process () and resulting population estimates can be imprecise because of the observation process (). Understanding factors leading to observation bias may help improve population estimates from these datasets. The Southern African Bird Atlas Project (SABAP) is probably Africa’s largest citizen science biodiversity data collection project (), focusing on distribution and relative abundance of birds in up to six countries of southern Africa. Resulting publications have provided a substantive basis for detailed conservation planning, policy development and management in the region (). Thus far two studies, which have examined how the index of abundance from this atlas (reporting rates) reflects local population abundance, have found that reporting rates were correlated with abundance (, ). Our study aims to explore correlates of detection for a set of birds from the Cape floristic region (Fynbos) in South Africa. The Fynbos is a hotspot renowned for its botanical diversity, and is home to six endemic passerines and one endemic turnicid (). Generally it is considered to have low bird biodiversity (), but the endemic species are of conservation concern especially due to threats resulting from alien vegetation encroachment, landscape conversion and climate change (, ). While many of these species live in hard to access mountain locations, the region has been well covered by atlasing efforts. Through a standardized distance sampling survey undertaken across the region, we have the unique opportunity to compare atlas reporting rates to bird densities accounting for correlates of detection. In the paper we aim to identify how species’ characteristics and behaviour influence detection rate in a point count survey. We hypothesize that larger, colourful, vocal species more tolerant of human presence and habitat modification will be those reported most frequently. Likewise, more common species, i.e. those occurring at higher densities, should be reported more frequently. We then examine how the citizen science atlas reporting rates correlate with density estimates calculated from the same survey area and use what we have learnt to create a model that allows prediction of bird density and population size from SABAP2 data.
process () and resulting population estimates can be imprecise because of the observation process (). Understanding factors leading to observation bias may help improve population estimates from these datasets. The Southern African Bird Atlas Project (SABAP) is probably Africa’s largest citizen science biodiversity data collection project (), focusing on distribution and relative abundance of birds in up to six countries of southern Africa. Resulting publications have provided a substantive basis for detailed conservation planning, policy development and management in the region (). Thus far two studies, which have examined how the index of abundance from this atlas (reporting rates) reflects local population abundance, have found that reporting rates were correlated with abundance (, ). Our study aims to explore correlates of detection for a set of birds from the Cape floristic region (Fynbos) in South Africa. The Fynbos is a hotspot renowned for its botanical diversity, and is home to six endemic passerines and one endemic turnicid (). Generally it is considered to have low bird biodiversity (), but the endemic species are of conservation concern especially due to threats resulting from alien vegetation encroachment, landscape conversion and climate change (, ). While many of these species live in hard to access mountain locations, the region has been well covered by atlasing efforts. Through a standardized distance sampling survey undertaken across the region, we have the unique opportunity to compare atlas reporting rates to bird densities accounting for correlates of detection. In the paper we aim to identify how species’ characteristics and behaviour influence detection rate in a point count survey. We hypothesize that larger, colourful, vocal species more tolerant of human presence and habitat modification will be those reported most frequently. Likewise, more common species, i.e. those occurring at higher densities, should be reported more frequently. We then examine how the citizen science atlas reporting rates correlate with density estimates calculated from the same survey area and use what we have learnt to create a model that allows prediction of bird density and population size from SABAP2 data.