Researchers and programmers have come up with modeling software for all kinds of complex systems, including modeling how the earth's systems may alter with climate change. But what has yet to be modeled is a deeply complex natural ecosystem from soil microbes and fungi all the way up to apex predators and giant trees. Just wrapping one's head around the scope of such a task is exhausting, and yet the knowledge that could be gained by creating such modeling software would be invaluable, and would help make smart policy changes regarding conservation. Which is why Microsoft is giving it a go. In fact, climate change models have been so successful, it's no wonder researchers are interested in using the same sort of system for biodiversity.
Drew Purves, head of Microsoft’s Computational Ecology and Environmental Science Group (CEES) and his colleagues at Microsoft Research in Cambridge, United Kingdom, are working with the United Nations Environment Programme World Conservation Monitoring Center (UNEP-WCMC) to create software that will accurately model a natural ecosystem -- or as they put it, a general ecosystem model (GEM).Microsoft's Green Blog states, "Building a GEM is challenging—but not impossible. Microsoft Research and the UNEP-WCMC have spent the past two years developing a prototype GEM for terrestrial and marine ecosystems. The prototype is dubbed the Madingley Model, and is built on top of another hugely ambitious project that the group just finished, modeling the global carbon cycle. With this as starting point, they set out to model all animal life too: herbivores, omnivores, and carnivores, of all sizes, on land in the sea."
The major challenge facing the project is, obviously, the need for as much data as possible. To make a GEM work, large-scale global collection of ecological data is needed. After all, how are we to model an ecosystem if we don't know much about how the ecosystem functions or even what organisms exist within it. The challenge needs to be met with the collaboration of all the governments around the world. If enough data can be collected and software devised to use the data for accurate modeling, then scientists would have an incredibly powerful new tool for illustrating how policy choices would affect ecosystems.