Selective observation causes differences in citizen science butterfly data

作者：Jan Christian Habel, Thomas Schmitt, Peter Huemer, Johannes Rüdisser, Patrick Gros, Werner Ulrich · 发表于：Basic and Applied Ecology · 年份：2025 · DOI：10.1016/j.baae.2025.06.003 · 被引用次数：3 · 研究领域：Species Distribution and Climate Change、Ecology and Vegetation Dynamics Studies、Plant and animal studies

ABSTRACT In times of insect decline, the need for biodiversity monitoring data has become increasingly urgent. However, standardised monitoring of biodiversity is time-consuming and cost-intensive. Citizen science (CS) initiatives therefore may provide valuable data and may complement data collected by professionals. Photo-apps equipped with automated taxonomic identification based on artificial intelligence play a central role in CS, at least for well distinguishable organisms such as the majority of butterfly species. In this study, we analysed butterfly (Papilionoidea) observations collected with three different photo-apps (i.e. Blühendes Österreich, iNaturalist, observation.org ). We compared these data with observations from the Global Biodiversity Information Facility (GBIF). For this purpose, we classified each butterfly species according to its detectability and attractiveness, as well as its ecology and behaviour. Our results show that the observations obtained from the three photo-apps mainly cover mobile, conspicuous and easy-to-identify species, while the rare and sedentary specialist species and species that are difficult to distinguish from other taxa are underrepresented. Our findings show that the observations collected differ significantly between the three apps, and Blühendes Österreich particularly lacks inconspicuous butterfly species. However, a detailed regional analysis of user performance revealed that the differences among the three apps largely stem ...