Boffins tout computer models to save forests

Drew Purves, of Microsoft Research, claimed that the computational modelling of forest dynamics will play a huge role in understanding deforestation and climate change.

"The convergence of recently-developed mathematical models, improved data sources and new methods in computational data analysis could help produce more realistic models which will help inform how to manage the world’s forests and understand their impact on our climate," said a Microsoft spokeswoman.

Part of the research is included in the paper Animal Versus Wind Dispersal And The Robustness Of Tree Species To Deforestation, which is written by Purves and Daniel Montoya from the Madrid university and published in the journal Science today.

The second part of the research was conducted by Princeton's Stephen Pacala and Purves and appears as the paper Predictive Models of Forest Dynamics in the same journal.

Pacala's study describes how computational data analysis helped identify which tree species are at most risk following deforestation.

"This knowledge can be used to develop new strategies to mitigate the effects of widespread habitat loss and help to protect species diversity," a Microsoft statement said.

There are trillions of trees on the planet, but the effects of changes to the world's forests are still largely unknown compared with well-researched climate change factors such as ocean dynamics.

"Dynamic global vegetation models have shown that forests could be a crucial part of the way the Earth's climate responds to man-made CO2 emissions," said Purves.

"But insufficient understanding of forests, and insufficient data and computing power have made their predictions highly uncertain.

"This kind of uncertainty helps climate sceptics who erroneously conclude that, because the Earth is a complex but poorly understood system, we should not change our behaviour."

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