Abstract:

Background & Aims: Biodiversity conservation is essential for ecological security and sustainable human development. Nevertheless, the intricate interactions within ecosystems and the impact of external influences like human actions and climate change create substantial hurdles for conservation efforts. The advent of Artificial Intelligence (AI) and Large Language Models (LLMs) offers new opportunities in this field. This study aims to review how these technologies are being used. 

Methods: We discussed recent progress in using AI and LLMs for biodiversity conservation research and practice. Our focus was on AI and LLMs in knowledge synthesis and discovery, ecosystem modeling, assessment and monitoring, decision-making, and fieldwork. 

Results & Conclusion: There is great potential for AI and LLMs in biodiversity conservation research and practices. Despite the promise, challenges such as data quality, model response times, ecosystem heterogeneity, ethical considerations, and data security remain. Future research should focus on developing specialized AI models and building high-quality, multimodal biodiversity datasets to effectively address these challenges.

Key words: Artificial Intelligence, Large Language Models, Biodiversity Conservation, Knowledge Discovery, Conservation Decision-making