Spatial Uncertainty in Plant Records: Implications for Research and Conservation

Aim Species occurrence data are fundamental to ecological research and biodiversity conservation, with primary inputs derived from natural history collections and their associated digital repositories. The reliability of such data is strongly dependent on spatial accuracy. Although the rapid digitisation of herbarium specimens and the expansion of citizen science platforms such as iNaturalist have substantially increased data availability, concerns regarding geographic precision persist. Location Global, however we particularly focus on a threatened endemic tree species ( Humboldtia bourdillonii ) from the Western Ghats biodiversity hotspot, India as a case study. Methods We examined occurrence records derived from natural history collections and online biodiversity repositories, including digitised herbarium records and citizen science platforms. Records were evaluated for geographic precision and potential spatial errors associated with imprecise georeferencing, incorrect or ambiguous localities and coordinate obscuration. We assessed how these inaccuracies could affect the interpretation of species distributions and conservation status. Results Errors arising from imprecise georeferencing, mislabelled localities, and deliberate coordinate obscuration can significantly bias biodiversity analyses, species distribution modelling and extinction risk evaluations. Using the narrowly endemic and highly threatened tree species Humboldtia bourdillonii from the Western Ghats biodiversity hotspot as a case study, we illustrate how spatial inaccuracies in databases can impact conservation assessments. Main Conclusions For geographically restricted and threatened plants, occurrence data quality may be more important than data quantity. The rapid expansion of digitised collections and citizen science observations provides valuable opportunities for biodiversity research, but increased availability does not necessarily ensure increased reliability. Expert taxonomic and geographic validation, rigorous data cleaning and field‐based verification should therefore be integral components of occurrence‐data workflows and conservation assessments.