Open-source databases provide new insights
A team of researchers led by Dr. Anahí Espíndola collected geographical, environmental and morphological information of those plant species where conservation status is known. The data, collected from open-source databases, was used to training a machine learning model. Based on this model, the research team was able to make predictions on the conservation status of over 150.000 land plant species worldwide.
The model predicts the probability a species does not fall under the IUCN Red List Least Concerned (LC) category, meaning the species is to some extent at risk. What would normally be a very costly and time-consuming process, this method provided new insights on the conservation status of plant species of which 95% cannot be found on the Red List.
The categorization of species’ conservation status by the IUCN Red list.