The Future of Artificial Intelligence in Ecosystem Modeling

2025/09/22 by Scott Spillias, Rowan Trebilco, Matthew Adams +23 · 2 voices
Environmental Science · #Ecosystem dynamics and resilience #Land Use and Ecosystem Services #Sustainability and Ecological Systems Analysis

paper · pdf · doi:10.1093/biosci/biaf169

openalex publication_date 2025/09/22 · openalex created_date 2025/11/28 · openalex updated_date 2026/07/28

Abstract

Developing ecosystem models has traditionally been limited to a small global community of experts because of the complex skills and resources required. However, the emergence of user-friendly artificial intelligence (AI) tools with powerful generative capabilities could democratize ecosystem modeling, enabling both experts and nonspecialists to build models. We explore a speculative future where AI enables automated end-to-end model development and application. Although such tools could accelerate and enhance modeling tasks, their widespread adoption raises concerns about data integrity, bias, interpretation reliability, and the potential erosion of human expertise. We argue that regardless of AI's technical advancement, human engagement and control remain essential. The global community must respond by identifying key factors that distinguish desirable outcomes and developing infrastructure, standards, and ethical guidelines to ensure AI use in ecosystem modeling remains scientifically robust while supporting sustainable and equitable outcomes.

Citations

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Discussions

• Some interesting points from the article: doi.org/10.1093/bios... - AI could help identify appropriate model complexity. Interesting, given this gets pretty philosophical - AI could help researchers [bsky, 2 points, 0 comments]
• In #BioScience, authors explore a speculative future where #AI enables automated end-to-end model development and application. #aibs doi.org/10.1093/bios... [bsky, 0 points, 0 comments]

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