Deforestation: geographers find a “point of no return”

There is a kind of point of no return in terms of the level of deforestation that the forest then disappears very quickly. This is what some researchers at the University of Cincinnati theorized according to a statement that appeared on the university’s website.

The study, published in Geophysical Research Letters, is based on the analysis of high-resolution satellite images found by the satellites of the European Space Agency. The geographer Tomasz Stepinski, together with his colleague Jakub Nowosad, analyzed these images, dating back to the period between 1992 and 2015, and found that once you reach about half of them, the forest then begins to disappear very quickly and this applies to different environments, periods and areas, which suggests a sort of “ground rule”.

The two researchers discovered that nature hates “mixed” landscapes, at least on a scale of up to 81 square kilometres. In practice, landscapes made from different environments, such as cultivated fields and forest, tend, with the passage of time, to mix and become homogeneous and this seems a sort of law independent of the type of landscape.

According to the two researchers it is something “very intuitive”: “Planet Earth wants to be homogeneous. The Earth wants to be the same in all these areas. And when they start to change, they don’t stop until they convert everything into another homogeneous block”.

This means that once the deforestation of a certain area has started and if it exceeds a certain point, nature itself will, in a certain sense, strive to ensure that the whole area is not covered by too many trees.

Researchers have not yet understood the reasons why these “blocks”, once the transition has begun and once they have reached a certain point, seem to trigger a sort of process through which the change takes place more quickly, in a long-term vision.

According to Nowosad, it would be useful to carry out new studies to understand if there are “turning points for other landscape transitions”: “This model can be used to help understand how landscapes have evolved and will evolve in the future”.

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