Forestry and Other Land Use: Difference between revisions

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''This page is about the intersection of forestry and machine learning in the context of climate change mitigation and adaptation. For an overview of land use as a whole, please see the [https://en.wikipedia.org/wiki/Land_use Wikipedia page] on this topic.''[[File:Agriculture.png|thumb|A schematic of the ways that machine learning can support carbon negative agriculture, forestry, and land use.]]
Plants, microbes, and other organisms have been drawing CO2 from the atmosphere for millions of years. Most of this carbon is continually broken down and recirculated through the carbon cycle, and some is stored deep underground as coal and oil, but a large amount of carbon is sequestered in the biomass of trees, peat bogs, and soil. Our current economy encourages practices that are freeing much of this sequestered carbon through deforestation and unsustainable agriculture. On top of these effects, cattle and rice farming generate methane, a greenhouse gas far more potent than CO2 itself. Overall, land use by humans is estimated to be responsible for about a quarter of global GHG emissions<ref>{{Cite book|title=Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change|url=https://www.ipcc.ch/report/ar5/wg3/|date=2014|coeditors=O. Edenhofer, R. Pichs-Madruga, Y.