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gcb12629-sup-DataS1.docxWord document1712K

Data S1. Figures.

Figure S1. Distribution of the 58 study sites in environmental space of altitude, mean annual temperature, mean annual evapotranspiration (ET, mm yr−1), mean annual rainfall, and temperature seasonality (TS). The gray shades in the background represent the range of observed variation in currently forested areas in the tropical belt. Red dots indicate Latin American sites, green African sites, and blue Southeast Asian and Australian sites.

Figure S2. Among-site relationship of the individual coefficient of variation to bioclimatic variables (TS: temperature seasonality; CWD: climatic water deficit) across study sites, for Model 4. Each point represents the individual coefficient of variation CV(j) of a study site j, as inferred from Model 4. Point color and size are as in Fig. 3.

Figure S3. Among-site relationship of the site-level bias with bioclimatic variables (TS: temperature seasonality; CWD: climatic water deficit) for Model 4. Each point represents the Bias(j) for site j as inferred from Model 4. Point color and size are as in Fig. 3.

Figure S4. Among-site relationship of the form factor (ratio AGB /ρD2H with bioclimatic variables (TS: temperature seasonality; CWD: climatic water deficit). Each point represents the mean form factor of a study site (equivalent to the fitted parameter of Model 5). Correlation tests were performed on each dataset. In panel (a) P = 0.09 (Bartlett test); in panels (b) to (d), P < 10−3, P = 0.08, P < 10−3 (Spearman correlation). Point color and size are as in Fig. 3.

Figure S5. Forward selection for bioclimatic variables in Eqn (3). The first selected variable is TS (temperature seasonality), and including it results in a decline of the residual standard error (σ’, noted RSE in the ordinate axis) from 0.430 to 0.292. The second selected variable is CWD (climatic water deficit), and including it results in a decline of the RSE from 0.292 to 0.272. The third selected variable is PS (precipitation seasonality), and including it results in a further decline of the RSE from 0.272 to 0.243. Additional environmental variables induced comparatively very little further decline in RSE (a gain of 0.022).

Figure S6. Comparison between the pantropical allometric AGB Model 7 and a model in which Feldpausch et al. (2012) regional diameter–height equations were used. (a) Individual coefficient of variation at each site for both types of allometries. (b) Bias at each site for both types of allometries. Point color and size are as in Fig. 3. The outlying sites are labeled.

gcb12629-sup-DataS2.docxWord document48K

Data S2. Description of the study sites.

Table S1. Study sites and their characteristics.

gcb12629-sup-DataS3.docxWord document18K

Data S3. Details about the database construction.

Table S2. Description of the variables included in the dataset (n = 4004).

gcb12629-sup-DataS4.pdfPDF document1562K

Data S4. Illustration of the goodness of fit at each of the 58 study sites. The full dataset is plotted in the background (black). The foreground points and regression line represent the best-fit regression for local datasets.

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