**3. Results**

#### *3.1. The GLAS Parameters in the Mangrove Distribution Zone*

The discrete GLAS parameter points were extrapolated to spatially continuous layers using the random forest method for leading edge extent, waveform extent, and trailing edge extent (Figure 3). Overall, the random forest models explained 40.32%, 59.12%, and 41.39% of the variance in leading edge extent, waveform extent and trailing edge extent, respectively. The root-mean-square residuals for leading edge extent, waveform extent, and trailing edge extent were 4.30, 6.98, and 2.35 m, respectively. According to the extrapolated results, the mean value of leading edge extent, waveform extent, and trailing edge extent for the mangroves were 11.34 ± 5.61 m, 19.06 ± 7.09 m, 4.19 ± 1.34 m, respectively. These three GLAS parameters showed similar spatial patterns of mangrove distribution. The highest values of all three parameters appeared in the Indonesian archipelago, Central America, and the Gulf of Guinea.

**Figure 3.** The spatial-continuous map of three GLAS parameters in the mangrove distribution zone, (**a**) waveform extent, (**b**) leading edge extent, and (**c**) trailing edge extent. Note that the spatially continuous map was drawn using points since the mangrove distribution zone is narrow and cannot be represented well using a raster map at the global scale.

#### *3.2. The Global Mangrove Forest AGB Map*

We used a random forest regression model with the three extrapolated GLAS parameters and other predictor variables to estimate global mangrove AGB. The random forest model explained 52.34% of the variance in AGB. The final AGB distribution pattern is similar to that of the GLAS parameters (Figure 4). The mean AGB density of global mangrove was 115.23 Mg/ha with a standard deviation of 48.89 Mg/ha. This map of AGB for mangrove forests will be shared on the GUO-Lab website (http://www.3decology.org).

**Figure 4.** Predicted mangrove forest AGB distribution (**a**) throughout the world, (**b**) enlarged over Southeastern Asia, and (**c**) enlarged over Central America.

#### *3.3. Continental and National Level Mangrove Forest AGB Density*

Total global AGB for mangroves was 1.52 Pg (Table 2), but the contribution by region was not uniform. Southeastern Asia provided 34.98% of the AGB (0.53 Pg) while having both the largest area (4,044,906.25 ha) and high AGB density (131.36 ± 45.94 Mg/ha). South America encompassed the second largest area (2,062,231.25 ha) and high AGB density (111.33 ± 58.70 Mg/ha), and the second highest stock of AGB (0.15 Pg). The mangrove AGB density in Central America (110.29 ± 39.48 Mg/ha) was similar to that of South America, although the area of mangrove in Central America was much smaller (1,388,962.50 ha). Mangrove AGB stocks in Southern Asia (0.13 Pg) and Western Africa (0.12 Pg) were similar, although the density of AGB was much higher in Southern Asia (132.6 ± 29.79 Mg/ha) than in Western Africa (79.27 ± 34.32 Mg/ha). The extent of mangrove in Southern Asia (949,281.25 ha), on the other hand, was lower than that in Western Africa (1,475,343.75 ha). At the national level, Indonesia had the highest stock of AGB (0.36 Pg) because of the high AGB density (140.12 ± 41.02 Mg/ha) and large area covered by mangrove (2,547,556.25 ha). Mexico had the second largest AGB (0.1 Pg) since

it has large areas (891,312.50 ha) and high AGB density (113.98 ± 34.10 Mg/ha). The mangrove AGB density and stock for other important regions and countries are listed in Table 2.


**Table 2.** The mean AGB density and total AGB in the different regions and countries.

\* The geographic regions used to organize the final statistics results were defined by the United Nations (https: //unstats.un.org/unsd/methodology/m49/).

#### *3.4. The Accuracy of Mangrove AGB Estimation*

These estimates of mangrove AGB were validated using 103 independent validation plots (Figure 5). Predicted mangrove AGB was consistent with observerd AGB. The *R*<sup>2</sup> between predicted and observed AGB is 0.48 and the RMSE is 75.85 Mg/ha. The AGB estimation method in this study tended to marginally overestimate AGB densities at low values (<125 Mg/ha; Figure 5) and tends to underestimate forest AGB density at high values (>125 Mg/ha).

**Figure 5.** The validation of mangrove biomass estimated model. *R<sup>2</sup>* represents the adjusted coefficient of determination, *RMSE* represents the root-mean-square error.
