Assigning occurrence data to cryptic taxa improves climatic niche assessments: biodecrypt, a new tool tested on European butterflies

Leonardo Dapporto, Platania Leonardo, Mattia Menchetti, Cecília Corbella, Isaac Kay-Lavelle, Roger Vila, Martin Wiemers & Oliver Schweiger
Aim Occurrence data are fundamental to macroecology, but accuracy is often compromised when multiple units are lumped together (e.g. in recently separated cryptic species or citizen science records). Using amalgamated data leads to inaccuracy in species mapping, to biased beta-diversity assessments and to potentially erroneously predicted responses to climate change. We provide a set of R functions (biodecrypt) to objectively attribute undetermined occurrences to the most probable taxon based on a subset of identified records....
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