The carbon debt from Amazon forest degradation: integrating airborne lidar, field measurements, and an ecosystem demography model.

Amazon deforestation has declined over the last decade, yet forest degradation from logging, fire, and fragmentation continue to impact forest carbon stocks and fluxes. The magnitude of this impact remains uncertain, and observation-based studies are often limited by short time intervals or small study areas. To better understand the long-term impact of forest degradation and recovery, we have been developing a framework that integrates field plot measurements and airborne lidar surveys into an individual- and process-based model (Ecosystem Demography model, ED). We modeled forest dynamics for three forest landscapes in the Amazon with diverse degradation histories: conventional and reduced-impact logging, logging and burning, and multiple burns. Based on the initialization with contemporary forest structure and composition, model results suggest that degraded forests rapidly recover (30 years) water and energy fluxes compared with old-growth, even at sites that were affected by multiple fires. However, degraded forests maintained different carbon stocks and fluxes even after 100 years without further disturbances, because of persistent differences in forest structure and composition. Recurrent disturbances may hinder the recovery of degraded forests. Simulations using a simple fire model entirely dependent on environmental controls indicate that the most degraded forests would take much longer to reach biomass typical of old-growth forests, because drier conditions near the ground make subsequent fires more intense and more recurrent. Fires in tropical forests are also closely related to nearby human activities; while results suggest an important feedback between fires and the microenvironment, additional work is needed to improve how the model represents the human impact on current and future fire regimes. Our study highlights that recovery of degraded forests may act as an important carbon sink, but efficient recovery depends on controlling future disturbances.