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Automated Red Listing using Artificial Intelligence

How can we conserve as much plant diversity as possible for future generations?

Zizka et al., Diversity and Distributions 28(2), Wiley

Effective and engaged conservation is essential in the face of the ongoing biodiversity crisis. Red Lists of threatened species quantify species extinction risk and are a key tool in conservation research, practice and communication. Yet, due to the time-intense red-listing process, most Red lists are biased towards well-studied taxa (mammals, birds) and regions and temperate regions) while only a fraction of other groups such as plants or soil organisms are evaluated, meaning that important conservation decisions miss key components of biodiversity. We develop automated conservation assessments that use machine learning approaches to approximate species Red List status based on information from biological collections, floras and remote sensing data. In collaboration with Researchers from other European institutions we develop algorithms and software applying large datasets and deep learning to approximate species extinction risk in a Red List framework (Zizka et al. 2022). Recently we have applied this approach to quantify the extinction risk of orchid species worldwide (Zizka et al. 2022).