Reporting rate is the most commonly used abundance measure derived from SABAP2 data and reflects how many times a species appears per pentad; or set of pentads. Intuitively, species with high reporting rates should be more abundant, i.e. have a higher density, measured as the number of individuals per unit area. But reporting rate might also be influenced by differences in the ease with which species are detected. Factors that might affect detection rate in addition to abundance include bird size, sentinel and vocal behaviour, as well as the habitat in which a species occurs.
For example, density estimates of Cape Rockjumper are between 1–5 individuals per km2 across their range, Cape White-eye occur at a density of 40–50 individuals/km2 in Fynbos (Lee & Barnard 2017, Ostrich 88: 9-17), while Lark-like Bunting occurs at a density of 20-500 individuals/km2 (Lee et al. 2018, Ostrich 89: 363-372). By comparison, SABAP2 reporting rates are 5–15% for Cape Rockjumper, 50–60% for Cape White-eyes and 15-25% Lark-like Buntings. Larger, louder birds also tend to have higher reporting rates compared to their densities: Karoo Korhaan for instance has a reporting rate of 35–40%, despite occurring at a density of 1–2/km2. So, while reporting rates broadly reflect densities, these relationships are confounded by habitat, size and life-history traits. This means we can’t just compare reporting rates between species to say one species is more common. But what about within one species range? Does higher reporting rate in some locations mean the species is more common there?
Recently I explored the relationship between density and reporting rate in pentads for several species in the southern Karoo region. Our team calculated pentad specific density estimates for 49 species and compared these to reporting rates, finding a good match for 75% of these. That means for a given species, as a general rule higher reporting rate generally means the species is more common.
But what about the exceptions to the rule? The species for which there was no clear link between reporting rate and abundance were generally the most common species. This is because they have high reporting rates, and reporting rate has an upper threshold of 100%. However, density estimates have no upper limit: for Cape Sparrow a reporting rate of 100% can mean a density estimate of 2, 10 or 50. The only way to get around this is to have many, many, cards for a set of pentads (a hundred or more), where the required detail when then become apparent. A repercussion of this is that for common species with high reporting rates we may not be able to detect declines using SABAP2 data. Generally, though, the implications for this are we can have greater confidence in the information derived from the SABAP2 in terms of what reporting rates are telling us for a species. For instance, consistent declines in reporting rate over time are likely due to local declines in density: as long as we are consistent in our atlassing efforts.
With SABAP2 rolling forward, it also means that nearly all information required to make decisions regarding a species conservation status using IUCN criteria can now be acquired from SABAP2 data: range sizes and population trends (Lee et al. 2017, Bird Conservation International 27:323-336), and for some species, population sizes (de Kock and Lee 2019, African Zoology). That is a great achievement, which anyone who has ever submitted a list to SABAP2 can be proud of, although there are certainly species for which field work will be required: Hottentot Buttonquail being a case in point. May the atlassing efforts continue long into the Future.