Beyond Equations: Large Language Models as a New Frontier for Resilient Ecosystem Modelling

Abstract

Large language models (LLMs) offer a complementary interface to traditional ecological modelling, particularly in addressing the challenges of unstructured data integration, stakeholder communication and early warning signal detection. Rather than replacing mechanistic or statistical approaches, LLMs function as semantic assistants—extracting, organising and translating ecological knowledge across diverse textual sources. This letter reframes the role of LLMs from paradigm disruptors to epistemic extenders, emphasising their utility in pre-model discovery, mid-model augmentation and post-model communication. We contrast LLMs with conventional models along dimensions such as causality, transparency, and data interoperability and argue for a hybrid modelling paradigm that combines mechanistic rigour with language-driven flexibility. Ethical considerations—particularly related to hallucination, traceability, and digital infrastructure equity—are also addressed. We call for a cautious yet proactive integration of LLMs into ecosystem resilience research to improve inclusivity, agility and contextual awareness in ecological decision-making.