Figure captions
Fig. 1 Site locals (black dots) of studied forests along a
latitude gradient in China.
Fig. 2 Spatial patterns of soil microbial respiration along
latitude across all forests (a), broadleaved (b), coniferous (c) and
mixed (d) forests in China.
Fig. 3 Differences in soil microbial respiration among forest
types (a) and biomes (b) across China forests. Different letters denoted
significant differences at p < 0.05.
Fig. 4 Variance partitioning for three different categories:
climate, soil physicochemical property (PC) and microbial property (MP)
in explaining the soil microbial respiration across the continent (a),
in the latitude < 32.5°N (b) and > 32.5°N (c)
regions.
Fig.5 PiecewiseSEM
accounting for the direct and indirect effects of climate predictors,
soil properties and microbial properties on the microbial respiration
(MR) across the continent (a), in the latitude < 32.5°N (b)
and latitude > 32.5°N (c) regions. Climate, soil properties
and microbial properties are both composite variables. Numbers adjacent
to measured variables are their coefficients with composite variables.
Numbers adjacent to arrows are path coefficients are the directly
standardized effect size of the relationship. The thickness of the arrow
represents the strength of the relationship. Total standardized effects
of composite variables on microbial respiration are showed in
conditional and marginal R2 represent the proportion
of variance explained by all predictors without and with accounting for
random effects of “sampling site”. Significance levels of each
predictor are * p < 0.05, ** p < 0.01,
*** p < 0.001.
Fig. 6 Predictor relative importance of key variables among
climate, soil physicochemical and microbial properties in driving soil
microbial respiration based on boosted regression model analysis for
soils across the continent (a), latitude < 32.5°N (b) and
> 32.5°N (c) regions.