Societal Impact Statement
The current rate of global biodiversity loss creates a pressing need to increase efficiency and throughput of extinction risk assessments in plants. We must assess as many plant species as possible, working with imperfect knowledge, to address the habitat loss and extinction threats of the Anthropocene. Using the biodiversity database, Botanical Information and Ecology Network (BIEN), and the Andropogoneae grass tribe as a case study, we demonstrate that large‐scale, preliminary conservation assessments can play a fundamental role in accelerating plant conservation pipelines and setting priorities for more in‐depth investigations.
Summary
The International Union for the Conservation of Nature (IUCN) Red List criteria are widely used to determine extinction risks of plant and animal life. Here, we used The Red List's criterion B, Geographic Range Size, to provide preliminary conservation assessments of the members of a large tribe of grasses, the Andropogoneae, with ~1100 species, including maize, sorghum, and sugarcane and their wild relatives.
We used georeferenced occurrence data from the Botanical Information and Ecology Network (BIEN) and automated individual species assessments using ConR to demonstrate efficacy and accuracy in using time‐saving tools for conservation research. We validated our results with those from the IUCN‐recommended assessment tool, GeoCAT.
We discovered a remarkably large gap in digitized information, with slightly more than 50% of the Andropogoneae lacking sufficient information for assessment. ConR and GeoCAT largely agree on which taxa are of least concern (>90%) or possibly threatened (<10%), highlighting that automating assessments with ConR is a viable strategy for preliminary conservation assessments of large plant groups. Results for crop wild relatives are similar to those for the entire dataset.
Increasing digitization and collection needs to be a high priority. Available rapid assessment tools can then be used to identify species that warrant more comprehensive investigation.