Biodiversity: Difference between revisions
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== Recommended Readings == |
== Recommended Readings == |
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For a curated collection of case studies, consider, |
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* [https://www.cambridge.org/core/books/artificial-intelligence-and-conservation/17C33AF856648B208E47A10813CEC6DF Artificial Intelligence and Conservation] |
* [https://www.cambridge.org/core/books/artificial-intelligence-and-conservation/17C33AF856648B208E47A10813CEC6DF Artificial Intelligence and Conservation]: A curated collection of case studies. |
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A high-level |
* [https://www.nature.com/articles/d41586-019-00746-1 ''AI empowers conservation biology'']: A high-level overview of this problem space. |
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* [https://www.nature.com/articles/d41586-019-00746-1 ''AI empowers conservation biology''] |
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Further examples of conservation agency led efforts include, |
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Talks on this subject include, |
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== Community == |
== Community == |
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Revision as of 00:08, 13 August 2020
Changes in climate are increasingly affecting the distribution and composition of ecosystems. This has profound implications for global biodiversity, as well as agriculture, disease, and natural resources such as wood and fish. Machine learning can help by supporting efforts to monitor ecosystems and biodiversity.
Data
Methods and Software
Recommended Readings
- Artificial Intelligence and Conservation: A curated collection of case studies.
- AI empowers conservation biology: A high-level overview of this problem space.
- Natural Solutions Toolkit: Example in-the-field implementations.
- Climate, biodiversity, and land: using ML to protect and restore ecosystems: An overview talk, with pointers to practical starting points.
Community
Journals and conferences
- PLOS Collections - Ecological Impacts of Climate Change