The jury chose to highlight the importance of Reich's fieldwork over several decades, with pioneering experiments that integrate information from hundreds of species all over the world.
These experiments have come up with two of the new laureate's most salient findings: the discovery of the links forged between leaf design features and the behavior of an entire ecosystem, be it Mediterranean woodland or tropical rainforest; and, secondly, the way that biodiversity losses impact on remaining species. Reich, the jury affirms, has provided "the first evidence that species diversity affects plant productivity and ecosystem stability".
These results are a wake-up call on the "adverse consequences" of biodiversity loss. They also suggest that the ability of ecosystems to sequester atmospheric carbon dioxide may have been considerably overestimated. "If this is true" the citation goes on, "atmospheric CO2 concentrations may rise faster than anticipated, and global climate change may occur faster than predicted".
FROM LEAF TO FOREST TO THE PLANETARY SCALE
The connecting thread in Reich's work is his ability to link ecosystem events at the smallest scales with global processes, as he strives to elucidate the relationship between different levels of complexity: from the seedling to the tree, from the cell to the ecosystem and from the stand to the biosphere. In this way, the ecosystem is conceptually assimilated to a single living organism.
It all starts with the leaf. "Leaves only have a few functions they have to provide for plants, and because of that they have a predictable set of characteristics, which allow us to predict a lot about how an entire grassland or forest or crop system will behave physiologically", explained Reich shortly after hearing of the award. The traits of a leaf and the behavior of an ecosystem are shaped by biophysical and evolutionary factors, so it is possible to "extrapolate or scale or predict from the
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| Contact: Silvia Churruca comunicacion@fbbva.es 34-913-745-210 Fundacin BBVA Source:Eurekalert |
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