Extended Data Fig. 9: Remote sensing validation with forest inventory plot demography.

(a) Remotely sensed map of MAIAC EVI (1-km resolution), overlaid with aboveground NPP (ANPP) rates from 321 ground-monitored forest plots (red circles, % standing biomass y⁻¹) as aggregated to 1 degree grid plots (RAINFOR plots in Brienen et al. ²), with both EVI and ANPP taken during the 2000–2011 interval. ANPP rate is calculated as Aboveground Biomass (AGB) gain (Mg/(ha·yr)) (total annual AGB productivity of surviving trees plus recruitment, plus inferred growth of trees that died between censusing intervals) divided by initial AGB (Mg/ha) (standing above ground biomass at the start of the census interval). (b) ANPP rates as predicted by EVI (points from (a) plus solid regression line with statistics; Dashed line and associated statistics in grey represent linear regression without the high leverage point, shown in red, defined by Cook’s distances > 4/n, where n=number of points¹³⁴). EVI is the mean extracted from intervals matching the average census interval of the corresponding plots in Brienen et al. ² (c)–(e) MAIAC EVI anomalies (1-km pixels) versus ground-monitored tree demography in shallow water table forests during the 2015-2016 drought²⁶ for: (c) mortality, (d) recruitment, and (e) mortality:recruitment ratios in 1-ha plots. (f)–(h): GOSIF anomalies (5-km pixels) versus ground-monitored (f) mortality, (g) recruitment, and (h) mortality:recruitment ratios; Solid lines and statistics (R² and p-values) represent standard linear regression fits to all data. Red points, if they exist, are high leverage, i.e. with Cook’s distances > 4/n, where n=number of points¹³⁴, and dotted lines and associated statistics in grey represent standard linear regressions without such points, showing that remote detection of ground-derived demographic trends is robust. R² values reported here are consistent with the expectation that they should be less than for remote detection of tropical forest GPP (R² = 0.5-0.7), because GPP contributes only partially to the NPP driver of demography (as discussed in the 'Validation by forest plot metrics of demography and of physiological drought tolerance' section of Methods). Considering multple comparisons (six regressions), the probability, under the null hypothesis, of seeing five or more significant regresssions out of six is p = 0.000002 (Binomial test).