Avifauna richness and detection reliability between structured scientific surveys and citizen science data

Citizen science has emerged as a cost-effective complement to structured biodiversity surveys, yet its reliability for small-scale avian monitoring in Africa remains underexplored. This study compared avifaunal species richness, detection accuracy, and the influence of species traits on detectability between full-protocol African BirdMap data (citizen science) and structured surveys conducted within the Cape Coast Metropolitan Area, Ghana. Structured surveys recorded 208 species, while citizen science reported 215, with 176 species (71.3%) shared. A total of 32 and 39 species were unique to the structured survey and citizen science data, respectively. Structured surveys showed higher data accuracy and a narrower confidence interval (99.5%, CI: 0.97–0.99) than citizen science (96.4%, CI: 0.93–0.98). Generalized linear modeling also showed that species detectability was influenced primarily by traits rather than survey method. High vocalization and moderate plumage conspicuousness increased detection likelihood, whereas rarely vocal species were significantly underdetected. Once traits were accounted for, method type was not a significant predictor of detectability (p = 0.85). These findings indicate that well-standardized citizen science protocols can yield avian richness and detectability estimates comparable to structured surveys, though expert-led verification remains vital to minimize misidentification and maintain data quality. The results support integrating citizen science into local avifaunal monitoring, particularly in resource-limited contexts.