Rm’s spatial variation in
the latitude < 32.5°N region than in the latitude
> 32.5°N region (Fig. 4b,c) and for the first time revealed
the differences in the primary factors regulating the Rm’s variations in
the latitude < 32.5°N and > 32.5°N regions.
Microbial property, especially fungal biomass as the primary predictors
in regulating Rm’s variations was probably related to higher microbial
activity because of high MAT (Fig. 5b; Fig. 6b). Although some previous
studies demonstrated that in cropland or grassland ecosystems soil
microbial biomass was a strong regulator of soil respiration or litter
decomposition at regional or continental scales (Colman & Schimel,
2013; Bradford et al., 2017), they did not identify its relative
importance and also not observe that fungal biomass had different
importance in regulating Rm’s spatial variation in different regions.
Therefore, our findings advanced our understanding of Rm’s spatial
variation and its controlling mechanisms at different scales.
Although we have some important findings that to some extent enhance our
understanding of Rm’s variation and its mechanisms, here we noted that
the unique explanation of soil microbial property may be underestimated
because some key enzyme activities associating with SOC process were not
measured. Some experiments have emphasized the important role of enzyme
activities in controlling Rm through mediating the rate-limiting step of
SOC depolymerization (Ali et al., 2018; Dungait et al., 2012; Kandeler
et al., 2006). Therefore, we considered that the unique explanation of
soil microbial property to Rm’s spatial variation would be higher than
our current estimation if some key enzyme activities are measured.
Another important aspect to mention here is that we controlled soil
samples under 60% water holding capacity, which made Rm independent of
soil moisture (Ali et al., 2018; Wang et al., 2018). That is to say, the
influence of soil moisture on Rm was not considered in our study,
although soil moisture has strong effect on Rm (Chang et al., 2014;
Stoyan et al., 2000). Therefore, we should be careful when directly
using these results in predicting Rm in field and its dynamics under
global change environment.
In conclusion, we highlighted the importance of incorporating Rm’s
spatial variation in C-climate models for better predicting responses of
forest soil C dynamics to future environmental change using a novel
incubation method and for the first time revealed the hump-shaped
relationship between latitude and Rm with a latitudinal threshold of
32.5°N at the continental scale. The factors controlling Rm’s spatial
variation and underlying mechanisms varied in different regions,
although labile organic C was the most important variable in regulating
the Rm variation at the continental scale. Importantly, soil microbial
variables, particularly fungal biomass, played an important and unique
role in regulating Rm’s spatial variation, but their significances were
higher in shaping Rm’s variation across the continental and latitude
< 32.5°N region than at latitude > 32.5°N region.
Overall, our findings suggest labile organic C and fungal have critical
roles in controlling Rm in China’s forest ecosystems, and suggest that
including Rm spatial variation in Earth system models can potentially
improve our capacity to predict changes in soil organic C balance under
changing environment.