Remote sensing is a powerful tool for characterizing ecosystems at large scales. However, the relative importance of leaf traits and canopy structure in characterizing the spatial distribution of functionally distinct tropical forests – the most diverse, structurally complex, and heterogeneous ecosystems on Earth – remains under-explored. Using satellite-resolution LiDAR and imaging spectroscopy metrics, we map spatial turnover in tropical forest function, examine the relative importance of leaf traits and canopy structure, and analyze differences in aboveground carbon and demography. We find that leaf phosphorus, LMA, and canopy height are key distinguishing properties of forest types, achieving accuracies of 85-96% and correspond to differences in community growth and mortality rates. Our remotely sensed forest types align with ground-based forest definitions but enable mapping of their entire extent. At 30 m resolution, our method can be used at large scales with spaceborne data to reveal important differences in structure and function across tropical forests.

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED–2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the Eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥ 66%) experienced water-stress with declines in ET (up to 34%) and GPP (up to 35%), and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multi-year droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are not only driven by climate and deforestation, but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.