Temporal Dimensions of Data Quality in Bird Atlases: the Case of the Second Southern African Bird Atlas Project

Abstract

Halting biodiversity loss on land (Sustainable Development Goal [SDG] 15) is an unfolding problem, and as such, requires novel solutions. Citizen science (CS) promises large quantities of data, but introduces the challenge of ensuring these are valuable to conservation research and can inform meaningful action. This paper contributes to this endeavour, examining the impact of systematic as opposed to unstructured fieldwork on the biodiversity monitoring value of data from the Second Southern African Bird Atlas Project (SABAP2). SABAP2 “atlasers” work within a fine-scale grid system to generate avian species checklists that are comprehensive at the time of fieldwork. Though valuable, unstructured fieldwork efforts paint an incomplete picture; effective conservation action requires monitoring—keeping a finger on the pulse of local biodiversity through consistent and systematic data collection. Systematic collection allows for the detection of nuanced biological patterns such as seasonal population trends and movements, rapidly alerting scientists to anomalies and galvanizing swift response. It is, however, a demanding protocol, and implementation requires careful consideration of participant impact and motivations. Here, we used a newly developed approach for measuring temporal data quality to examine the systematic atlasing efforts of a CS community in the Hessequa Atlasing Area, South Africa, assessing the biodiversity monitoring value of structured data collection versus opportunistic checklists. We found that structured data collection increased the temporal resolution of atlas data, and thus its monitoring quality. We discuss challenges in maintaining achievable fieldwork goals for participants, and examine Hessequa’s project structure and participant motivations to provide recommendations for future project management.