A special issue of the Ecological Society of America's journal Frontiers in Ecology and the Environment has set out a definition of the new field and provides strategies for ecologists to do this type of research.
"Ecologists can no longer sample and study just one or even a handful of ecosystems," said Patricia Soranno, a Michigan State University professor of fisheries and wildlife and a macrosystems ecology pioneer.
"We also need to study lots of ecosystems and use lots of data to tackle many environmental problems such as climate change, land-use change and invasive species, because such problems exist at a larger scale than many problems from the past," said Soranno, who co-edited the special journal issue with Dave Schimel from the California Institute of Technology.
Data-intensive science, being promoted as a new way to do science of any kind, has great potential for ecology, Soranno said.
"Traditionally, ecologists are trained by studying and taking samples from the field in places like forests, grasslands, wetlands or water and measuring things in the lab," she said in an MSU release Monday. "In the future, at least some ecologists will need to also be trained in advanced computational methods that will allow them to study complex systems using big datasets at this large scale and to help integrate fine and broad-scale studies into a richer understanding of environmental problems."
Analysis that once took months or years to complete can now be conducted in hours or days using large amounts of data and supercomputers, she said.
"Even ten years ago, it would have been much harder to take this approach," Soranno said. "We didn't have the wonderful intersection that we have today of great tools, volumes of data, sufficient computing power and a better developed understanding of systems at broad scales."