Mapping the structural diversity of Central African and Western US forests using GEDI

This study maps forest structural diversity, a key component of ecosystem diversity, using NASA's GEDI spaceborne lidar, providing new opportunities to support conservation and restoration efforts. Focusing on biodiversity hotspots in Central Africa and the Western US, we evaluated GEDI's ability to capture spatial variation in forest canopy structure by comparing GEDI-derived metrics with 391 km 2 of airborne laser scanning (ALS) data. Forest structural traits were assessed at 1 km 2 resolution, with GEDI showing robust correlations with ALS, particularly in dense and flat Central African forests (r 2 up to 0.85), and moderate agreement in more heterogeneous terrain in the California Sierra Nevada (r 2 up to 0.55). We quantified structural diversity as horizontal variation in canopy structure using a probability density-based multivariate diversity framework. GEDI canopy height (rh98), canopy cover, and foliage height diversity jointly captured independent axes of canopy variation and explained structural diversity derived from wall-to-wall ALS (r 2 = 0.37 at 1 km 2 ). Resulting maps reveal high structural diversity in mid-elevation and coastal forests of the Western US and in forest-savanna transitions and volcanic ranges of Central Africa, consistent with gradients in disturbance, topography and aridity. Despite limitations related to sampling density, waveform noise and terrain complexity, this study demonstrates that GEDI's footprint-level metrics can be used directly to quantify forest structural diversity. These findings highlight the potential of spaceborne lidar to provide scalable, trait-based structural diversity indicators, while emphasizing that interpretation remains context dependent and benefits from integration with ecological data, environmental drivers and disturbance regimes. • GEDI lidar reveals structural diversity of Western US and Central African forests. • Landscape-scale validation with airborne lidar across 391 plots of 1 km 2 extent. • Diversity best captured using 3D index with GEDI RH98, Cover and FHD (r 2 = 0.37). • Diversity patterns follow floristic turnover, topography, aridity and disturbance. • Challenges arise from low canopy cover, complex terrain and low sampling density.