Main text
Understanding the driving mechanisms of soil organic carbon (SOC)
persistence is crucial to project future carbon-climate feedback
(Schmidt et al. 2011). Chen et al. (2021) (C21hereafter) hypothesized that plant carbon input, as a proxy of priming
effect, governs the topsoil carbon turnover across alpine grasslands in
Tibetan Plateau. A structure equation model was built to assess the
relationships between environmental variables and
Δ14C, an indicator of soil carbon turnover (Shiet al. 2020; Wu et al. 2021). However, only plant carbon
input was considered as a direct effect on Δ14C in
their final optimized model while the direct climate effect was reported
to be non-significant (Fig. 3 in C21 ). From the model,
plant carbon input exerts a stronger direct effect on topsoil carbon
turnover, while precipitation only has a weaker indirect effect. The
resultant lack of direct climate (mainly precipitation) effect on soil
carbon turnover is surprising and contradictive to previous reports that
soil carbon turnover is directly regulated by water availability
especially in arid and semi-arid regions (Carvalhais et al. 2014;
Wu et al. 2018).
We built and compared three possible structure equation models
(Fig. 1 ) using the datasets provided in C21 . Model-A
only considered the direct effect of plant input on topsoil
Δ14C. By contrast, model-B included direct effects on
topsoil Δ14C from both plant input and precipitation.
Model-C further included an additional direct effect from mineral
protection. Model-A generated similar statistical results withC21 , showing stronger total effect from plant input than from
precipitation. In model-B, the two path coefficients related to
Δ14C from both plant input and precipitation are still
significant (P < 0.05), and overall model performance
(AIC = 19.945) is better than model-A (AIC = 21.989). Moreover, the
strength of precipitation direct effect is comparable to that of plant
input. As a result, the total standardized effect of precipitation is
much larger than plant carbon input. In model-C, all three path
coefficients related with Δ14C fail to reject the null
hypothesis based on significance level of 0.05 because of severe
multicollinearity between the variables. Overall, the dataset inC21 best supported model-B that includes direct climate effect.
We could not include the chemical composition of soil organic matter,
which nevertheless had no significant effects for topsoil in C21 ,
in all the three models because the data was not made available.
We also conducted partial correlation analysis to detect the relative
importance of direct effects from climate, plant input, and soil mineral
composition on Δ14C. Partial correlation analysis
assesses the correlation between Δ14C and one specific
environmental factor after removing the effects of other environmental
factors. The results showed that precipitation is still the most
importance factor in regulating the topsoil carbon turnover than other
factors (Fig. 2 ). Furthermore, we find precipitation governs
the topsoil carbon turnover in alpine steppe, while temperature and
mineral protection play major roles across alpine meadow. The difference
likely implies that SOC decomposition is primarily limited by water in
the drier alpine steppe, which is partially relieved in the wetter
alpine meadow. In all cases, our results indicate that plant input does
not play the dominant role in regulating the topsoil carbon turnover.
The overlook of direct climatic effects on SOC turnover can also bias
the interpretation of the significant relationship between vegetation
indices and topsoil Δ14C on a global scale
(Fig. 4 in C21 ). C21 interpreted these
relationships as a universal law of the plant input effects on topsoil
carbon turnover. However, the correlation can arise because preferable
climatic conditions (e.g., warm and moist) increase both plant input and
SOC decomposition rate (Davidson & Janssens 2006). Direct climatic
effects on SOC turnover should be carefully removed before interpreting
the plant input effects from these global data.
Aside from overestimating the direct effects of plant input on SOC
turnover, C21 treated the amount of plant input as a proxy of
priming effects, which is however questionable. According to incubation
experiments using soils from the same ecosystems by Chen et al.(2019), the amount of plant input does not show significant direct
effect on soil priming intensity. Furthermore, components of plant input
(shoot, root and mycorrhizal) usually have quite different effects in
regulating priming effects (Huang et al. 2021). Therefore, it is
unreasonable to simply use the amount of plant input as the indicator of
priming effect.
Despite C21 likely
overestimated the contribution of plant input on SOC turnover, the study
raised an important scientific question on the relation between SOC
turnover and priming effect. Observed earth greening increased the fresh
carbon input in soil system, which may promote the priming effects and
accelerate the SOC turnover (Terrer et al. 2021). This crucial
process is still missing in most existing ecosystem models (Wu et
al. 2020), which may lead to an overestimation of the terrestrial soil
carbon storage potential.