Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 67 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of -4.14 +/- 0.76 MgC/hay. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data

Effects of Tropical Forest Degradation on Amazon Forest Phenology

Anthropogenic disturbances in tropical forests cause short-and long-term alterations in forest structure, species composition, and successional processes. However, improved understanding of the impacts of disturbance on forest functioning is needed to support forest management and conservation. In this study, we investigated the phenological responses of two sites in the Brazilian Amazon to forest degradation (selective logging and forest fires). We used MODIS-derived time-series to assess pre- and post-disturbance trajectories of two vegetation indices: Normalized Burn Ratio (NBR) and Enhanced Vegetation Index (EVI). We found that our study sites present different VI seasonality, and that selective logging did not cause phenological shifts. Fires, on the other hand, caused explicit EVI shifts in the transition from wet to dry season in the driest site and barely no shifts in the wettest site, and yearlong NBR shifts compared to intact forests at both sites. Changes in the magnitude and timing of phenological events highlight human-induced changes in tropical forests functioning. If widespread, these shifts may have large-scale implications for carbon sink stability in tropical regions