Abstract

India, as one of the world’s megadiverse countries, faces significant challenges in documenting and conserving its rich biodiversity due to habitat loss, climate change, and resource limitations. Traditional taxonomic methods, while foundational, are often timeconsuming and inaccessible, necessitating innovative solutions to accelerate biodiversity research. This review explores the transformative role of cybertaxonomy and artificial intelligence (AI) in advancing biodiversity documentation and conservation in India. Cybertaxonomy leverages digital databases, molecular tools like DNA barcoding, and advanced imaging techniques to modernize species classification and data sharing. AI complements these efforts through machine learning algorithms for species identification, predictive modeling for habitat mapping, and real-time monitoring using satellite data. Applications such as digitization initiatives by the Botanical Survey of India (BSI) and Zoological Survey of India (ZSI), AI-driven platforms like iNaturalist, and deep learning for invasive species detection highlight the potential of these technologies. However, challenges such as data standardization, limited expertise, and ethical concerns must be addressed through collaborative efforts, policy frameworks, and capacity-building programs. By strengthening public-private partnerships, integrating citizen science, and investing in AI and cybertaxonomy training, India can enhance its biodiversity research capabilities and address critical conservation challenges. This review underscores the importance of continued innovation and collaboration to preserve India’s natural heritage and contribute to global biodiversity goals.

Keywords

biodiversity conservation, citizen science, data standardization, deep learning, DNA barcoding, forest monitoring; invasive species, machine learning, species distribution modelling, virtual herbariums, wildlife monitoring