Researchers from the University of Bristol have found the evidence that Amazon rainforest is far more resilient to deforestation than the previous prediction. However, the impact of Amazon deforestation has decreased with the absence of bistability, as the research discovered.
According to the news release from the University of Bristol, the researchers have found that the dynamic bistability was absence in the Amazon reforestation. As a result, the Amazon rainforest regrows faster than estimated.
Bistability is a condition of two stable equilibrium states in a nonlinear dynamic system. For years, scientists have believed that after the Amazon deforestation, the shock from the forest clearance of drought will lead to the increase of fire occurrence in the area. Then, the area will become savannah for a long period before the trees grow back.
However, such dynamic does not occur in the case of Amazon deforestation. The research from the Ph.D. student at the University of Bristol, Bert Wuyts found the bistability does not appear after the Amazon deforestation. This makes the trees in Amazon rainforest regrow faster than previously predicted.
The research has been published in the journal Nature Communication. Wuyts was supervised by the Professor of Applied Non-linear Mathematics at Bristol University Alan Champneys and the Professor in the School of Geographical Science, Joanna House. Wuyts presented his mathematical modeling of the aftermath of Amazon deforestation in the paper titled "Amazonian Forest-Savanna Bistability And Human Impact."
"I decided to take a fresh look at the data," Wuyts explained his research on the Amazon deforestation. "Suddenly the property of bistability disappeared almost completely.”
Wuyts gather the satellite data of Amazon deforestation for his research and analyzed the mathematical model of the rainforest. For two years, he examined the data and concluded that the Amazon rainforest is more resilient to deforestation than estimated. Watch the time lapse of Amazon deforestation below:
