"Until now, one of the most important pieces of the climate change jigsaw has been missing," Pacala said. "We argue that we can significantly further our understanding of forest dynamics if scientists work together to use new computational techniques and data sources provided governments and others make more data available in useful forms. We feel that these discoveries could unlock the climate change mysteries of forests on a global scale in as little as five years."
The second paper published in Science today, "Animal vs Wind Dispersal and the Robustness of Tree Species to Deforestation," by Daniel Montoya from the Universidad de Alcal in Madrid and Purves in Cambridge, with Miguel A. Rodrguez of the Universidad de Alcal and Miguel A. Zavala of Centro de Investigacin Forestal, Instituto Nacional de Investigacin y Tecnologa Agraria y Alimentaria (INIA-CIFOR) in Madrid, examines what happens to individual tree species in the face of deforestation. Using data from nearly 90,000 survey plots in the Spanish peninsula, the paper found tree species that rely on wind to disperse seeds, rather than animals, are more vulnerable to deforestation.
Montoya said, "By applying various methods in computational data analysis to a large source of forest data, we have confirmed that, in Spain at least, plants with animal-dispersed seeds are less vulnerable to habitat loss, because animals provide trees with an intelligent dispersal mechanism, travelling and distributing seeds between areas of remaining forest. In contrast, a wind dispersal method is more susceptible to habitat loss, as seeds are more likely to fall in inhospitable environments. Using methods like this, conservationists can identify the species at most risk following deforestation, and use th
|Contact: Rosanna Hill|
Microsoft Research Cambridge