Biodiversity: Difference between revisions
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== Machine Learning Application Areas ==
*[[Species Identification|Species identification]]: Machine learning tools are increasingly being used to help in the identification of organisms, both from photographic documentation and (in cases such as birds) audio recordings. These tools are deployed in personal apps and as part of citizen science projects, as well as within formal scientific monitoring efforts.
*[[Ecosystem Monitoring|Ecosystem monitoring]]: Understanding the overall state of an ecosystem can be valuable both in preserving biodiversity and in maintaining ecosystem services such as food, wood, pollination, and carbon sequestration. Machine learning has the potential to scale and democratize ecosystem monitoring.
*[[Biodiversity Data Analysis|Biodiversity data analysis]]: There is an increasing wealth of data available on biodiversity, species distributions, and ecosystem health (including some data gathered using ML approaches). Machine learning can be useful in working with this data and analyzing trends.
== Background Readings ==
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