The Amazon rainforest is among the Earth’s climate tipping elements. Under ongoing global warming, the frequency of severe droughts such as in 2005 and 2010 is projected to increase strongly, up to the point where these droughts may become the new climate normal in the second half of this century. Taking into account the adaptation of the forest to past environmental conditions, we find that nonlinear thresholds in the hydrological balance of the rainforest might be exceeded under drier future conditions, leading to self-amplified forest transitions. Thereby, we reveal that the lack of moisture recycling in some parts of the forest can be propagated downwind by the reduction of atmospheric moisture transport, resulting in approximately one-third of all tipping events.
Tipping elements are nonlinear subsystems of the Earth system that have the potential to abruptly shift to another state if environmental change occurs close to a critical threshold with large consequences for human societies and ecosystems. Among these tipping elements may be the Amazon rainforest, which has been undergoing intensive anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations from climatological rainfall regimes may cause local forest collapse that cascades through the coupled forest–climate system. We develop a conceptual dynamic network model to isolate and uncover the role of atmospheric moisture recycling in such tipping cascades. We account for heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, a future climate characterized by permanent drought conditions could trigger a transition to an open canopy state particularly in the southern Amazon. The loss of atmospheric moisture recycling contributes to one-third of the tipping events. Thus, by exceeding local thresholds in forest adaptive capacity, local climate change impacts may propagate to other regions of the Amazon basin, causing a risk of forest shifts even in regions where critical thresholds have not been crossed locally.