This story excerpt was translated from Portuguese. To read the original story in full, visit National Geographic. You may also view the original story on the Rainforest Journalism Fund website here. Our website is available in English, Spanish, bahasa Indonesia, French, and Portuguese.
Scientists from the National Institute of Amazonian Research have returned to the field to rescue lost information, compose new scenarios, create questions, and draw futures about the largest tropical forest in the world.
Amazonas was one of the Brazilian states most affected by the COVID-19 pandemic, with more than 600,000 cases, 14,000 deaths, and the epicenter of two severe epidemic waves. However, the pandemic period did not prevent criminal actions that caused the highest rate of deforestation in the Legal Amazon in 15 years, according to the Institute of Man and Environment of the Amazon. The loss of vegetation in the Amazon state represented the worst variation in the biome, with a 50% increase from August 2021 to July 2022.
Scientific work in the field was paralyzed for two years at the National Institute for Amazon Research (Inpa), located in Manaus, the capital of Amazonas. During this period, the researchers at Inpa, one of the largest centers of science in the biome, felt the loss of people who had dedicated years and passion to studying the forest's biodiversity, such as the death of the agronomist and former director of the institute, Enéas Salati, in February this year.
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The impossibility of going into the field for health reasons has opened a huge question mark over the continuity of the studies, the absence of information in the period, and even the loss of sponsorship and support. Some data that could only be collected in situ will be unrecoverable. However, in this period there have been a number of discoveries from materials already collected, an alternative of science during the pandemic seclusion.
In the second quarter of this year, Inpa researchers began to restructure their work, continue their research, review studies, and understand the ways to recover the break in the sequence of data production.