More than 15,000 plant species have a high probability of being considered threatened or near-threatened under a new model used to predict conservation status.
More than 15,000 plant species have a high probability of being considered threatened or near-threatened under a new model used to predict conservation status. The model, which shows the predicted levels of risk to plants worldwide, was published as part of a study to help governments and resource managers evaluate where conservation resources are most needed.
Findings from the model, built by a research team from the University of Idaho, University of Maryland, Radford University and The Ohio State University, were published today in the Proceedings of the National Academy of Sciences.
The International Union for Conservation of Nature’s (IUCN) Red List of Threatened Species is a powerful tool for researchers and policymakers working to limit species loss across the globe. A new approach developed at U of I and The Ohio State University uses the power of machine learning and open-access data to predict plant species that could be eligible for at-risk status on the IUCN Red List.
Adding even a single species to IUCN’s Red List demands hours of expensive, rigorous and highly specialized research. As a result, many known species have not been formally assessed by the IUCN and ranked from least concern to critically endangered; only about 5 percent of all currently known plant species appear on IUCN’s Red List in any capacity.
Continue reading at University of Idaho.
Image via Pixabay.
