Relationships between scaling constant/intercept and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are standard errors of the scaling exponents.</p

Relationships between scaling exponent and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The scaling exponent of each age, DBH, height, density, latitude, longitude, and elevated group was estimated using reduce major axis (RMA) regression analysis. The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are standard errors of the slopes.</p

Relationships between belowground biomass and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are too small to be shown.</p

Map of sampling sites of data used in this study.

<p>Map of sampling sites of data used in this study.</p

Relationships between aboveground biomass and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The model with the best fit among the linear, quadratic and power function models is presented. * significant at α = 0.05 level, ** significant at α = 0.01 level. Error bars are too small to be shown.</p

Relationship between belowground biomass and aboveground biomass of forests in China.

<p>The model is estimated using reduced major axis regression method (n = 6153). ** significant at α = 0.01 level.</p

Relationships between belowground biomass and aboveground biomass for different age groups.

<p>a: age< = 15; b: 15110. The model was fit using reduced major axis regression method. ** significant at α = 0.01 level.</p