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Study maps Earth based on climate change vulnerability


Daniel Martins
Digital Reporter

Sunday, February 21, 2016, 1:23 PM - We know climate change can put a strain on global ecosystems, but new research has given one of the clearest pictures yet as to what areas, exactly, are most at risk.

Using satellite data from 2000 to 2013, researchers come come up with a "vegetation sensitivity index," essentially a map of the world based on climate change sensitivity over the previous 14 years.

"We have found ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, forests in South America, and eastern areas of Australia,” biologist and lead author Alistair Seddon said in a release from the University of Bergen.

Canada has plenty of Arctic tundra and prairie territory to go around, and the study shows the most of the Prairies, the northern mainland of Canada's Arctic territories, and much of the Yukon shows the greatest sensitivity to climate change within Canada's own borders.

But Canada gets off lightly compared to other parts of the world, like the Russian Arctic, Amazon and Indonesian rainforests, and the Andes mountains of South America are especially hard-hit.

Image: LEFT/Bergen University

The researchers used satellite-recorded data on air temperature, water availability and cloud cover to determine how much those areas had changed under climate change. Seddon says this kind of information can be useful for national-scale assessments of ecosystems.

"Even more interesting is that as satellite measurements continue and so as the datasets get longer, we will be able to recalculate our metric over longer time periods to investigate how and if ecosystem sensitivity to climate variability is changing over time," he says.

The study was published in the February issue of Nature.

SOURCES: Nature | University of Bergen

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