Distribution and Sampling Biases of Citizen Science Observations Uploaded to iNaturalist from Hungary

The amount of biodiversity data collected in citizen science projects is increasing, yet we often know little about sampling biases in the data. We examined such biases in the temporal and spatial distribution of observation records uploaded to the iNaturalist platform from Hungary. We found that the number of records has grown rapidly recently in the past ten years. We explored temporal patterns and found that records peaked in early summer, on weekend days, and at mid-day. Engagement varied across participants: The majority of records were uploaded by a few enthusiastic observers, while most users uploaded less than 10 records. Records of insects, plants, and vertebrates were more likely to be uploaded than other groups, and vertebrates had more complete species coverage than others. Both landscape and socioeconomic factors explained the spatial variation in the records: For instance, similar to other countries, there were more records submitted and records of more diverse taxa in places that were closer to urban areas, closer to protected areas, had greater land use diversity, and were at higher altitude. Species recording, using tools like iNaturalist, can fill taxonomic gaps in knowledge in countries like Hungary that lack large citizen science communities, especially for less popular invertebrate taxa. However, the presence of sampling biases demonstrates the need to better design biodiversity mapping projects to fill spatial gaps in coverage and so inform conservation decision-making.