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The article discusses a study by N. Bochow and N. Boers, published in the issue, which designed a novel model of the coupled forest-atmosphere system and used it to search for signs of Amazon dieback. Topics include comparison of global climate model simulations, detection of early signs of Amazon Forest dieback, and avenues for future model improvements.

Amazon forest dieback is seen as a potential tipping point under climate change. These concerns are partly based on an early coupled climate–carbon cycle simulation that produced unusually strong drying and warming in Amazonia. In contrast, the fifth-generation Earth system models (Phase 5 of the Coupled Model Intercomparison Project, CMIP5) produced few examples of Amazon dieback under climate change. Here we examine results from seven sixth-generation models (Phase 6 of the Coupled Model Intercomparison Project, CMIP6), which include interactive vegetation carbon and in some cases interactive forest fires. Although these models typically project increases in area-mean forest carbon across Amazonia under CO2 -induced climate change, five of the seven models also produce abrupt reductions in vegetation carbon, which indicate localised dieback events. The northern South America (NSA) region, which contains most of the rainforest, is especially vulnerable in the models. These dieback events, some of which are mediated by fire, are preceded by an increase in the amplitude of the seasonal cycle in near-surface temperature, which is consistent with more extreme dry seasons. Based on the ensemble mean of the detected dieback events we estimate that 7±5 % of the NSA region will experience abrupt downward shifts in vegetation carbon for every degree of global warming past 1.5 ∘ C. [ABSTRACT FROM AUTHOR]

Long-term meteorological analyzes suggest an increase in air temperature and a decrease in rainfall over the Amazon biome. The effect of these climate changes on the forest remains unresolved, because field observations on functional traits are sparse in time and space, and the results from remote sensing analyses are divergent. Then, we analyzed the drought response in a 'terra firme' forest fragment in the southwestern Amazonia, during an extreme drought event influenced by ENSO episode (2015/2017), focusing on stem growth, litter production, functional traits and forest canopy dynamics. We use the Moderate Resolution Imaging Spectroradiometer (MODIS), corrected by Multi-Angle Implementation of Atmospheric Correction (MAIAC) to generate the enhanced vegetation index (EVI) and green chromatic coordinate (Gcc) vegetation indices. We monitor stem growth and measure the functional traits of trees in situ, such as the potential at which the plant loses 50% of hydraulic conductivity (P50), turgor loss point (πTLP), hydraulic safety margin (HSM) and isohydricity. Our results suggest that: (a) during the dry season, there is a smooth reduction in EVI values (browning) and an increase in the wet season (greening); (b) in the dry season, leaf flush occurs, when the water table still has a quota at the limit of the root zone; (c) the forest showed moderate resistance to drought, with water as the primary limiting factor, and the thickest trees were the most resistant; and (d) a decline in stem growth post-El-Niño 2015/2016 was observed, suggesting that the persistence of negative rainfall anomalies may be as critical to the forest as the drought episode itself. [ABSTRACT FROM AUTHOR]