Predicting changes in the abundance of African wetland birds by incorporating abundance–occupancy relationships into habitat association models

Aim To map changes in the abundance of African wetland birds using remotely derived habitat data. We show that abundance–occupancy relationships can be coupled with habitat association models to map changes in abundance. As conservation resources are more easily allocated when spatial and temporal patterns of abundance are known, our method provides guidance for conservation planning. Location Papyrus, Cyperus papyrus, swamps in east central Africa. Methods Presence/absence surveys of six bird species in 93 wetlands were used to construct models predicting probability of occurrence from habitat characteristics. Densities were then determined from surveys in 23 additional wetlands and modelled as functions of occurrence probability. We then used satellite imagery to derive habitat characteristics remotely in two time periods (1984–87 and 2000–03) and used the modelled relationships between (1) habitat and occupancy and (2) occupancy and density, to infer changes in abundance in all c. 30,000 wetlands within the study area. Results Wetlands within the region declined by 8.6% between the two time periods, but by > 75% in regions of high human population density. Bird densities were also highest in these regions, which comprised wetlands subject to high levels of disturbance. The geographical coincidence of high densities and habitat loss and the existence of positive associations between bird density and occurrence meant that birds declined by much more than the average rate of their habitat. Main conclusions Targeting conservation efforts in areas with high drainage would protect a high proportion of the bird populations. Encouraging people to derive income from disturbance to which the birds are tolerant, rather than drainage, is likely to be an effective strategy. Because habitat characteristics are a key driver of abundance–occupancy relationships, we conclude that there is wide‐scale scope to couple abundance–occupancy relationships with remote habitat mapping to efficiently inform conservation planning.