Abstract
Deforestation of the Amazon may reach a critical point where abrupt declines in rainfall could cause widespread forest dieback.
The Amazon Forest, the world’s largest tropical forest and a megadiverse ecosystem that regulates local, regional, and global climate, is facing many threats. Climate change causes warming and is altering rainfall patterns (1). Deforestation carves deeper into the Amazon each year, and nearly 20% of the Amazon has already been cleared (1). Deforestation reduces the amount of water that the forest pumps back into the atmosphere, resulting in further reductions in rainfall (2).
How resilient is the Amazon Forest to these threats? Some studies have suggested that global warming of 3°C or clearance of between 20 and 40% of the Amazon could cause rainfall to decline so much that the rest of the Amazon Forest can no longer survive (3). This is known as Amazon dieback and is a potential tipping point in our Earth system (4): Death of the forest would lead to a large pulse of carbon dioxide emissions that would further accelerate climate change. The future of the Amazon is therefore critical not only to the 50 million people who live there but also to everyone on our planet.
Researchers have used climate models to test the probability of Amazon dieback (5). But how well do these models capture the complex interactions and feedbacks between the forest, atmosphere, and climate? A worry is that climate models may underestimate the sensitivity of the forest-climate system. If this is the case, the Amazon may be in imminent danger of crossing climate or deforestation thresholds that can result in large-scale loss of the Amazon Forest.
In this issue of Science Advances, Bochow and Boers (6) design a novel model of the coupled forest-atmosphere system and use it to search for signs of Amazon dieback. Instead of using a traditional climate model, they design a dynamical model of the Amazon Forest–climate system. The model includes the key interactions between the forest, atmosphere, and climate simulated as a parcel of air moves across the Amazon basin. The model simulates the reduction in evapotranspiration (the land-atmosphere flux of water) due to deforestation and the reduction in the inflow of atmospheric moisture due to the associated reduction in latent heating. The model also includes an interaction between vegetation and soil moisture, with tree mortality occurring when soil moisture falls below a critical threshold.
They then use the model to simulate forest, atmosphere, and climate responses under incremental deforestation (Fig. 1). At first, the model simulates a gradual decline in rainfall as the deforestation extent expands. Then, as deforestation reaches a critical threshold, an abrupt decline in rainfall is simulated with rainfall declining by 30 to 50%. This occurs because of a rapid collapse of incoming moisture driven by the reduction in latent heating due to forest loss. When the model includes the feedback between vegetation and soil moisture, the system becomes even more sensitive, the decline in rainfall becomes more abrupt and the critical deforestation threshold occurs as much as 8 years earlier. Unlike many other studies, this simulation accounts for nonlinear interactions between the vegetation and atmosphere, allowing isolation of such potential tipping points.
Fig. 1. The impacts of deforestation on rainfall in the Amazon.
Deforestation causes reductions in evapotranspiration and moisture inflow within the Amazon, leading to reductions in rainfall; declining rainfall can cause tree mortality, resulting in additional deforestation (top right schematic). The graph shows the impacts of deforestation on rainfall. As the deforested area expands (moving from left to right on the x-axis), rainfall declines gradually at first (y-axis) until a critical deforestation threshold is reached where rainfall declines abruptly (solid line). When the model includes coupled atmosphere-vegetation dynamics, the critical threshold occurs when less of the Amazon has been deforested (and therefore likely to occur earlier), and the decline in rainfall is more rapid (dashed line). Illustration credit: Ashley Mastin/Science Advances.
DETECTING EARLY SIGNS OF AMAZON FOREST DIEBACK
Bochow and Boers use this tool to identify early warning signs that the Amazon Forest is approaching a potential tipping point. Declines in soil moisture and a lengthening of the dry season precede rapid deforestation-induced declines in rainfall. Searching historical climate reanalysis data, Bochow and Boers found clear evidence for emerging signals. Over the past 40 years, soil moisture across the Amazon declined with the dry season lengthening by 5 to 15 days, primarily due to later onset of the wet season.
Previous studies have found that deforestation causes self-amplified forest loss through a weakening of moisture recycling across the Amazon (7). Another theory known as the “Biotic Pump” also suggests that forests play a crucial role in atmospheric moisture transport with forests maintaining atmospheric winds and deforestation causing strong declines in rainfall (8). The Bochow and Boers study further points to the possibility that the forest itself strongly controls rainfall in the Amazon.
In comparison, global climate model simulations indicate that extensive deforestation of the Amazon would only cause a −11 to +2% change in basin-wide rainfall (9), insufficient to initiate widespread dieback of the Amazon Forest. Why do the climate models simulate a lower sensitivity of rainfall to deforestation? Most, but not all, of the climate models simulate that deforestation causes a reduction in evapotranspiration, in agreement with Bochow and Boers. However, the magnitude of the reduction is much smaller in the climate models (9), possibly explaining their lower sensitivity. A crucial unknown is whether deforestation leads to increased or decreased inflow of atmospheric moisture. Some climate model simulations suggest that deforestation of the Amazon causes increased inflow of atmospheric moisture (9), offsetting some of the reduction in moisture due to reduced evapotranspiration. This is opposite to the response assumed by Bochow and Boers. New studies are needed that test how the sensitivity of simulated atmospheric moisture and rainfall to deforestation varies with assumed land-surface properties in the model. The simulated sensitivity then needs to be carefully evaluated against measurements. This should help determine whether climate models are underestimating the sensitivity of rainfall to deforestation in the Amazon.
AVENUES FOR FUTURE MODEL IMPROVEMENTS
Another reason for the lower sensitivity of climate models may be their coarse spatial resolution, with grid squares of 100 to 300 km necessitating a simple representation of complex land-atmosphere interactions. In particular, the process of convection, which is crucial for simulation of rainfall, is calculated through parameterizations that may not correctly represent the interactions between the land and atmosphere. New computing power allows climate models to run at the kilometer scale that is required for an explicit simulation of convection (10), allowing researchers to explore land-atmosphere interactions in unprecedented detail. This may help improve projections of the rainfall response to deforestation.
Bochow and Boers show that the forest-climate system is much more sensitive to deforestation when vegetation feedback loops are included. But we urgently need a better understanding of these processes. In particular, we need to know how resilient the forest is to drought. Emerging information from long-term drought experiments can assist with advancing understanding in this area. A network of monitoring plots across the Amazon Forest has detected a reduction in carbon sequestration over the past 30 years due to increased tree mortality (11), possibly resulting from increased climate variability. This may be another early warning signal of the negative impacts of a changing climate. Forest degradation and fire are now widespread across the Amazon, but these processes are not included in many climate models. Clearly, climate models need to be further improved and tested to ensure that they are providing policy-relevant information (12) and not underestimating the impacts of deforestation.
Another big uncertainty not addressed in the model designed by Bochow and Boers is how the forest will respond to increasing carbon dioxide concentrations, which may result in further declines in rainfall (5) . Insights may be gained from the Amazon Free-Air Carbon Dioxide Enrichment (AmazonFACE) experiment that will study the response of Amazon forests to increased carbon dioxide concentrations. This experiment will provide vital data to help understand how forests will respond in the future.
A major weakness in our current understanding is that we still do not know the critical deforestation threshold that will initiate Amazon Forest dieback. Each year, more of the Amazon is cleared, pushing the system closer to this unknown threshold. Deforestation rates in the Amazon have varied greatly over the past two decades (1). In the Brazilian Amazon, deforestation rose to a decadal high in 2021. Since then, new political leadership has helped bring deforestation under control, and deforestation rates in the Brazilian Amazon have declined in recent months. This buys the Amazon some more time. But how much time the Amazon has left is unknown.
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