According to him, the model may not be perfect but you don't need a perfect model of something to make useful predictions: Tomorrow's weather, the effects of a drug, and the existence of subatomic particles like the Higgs Boson were all theorized from imperfect models. And he adds that, even without simulating bacteria or the effects of certain features like streams, researchers can reach predictions that match up to the real world. A rise in temperature, for example, would kill off certain plants and cause others to thrive, which would affect the soil they live in, the herbivores that feed on them, and the carnivores that feed on them. It could all be simulated within the model.

Purves elaborates: "What we are really missing is good data on the state of whole ecosystems... how much herbivore biomass there is in total, or, how many individuals of each size class?" After all, a thousand, big wildebeest may consume more grass than small ones, and seek out higher territories. And since every creature ends up recycled into the ecosystem again, every statistic is important to keep track of.

Parves also says that, this computational model can be a powerful source that not only advances science but can also affect policy making. With a true model of a state or region's ecosystem, the effects of dams, runoff, climate change, and other things can be calculated objectively and included as part of the lawmaking discussion.

On that front, the researchers have been collaborating with the United Nations Environment Programme World Conservation Monitoring Centre to help hone their work for political relevance and broaden its applications.

New updates to the project will be logged at the Computational Ecology and Environmental Science section of Microsoft Research.

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