Communications of the ACM
Scientists Enlist Big Data to Guide Conservation Efforts
Using data on Australias acacia trees, the new model maps areas of endemism the rainforests of southwest Western Australia, the Gascoyne region and Tasmania where conservation efforts might preserve rare and endangered species.
Credit: UC Berkeley NewsCenter
University of California, Berkeley researchers have developed the categorical analysis of neo- and paleoendemism (CANAPE), a model that uses big data to help identify the best areas to set aside as preserves and to help biologists understand the evolutionary history of life on Earth. CANAPE accounts for the number of species in a given area, as well as the variation among species and their geographic rarity.
"These new methods will allow assessment of conservation reserve coverage and identify complementary areas of biodiversity that have unique evolutionary histories in need of conservation," says Berkeley professor Brent Mishler.
He says the method is based on relative phylogenetic endemism because it is a better measure of diversity and rarity, and should be what researchers and policymakers examine when considering whether to conserve an area. However, Mishler notes the model can be used with any good georeferenced database of species abundance and relatedness.
The CANAPE technique starts with the branches connecting species in a specific region or phylogenetic diversity, but then assigns more weight to those branches that are endemic or restricted in range. "This provides a powerful conservation argument as well as a method of identifying areas containing endangered lineages we need to protect," Mishler says.
From UC Berkeley NewsCenter
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