Understanding patterns of biodiversity is crucial for developing
appropriate conservation and management plans. The IUCN RedList is
looked upon as a source of globally-consistent assessment of species
extinction risk, including range maps as part of the extinction risk
assessment. Species ranges are a central criterion in determining
extinction vulnerability, and consequently apportioning conservation and
research efforts. Thus, the accuracy of these maps is crucial to the
effective conservation of global biodiversity. Given difficulties in
acquiring sufficient, reliable point data and the need for species or
diversity maps within many studies, countless papers rely on these
centralized expert range maps. However, such efforts are vulnerable to
errors if not carefully checked, and the drive to assess as many species
as possible rather than to ensure meaningful quality assessment may
drive high error rates, with huge implications for species conservation.
Recent efforts to account for the over-generalization of species ranges
by trimming species ranges with landcover and elevation also makes a
number of assumptions on the consistency and accuracy of global data,
the lack of politically-driven biases. Here, we analyse the biases
present in 50768 animal IUCN and BirdLife maps and provide suggestions
on how such analyses could be improved, and flag spatial and taxonomic
inconsistencies to enable analysis to acknowledge the limitations of
data in further analysis based on these maps. We also discuss effective
ways to overcome these biases, the limits of such applications and
explore alternative means of mapping diversity patterns.