Stephenson, Nile; Pettorelli, Nathalie; Early, Regan; (2025) Occupancy of Urban Habitats by the Jersey Tiger Moth Is Revealed by Social Media Data but Not Traditional Monitoring. Ecology and Evolution , 15 (3) , Article e71086. 10.1002/ece3.71086.

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Abstract

As the world's climate changes, species are undergoing range shifts. Range shifts are generally documented using databases such as the Global Biodiversity Information Facility (GBIF), which largely contain data from monitoring schemes and wildlife surveys. Such databases have two major limitations: (i) data may be spatially biased because traditionally surveyed areas are in rural habitats and (ii) there is a time lag between formal monitoring and survey data collection and assimilation into GBIF, which means rapid range shifts cannot be tracked. Alternative data sources, such as social media, could provide information on species distributions and range shifts that compensate for spatial biases in GBIF records because social media data may be collected outside traditionally surveyed areas. Such data are also usually shared online immediately after a wildlife sighting. The complementarity of GBIF and social media data, however, has rarely been assessed, particularly when tracking range shifts. Despite their potential utility, social media data may be particularly prone to temporary trends or geographic variation in behaviour that are not understood. We lack tools with which to counter these biases. To address these knowledge gaps, we compare the habitat usage revealed by biological records of the Jersey tiger moth from GBIF and from social media data sources (Instagram and Flickr). We develop a novel method to investigate recorder bias in social media data and compare between data sources. We find that biological records from Instagram reveal greater than expected occurrence in urban environments. Recorder effort differs notably between data sources and Instagram complements GBIF by recording species in areas unaccounted for by GBIF. By incorporating recorder effort metrics, data from social media sources could be used to improve monitoring of range-shifting species in urban spaces.

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