resilience

Scientists have made a counterintuitive discovery about the Amazon rainforest

This is absolutely not what they expected to find.

Photo by Diego Baravelli/picture alliance via Getty Images

When it comes to climate change and the Amazon rainforest, the news is never good. Through 2019 and 2020, the news has been dominated by images of forests ablaze, and a land wracked by climate change and illegal logging.

But there's still a lot scientists don't yet know about the mysterious Amazon.

A new study published Friday in Science Advances is a case in point. In the study, scientists reveal some puzzling ecological traits in the wettest regions of the Amazon, suggesting the rainforest may be tougher than we think.

Neural networks — In the study, scientists look at the relationship between increasing air dryness (also known as vapor pressure deficit) and gross primary production in the Amazon.

Gross primary production refers to the total amount of carbon that plants in forest "fix," or uptake during photosynthesis.

The scientists used observational data from a nine-year period between June 2007 and May 2016, inputting the data into a machine learning tool known as an artificial neural network. These networks helped the researchers analyze and compare their results with existing models and simulations of how dry air changes the Amazon's ability to act as a carbon sink.

"What I wanted to do was basically use different environmental predictors and input those into a model so that I could predict changes in photosynthesis," Julia K. Green, lead author on the study and researcher at Laboratoire des Sciences du Climat et l'Environnement in France, tells Inverse.

Aerial view showing a boat speeding on the Jurura river in the municipality of Carauari, in the heart of the Brazilian Amazon Forest, on March 15, 2020Photo by FLORENCE GOISNARD/AFP via Getty Images

Simulation v. Reality — Armed with their model, Green and her colleagues then compared typical predictions of land surface simulations to what's actually going on in the Amazon.

"These are the models that we're using to make climate change predictions. And so our predictions can only be as good or as accurate as those models are," Green says.

The wetter parts of the Amazon boast trees with deep root systems. But the models show that vegetation in these areas can become stressed due to "water deficit," caused by increasingly dry air or soil, Green says. That water deficit can severely impact photosynthesis.

"Plants have these little pores on their leaves called stomata. And what ends up happening is that to basically take carbon dioxide in, the plant has to open the stomata on their leaf to allow the gas to be absorbed," Green explains.

But as the "plant takes some carbon dioxide, it loses water through that through the leaf surface, because the air is drier," Green says. As a result: "the drier the air, the more closed the stomata are going to become" in order to conserve water, she explains.

The researchers assumed — and so did their models — that the closing of the stomata from air dryness would reduce photosynthesis.

Magnification of the underside of an oak leaf, with stomata evident, drawingPhoto by DeAgostini/Getty Images

"What we were seeing is that in model simulations with just a little bit of dryness, the photosynthesis in these rainforest regions was really decreasing in the models. And we weren't sure if that necessarily seemed realistic," Green says.

That's where the artificial neural networks came in — Green used their findings to come up to a surprising conclusion: The simulation models were wrong.

"What we ended up seeing is that as vapor pressure deficit increases, that photosynthesis in these really, really wet areas of the forest [increases]," she explains.

The reason why is to do with the nature of the Amazon forest itself. The Amazon has a very "dynamic" forest canopy, Green says, which compensates for the closing of the stomata, counterintuitively increasing photosynthesis.

"After the air starts to dry, what ends up happening is that the forest ends up shedding a lot of these old leaves at the top of the canopy," Green says. "New younger leaves end up replacing them. And these new younger leaves have much higher photosynthetic capacity than the leaves that they're replacing."

Brazil, Sao Gabriel da Cachoeira: Aerial view of the Amazon forest near Sao Gabriel da CachoeiraPhoto by Diego Baravelli/picture alliance via Getty Images

A natural resilience — The Amazon serves one of the world's most important carbon sinks. And that carbon sink relies on photosynthesis to survive.

But these results suggest the Amazon has its own natural resilience during periods of drier air. But whether the findings suggest the Amazon holds up better against extreme weather events, like drought brought on by climate change, is unclear, Green says.

"This study, while it is showing that the forests are more resilient to air dryness than we thought and what's depicted, it's not saying that should air dry out to levels that we haven't seen so far that it's going to be okay," Green says.

Abstract: Earth system models predict that increases in atmospheric and soil dryness will reduce photosynthesis in the Amazon rainforest, with large implications for the global carbon cycle. Using in situ observations, solar-induced fluorescence, and nonlinear machine learning techniques, we show that, in reality, this is not necessarily the case: In many of the wettest parts of this region, photosynthesis and biomass tend to increase with increased atmospheric dryness, despite the associated reductions in canopy conductance to CO2. These results can be largely explained by changes in canopy properties, specifically, new leaves flushed during the dry season have higher photosynthetic capacity than the leaves they replace, compensating for the negative stomatal response to increased dryness. As atmospheric dryness will increase with climate change, our study highlights the importance of reframing how we represent the response of ecosystem photosynthesis to atmospheric dryness in very wet regions, to accurately quantify the land carbon sink.
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