Plant Science Colloquium with Prof. Dr. Alexander Zizka The public availability of biodiversity data is drastically increasing. Specifically, information on species geographic occurrence from digitized herbarium collections has huge potential for global synthesis in plant biogeography and conservation. Yet, low data precision is often preventing the effective use of this large-scale information. Here, I briefly outline major caveats of large-scale distribution data from public databases and then illustrate their potential, with two case studies: A global synthesis on the evolution of insular woodiness, and a novel approach to use deep learning to automatize Red List assessments. https://www.inres.uni-bonn.de/de/inres/veranstaltungen/plant-science-colloquium-with-prof-dr-alexander-zizka https://www.inres.uni-bonn.de/++resource++plone-logo.svg

The public availability of biodiversity data is drastically increasing. Specifically, information on species geographic occurrence from digitized herbarium collections has huge potential for global synthesis in plant biogeography and conservation. Yet, low data precision is often preventing the effective use of this large-scale information. Here, I briefly outline major caveats of large-scale distribution data from public databases and then illustrate their potential, with two case studies: A global synthesis on the evolution of insular woodiness, and a novel approach to use deep learning to automatize Red List assessments.