Filling in the gaps

Species distributions are often poorly known and derived from spatially biased occurrence records. This lack of information is termed the Wallacean Shortfall. Two sources of error in our knowledge of species distributions are false absences (omission errors) and false presences (commission errors) . This uncertainty limits our process-based understanding of species distributions and is an obstacle to assessing the current status of species distributions, monitoring temporal trends and designing reserve networks. Here we employ a method which allows species occurrence records to be modelled at the spatial grain at which they were collected (Beale et al. 2014). Instead of coarsening fine-grain records, the relationship between recording intensity and detection probability is modelled to account for the spatial variation in recording intensity that is inherent in opportunistic data. We apply this method to the Brindled Green moth, a species whose distribution is widespread but under-recorded in the British Isles, with many gaps in the known distribution at grains <100km2 grain.