Amazonia is home to more than half of the world’s remaining tropical forests, playing a key role as reservoirs of carbon and biodiversity. However, whether at a slower or faster pace, continued deforestation causes forest fragmentation in this region. Thus, understanding the relationship between forest fragmentation and fire incidence and intensity in this region is critical. Here, we use MODIS Active Fire Product (MCD14ML, Collection 6) as a proxy of forest fire incidence and intensity (measured as Fire Radiative Power—FRP), and the Brazilian official Land-use and Land-cover Map to understand the relationship among deforestation, fragmentation, and forest fire on a deforestation frontier in the Brazilian Amazonia. Our results showed that forest fire incidence and intensity vary with levels of habitat loss and forest fragmentation. About 95% of active fires and the most intense ones (FRP > 500 megawatts) were found in the first kilometre from the edges in forest areas. Changes made in 2012 in the Brazilian main law regulating the conservation of forests within private properties reduced the obligation to recover illegally deforested areas, thus allowing for the maintenance of fragmented areas in the Brazilian Amazonia. Our results reinforce the need to guarantee low levels of fragmentation in the Brazilian Amazonia in order to avoid the degradation of its forests by fire and the related carbon emissions.

Full-waveform LiDAR (FWF) offers a promising advantage over other technologies to represent the vertical canopy structure of secondary successions in the Amazon region, as the waveform encapsulates the properties of all elements intercepting the emitted beam. In this study, we investigated modifications in the vertical structure of the Amazonian secondary successions across the vegetation gradient from early to advanced stages of vegetation regrowth. The analysis was performed over two distinct climatic regions (Drier and Wetter), designated using the Maximum Cumulative Water Deficit (MCWD). The study area was covered by 309 sample plots distributed along 25 LiDAR transects. The plots were grouped into three successional stages (early—SS1; intermediate—SS2; advanced—SS3). Mature Forest (MF) was used as a reference of comparison. A total of 14 FWF LiDAR metrics from four categories of analysis (Height, Peaks, Understory and Gaussian Decomposition) were extracted using the Waveform LiDAR for Forestry eXtraction (WoLFeX) software (v1.1.1). In addition to examining the variation in these metrics across different successional stages, we calculated their Relative Recovery (RR) with vegetation regrowth, and evaluated their ability to discriminate successional stages using Random Forest (RF). The results showed significant differences in FWF metrics across the successional stages, and within and between sample plots and regions. The Drier region generally exhibited more pronounced differences between successional stages and lower FWF metric values compared to the Wetter region, mainly in the category of height, peaks, and Gaussian decomposition. Furthermore, the Drier region displayed a lower relative recovery of metrics in the early years of succession, compared to the areas of MF, eventually reaching rates akin to those of the Wetter region as succession progressed. Canopy height metrics such as Waveform distance (WD), and Gaussian Decomposition metrics such as Bottom of canopy (BC), Bottom of canopy distance (BCD) and Canopy distance (CD), related to the height of the lower forest stratum, were the most important attributes in discriminating successional stages in both analyzed regions. However, the Drier region exhibited superior discrimination between successional stages, achieving a weighted F1-score of 0.80 compared to 0.73 in the Wetter region. When comparing the metrics from SS in different stages to MF, our findings underscore that secondary forests achieve substantial relative recovery of FWF metrics within the initial 10 years after land abandonment. Regions with potentially slower relative recovery (e.g., Drier regions) may require longer-term planning to ensure success in providing full potential ecosystem services in the Amazon.