BOSTON, Jan. 4 (UPI) -- New analysis suggests climate-inspired ecological changes in the Amazon won't be quite as dramatic as previously predicted.
Recent studies have suggested climate change will hasten a collapse of Amazonian rainforests, paving the way for the proliferation of treeless savannahs.
In a new PNAS paper, however, scientists at Harvard University argue those projections are inaccurate. Their models suggest the Amazon will experience a slow transition -- as a result of climate change -- "from high-biomass moist forests to transitional dry forests and woody savannah-like states."
According to the new analysis, previous prediction models erroneously treated the Amazon as a homogeneous ecosystem.
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"In earlier approaches, they use an aggregated representation of the ecosystem," senior study author Paul Moorcroft, a professor of evolutionary biology at Harvard, said in a press release. "One way to think about it is they're modeling an average tropical tree in an average tropical environment. But because of that, when the system responds, it all responds at once, because it's essentially all the same."
"In reality, ecosystems have a variety of individual plants, with different plants in different locations," Moorcroft explained. "Our approach is to capture that heterogeneity, and what we were able to show is that this predicts a more graded response to climate change."
The new model, called Ecosystem Demography, or ED2, tries to incorporate the concept that different trees in different places will respond differently to climate change. The model's outputs suggest a drying climate will result in a gradual transition -- not an all-or-nothing transformation.
"Our analysis predicts that as the climate changes, the ecosystem will respond almost immediately, but those changes will be less drastic, so in some sense it says the ecosystem is both more vulnerable and more resilient," Moorcroft said.
Researchers say more work needs to be done to predict how a transition toward low-biomass forests will affect precipitation patterns, agriculture, hydroelectric power and biodiversity.
