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Amazon forests are becoming increasingly vulnerable to disturbances such as droughts, fires, windstorms, logging, and forest fragmentation, all of which lead to forest degradation. Nevertheless, quantifying the extent and severity of disturbances and their cumulative impact on forest degradation remains a significant challenge. In this study, we combined multispectral data from Landsat sensors with hyperspectral data from the Earth Observing-One (Hyperion/EO-1) sensor to evaluate the efficacy of multiple vegetation indices in detecting forest responses to disturbances in an experimentally burned forest in southeastern Amazonia. Our experimental area was adjacent to an agricultural field and consisted of three 50-ha treatments – an unburned Control, a plot burned every three years, and a plot burned annually from 2004 to 2010. All plots were monitored to assess vegetation recovery after fire disturbance. These areas were also affected by three drought events (2007, 2010, and 2016) over the study period. We evaluated a total of 18 Vegetation Indices (VI), one unique to Landsat, 12 unique to Hyperion/EO-1, and five commons to both satellites (i.e., 6 total from Landsat and 17 from Hyperion). We used linear models (LM) to evaluate how changes in ground observations of forest structure (biomass, leaf area index [LAI], and litter production) associated with fire were captured by the two VIs most sensitive to forest degradation. Our results indicate that the Plant Senescence Reflectance Index (PSRI) derived from Hyperion/EO-1 was the most sensitive to vegetation changes associated with forest fires, increasing by 94% in burned vs. unburned forests. Of the Landsat-derived VIs, we found that the Green-Red Normalized Difference (GRND) were the most sensitive to forest degradation by fire, showing a marked decline (87%) in the burned plots compared with the unburned Control. However, compared to PSRI, the GRND was a better predictor of changes associated with fire, both in the forest interior or forest edge, for the three ground variables: biomass stocks (r2 =0.5–0.8), LAI (r2=0.8–0.9), and litter production (r2=0.4–0.7). This study demonstrate that VIs can detect forest responses to fire and other disturbances over time, highlighting the relative strengths of each VI. In doing so, it shows how the integration of multispectral and hyperspectral data can be useful for monitoring tropical forest degradation and recovery. Moreover, it provides valuable insights into the limitations of existing approaches, which can inform the design of next-generation sensors for global forest monitoring. 

Tropical ecosystems store over half of the world’s aboveground live carbon as biomass, and water availability plays a key role in its distribution. Although precipitation and temperature are shifting across the tropics, their effect on biomass and carbon storage remains uncertain. Here we use empirical relationships between climate and aboveground biomass content to show that the contraction of humid regions, and expansion of those with intense dry periods, results in substantial carbon loss from the neotropics. Under a low emission scenario (Representative Concentration Pathway 4.5) this could cause a net reduction of aboveground live carbon of ~14.4–23.9 PgC (6.8–12%) from 1950–2100. Under a high emissions scenario (Representative Concentration Pathway 8.5) net carbon losses could double across the tropics, to ~28.2–39.7 PgC (13.3–20.1%). The contraction of humid regions in South America accounts for ~40% of this change. Climate mitigation strategies could prevent half of the carbon losses and help maintain the natural tropical net carbon sink. 

Amazon forests are undergoing rapid transformations driven by deforestation, climate change, fire, and other anthropogenic pressures, leading to the hypothesis that they may be nearing a catastrophic tipping point—beyond which ecosystems could shift to a permanently altered state. This review revisits the concept of an Amazon tipping point and assesses the risk of forest collapse from an ecological perspective. We synthesize evidence showing that environmental stressors can drive critical ecosystem transitions, either gradually through incremental loss of resilience or abruptly via synergistic feedbacks. The interplay between climate and land-use change amplifies risks to biodiversity, ecosystem services, and livelihoods. Yet, there is limited evidence for a single, system-wide tipping point. Instead, the Amazon's resilience—although not unlimited—offers meaningful pathways for recovery. The most immediate and effective strategies to support this resilience include slowing forest loss, mitigating climate change, reducing fire activity, curbing defaunation, and restoring degraded ecosystems. Without decisive action to address direct threats, the Amazon system may be pushed beyond safe ecological-climatological operating limits—even in the absence of sharply defined thresholds—due to the scale and persistence of anthropogenic pressures. Preserving the Amazon's ecological integrity and its vital role in regulating the global climate requires urgent, sustained conservation efforts in collaboration with local and Indigenous communities. 

Abstract Soil moisture is a crucial variable mediating soil‐vegetation‐atmosphere water exchange. As climate and land use change, the increased frequency and intensity of extreme weather events and disturbances will likely alter feedbacks between ecosystem functions and soil moisture. In this study, we evaluated how extreme drought (2015/2016) and postfire vegetation regrowth affected the seasonality of soil water content (0–8 m depth) in a transitional forest in southeastern Amazonia. The experiment included three treatment plots: an unburned Control, an area burned every three years (B3yr), and an area burned annually (B1yr) between 2004 and 2010. We hypothesized that (a) soil moisture at B1yr and B3yr would be higher than the Control in the first years postfire due to lower transpiration rates, but differences between burned plots would decrease as postfire vegetation regrew; (b) during drought years, the soil water deficit in the dry season would be significantly greater in all plots as plants responded to greater evaporative demand; and (c) postfire recovery in the burned plots would cause an increase in evapotranspiration over time, especially in the topsoil. Contrary to the first expectation, the burned plots had lower volumetric water content than the Control plot. However, we found that droughts significantly reduced soil moisture in all plots compared to non‐drought years (15.6%), and this effect was amplified in the burned plots (19%). Our results indicate that, while compounding disturbances such as wildfires and extreme droughts alter forest dynamics, deep soil moisture is an essential water source for vegetation recovery.