Assessment of Urban Bias in Iberian Butterfly Sampling through Citizen Science Data

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint. You must log in to post a comment. There are no comments or no comments have been made public for this article. This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint. Add a Comment You must log in to post a comment. Comments There are no comments or no comments have been made public for this article. Citizen science platforms have revolutionized biodiversity monitoring by enabling large-scale data collection. However, concerns about potential biases, such as urban sampling bias, have raised questions about the quality and representativeness of these datasets. This study assesses the spatial distribution of butterfly observations collected through the citizen science platform Biodiversidad Virtual in the Iberian-Balearic region over a 23-year period (2000–2023). Butterfly records were classified into three ecosystem types—urban areas, grasslands, and forests—and three population density zones—urban, peri-urban, and rural areas—using land cover and population density maps. Temporal trends in observation growth and minimum distances of records to urban and rural areas were analyzed. The results show consistent growth in butterfly observations across all ecosystem types, with rural and natural areas contributing significantly more records than urban areas. Observations in grasslands exhibited the highest growth rate, followed by forests and urban areas. The analysis of distances revealed preference for recording biodiversity in natural areas, with records consistently closer to rural areas than urban centers. These findings challenge the perceived dominance of urban bias in citizen science datasets and highlight the capability of citizen science platforms to capture data from diverse ecosystems. This study shows that, for one of the most important georeferenced datasets on butterflies of the Iberian Peninsula, urban biases are minimal, and geographic representation is robust. Further research is recommended to examine cultural and regional factors in other databases, enhancing their application in ecological research and conservation planning. https://doi.org/10.32942/X2392D Entomology, Life Sciences, Research Methods in Life Sciences, Terrestrial and Aquatic Ecology Biodiversity Monitoring, Sampling bias, Land cover classification, Lepidoptera, Habitat distribution, spatial analysis, Conservation data quality, sampling bias, Land Cover Classification, lepidoptera, Habitat distribution, spatial analysis, Conservation data quality Published: 2025-01-24 12:09 Last Updated: 2025-01-24 17:09 CC-By Attribution-NonCommercial-NoDerivatives 4.0 International Language: English