1.Predictions on species richness and incidence of species are made using data for three scales of mapping from the Greater Manchester butterfly atlas; for the whole of the conurbation (2 km×2 km scale) and for two sample areas centred on the Mersey Valley (1 km×1 km scale; 1 ha scale). Predictions are based on data for recording effort, altitude, biotopes, host-plants and nectar resources.
2.Data for Greater Manchester indicate that substantial shortfalls may occur in recording butterfly species for atlases despite the fact that butterflies are generally easily identified and well supported with recorders. Shortfalls tend to be larger for species with fewer records, indicating that some species may be more easily overlooked than others.
3.The results demonstrate that targeting squares for re-survey is necessary and feasible. The predictions have other valuable research applications, the most important of which is being able to assess the accuracy of distribution maps, to correct them, and to make projections of distribution changes.
4.Predictions may be enhanced by improvements to mapping in three ways: (i) Collecting data on recording effort. Variation in recording effort typically accounts for differences in species richness and incidence of species more than any other variable; (ii) Collecting data on biotopes and specific resources. The present results are promising and demonstrate that the collection of environmental data linked to a suitable sampling frame could facilitate knowledge of the distribution of species over extensive areas that remain under-recorded; and (iii) Distinguishing between breeding individuals and vagrants. Vagrancy is a problem associated both with species and scale. Although species vary substantially in their capacity to migrate beyond their habitats, the effect of vagrancy on distribution maps becomes an increasingly large problem as the grain of mapping (size of recording units) decreases. It is suggested that over-recording can be a problem, particularly when mapping is fine-grained.