Data from: Assessing ChatGPT for taxonomic and floristic studies

The advancement of biological sciences has long been linked to
technological progress. ChatGPT, a generative artificial intelligence
chatbot, produces human-like conversational responses and offers potential
support for research across diverse scientific disciplines. However, its
utility in natural sciences, particularly botanical research, remains
largely unexplored. This study systematically evaluates ChatGPT’s
performance in plant identification, creation of taxonomic keys,
morphological description analysis, distribution mapping, and image-based
species recognition. Across multiple tests involving taxa from different
regions, the chatbot frequently produced inconsistent or incorrect
outputs, including misidentification of species, erroneous synonymy
assignments, fabricated references, and non-functional visualisations.
Performance was especially limited for closely related species, hybrids,
and microphotographs, while genus-level identification and text refinement
were comparatively more reliable. These findings highlight the risks of
relying on ChatGPT for botanical research, particularly for students and
early-career researchers, emphasising the necessity of critical
verification. Despite current limitations, ongoing improvements in AI
suggest that future versions may offer more consistent and accurate
support in biodiversity studies.