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. 2023 Dec 13;14:8277. doi: 10.1038/s41467-023-44127-9

Table 1.

Variable importance for how each parameter type influences the deforestation emission baseline, as well as statistical tests (one-way ANOVA and Tukey’s HSD post-hoc) comparing relative variabilities between the different levels of each parameter, for n = 2794 jurisdictions

Parameter Variable Importance Statistical tests
Mean SE One-Way ANOVA Tukey’s HSD post-hoc
Deforestation rate
Projection approach 10.2 0.18 F(6,19524) = 1678, p < 0.01 All pairs p < 0.05, except global-regional_s (p = 0.1) and global_s-regional_s (p = 0.07)
Forest dataset 4.41 0.14 F(4,12791) = 430, p < 0.01 All pairs p < 0.05, except hansen15-30 (p = 0.97)
Historical reference years 2.22 0.16 F(10,30749) = 82, p < 0.01 All pairs p < 0.05, except 7-8, 8-9, 9-10, 9-11, 10-11, 10-12, 11-12, 11-13, 12-13, 12-14, 13-14, 13-15, 14-15.
Carbon
Forest dataset 0.74 0.04 F(4,13565) = 2.5, p = 0.042 All pairs p > 0.05.
AGB 1.31 0.04 F(2,8379) = 8.4, p < 0.01 gedi-soto & gedi-spawn (p < 0.01); soto-spawn (p = 0.99)
BGB 0.50 0.02 F(2,8385) = 26.8, p < 0.01 ipcc-soto & soto-spawn (p < 0.01); ipcc-spawn (p = 0.98)
SOC 0.23 0.02 F(1,5594) = 0.3, p = 0.556 esdac-olm (p = 0.556)

aBold indicates statistically-significant values