Interpreting Bird Atlas Data Using Logistic Models: An Example From Lesotho, Southern Africa

Presence-absence maps of the occurrence of species may be difficult to interpret because of uneven coverage in field surveys. 2. Using data collected in the mountain Kingdom of Lesotho, southern Africa, where even coverage was virtually impossible to achieve, a method is presented to improve bird atlas maps by plotting predicted probabilities of occurrence calculated from logistic models. 3. A set of habitat variables derived from maps was reduced to principal components and then used in logistic models to predict the occurrence of bird species across the country. The models generate a probability of occurrence for all survey squares irrespective of coverage. Maps for the Cape vulture Gyps coprotheres (Forster), ground woodpecker Geocolaptes olivaceus (Gmelin) and pied crow Corvus albus Muller are presented as examples. 4. The models were assessed by jack-knife analysis and correctly predicted presence and absence in the field data. 5. Relationships between the predicted probabilities, recording frequency (reporting rate) and density are discussed.