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Species Distribution Essential Biodiversity Variables (SD EBVs;  Pereira et al. 2013 ,  Kissling et al. 2017 ,  Jetz et al. 2019 ) are defined as measurements or estimates of species’ occupancy along the axes of space, time and taxonomy. In the “ideal” case, additional stipulations have been proposed: occupancy should be characterized contiguously along each axis at grain sizes relevant to policy and process (i.e., fine scale); and the SD EBV should be global in extent, or at least span the entirety of the focal taxa’s geographical range ( Jetz et al. 2019 ). These stipulations set the bar very high and, unsurprisingly, most operational SD EBVs fall short of these ideal criteria. In this presentation, I will discuss the major challenges associated with developing the idealized SD EBV. I will demonstrate these challenges using an operational SD EBV spanning ~6000 species in the United Kingdom (UK) over the period 1970 to 2019 as a case study ( Outhwaite et al. 2019 ). In short, this data product comprises annual estimates of occupancy for each species in all sampled 1 km cells across the UK; these are derived from opportunistically-collected species occurrence data using occupancy-detection models ( Kéry et al. 2010 ). Having discussed which of the “ideal” criteria the case study satisfies, I will then touch on what are, in my view, two underappreciated challenges when constructing SD EBVs: dealing with sampling biases in the underlying data and the difficulty in evaluating the extent to which they bias the final product. These challenges should be addressed as a matter of urgency, as SD EBVs are increasingly applied in important settings such as underpinning national and international biodiversity indicators (see e.g.,  https://geobon.org/ebvs/indicators/ ).

Practical Considerations for Implementing Species Distribution Essential Biodiversity Variables