2025
ACL
ACL 2025
Scaling Species Diversity Analysis in Carbon Credit Projects with Large-Context LLMs
Abstract
AbstractReforestation and revegetation projects can help mitigate climate change because plant growth removes CO2 from the air. However, the use of non-native species and monocultures in these projects may negatively affect biodiversity. Here, we describe a data pipeline to extract information about species that are planted or managed in over 1,000 afforestation/reforestation/revegetation and improved forest management projects, based on detailed project documentation. The pipeline leverages a large-context LLM and results in a macro-averaged recall of 79% and a macro-averaged precision of 89% across all projects and species.
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Keyword Pioneer
— species diversity
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio