Biodiversity

''This page is about the intersection of ecosystems and machine learning in the context of climate change adaptation. For an overview of biodiversity monitoring as a whole, please see the Wikipedia page on this topic.''

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.

Ecology

 * Camera trap image classification
 * Analysis of citizen science data
 * Environmental sensor network analysis

Primers

 * "AI empowers conservation biology" (2019) : A high-level overview of this problem space. Available here.
 * "Climate, biodiversity, and land: using ML to protect and restore ecosystems" (2020) : An overview talk, with pointers to practical starting points. Available here.

Textbooks


 * "Artificial Intelligence and Conservation" (2019) : A curated collection of case studies. Book description here.

Other

 * Natural Solutions Toolkit : Example in-the-field implementations. Available here.

Journals and conferences

 * PLOS Collections: A collection featuring work on the ecological impacts of climate change, available here.

Data

 * Camera Trap ML Survey: An overview of datasets used in current camera trap machine learning projects, available here.