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AI-driven knowledge synthesis for food web parameterisation
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DOI：10.1016/j.envsoft.2026.106865.png)
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Abstract
En 中文
• LLM-based framework automates species grouping and diet matrix creation with >99.7% consistency. • 51%–59% of trophic interactions show high stability (stability score > 0.7) across iterations. • In expert comparison, SPELL achieved 81.6% agreement and 80% of diet differences <0.2. • LLM-driven synthesis integrates global databases with unstructured local knowledge. • Reduces ecosystem model development time from months to hours.
Keywords:
Artificial intelligence
Ecological modelling
Ecopath with ecosim
Diet interaction
Large language models
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