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.