Toward a New Paradigm of Human-AI Collaborative Ecological Knowledge Production: An Interdisciplinary Methodological Perspective on Mapping Grassland Vegetation Formations on the Qinghai-Tibetan Plateau

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This research aims to explore the shifts in ecological knowledge production mechanisms when integrating artificial intelligence in the study of grassland vegetation formations.
Utilized long-term field survey data, multi-source remote sensing data, and environmental variables.
Implemented artificial intelligence models for vegetation formation recognition at both sample and regional scales.
Analyzed through interdisciplinary research theory, Mode 2 knowledge production theory, and fourth paradigm theory.
Identified changes in the grassland vegetation structure of the Qinghai-Tibetan plateau over the last 40 years.
Revealed a shift from discipline-driven to problem-oriented knowledge production.
Illustrated the integration of ecological knowledge into AI processes during various analytical phases.

Interdisciplinary research reveals ecological knowledge production changes with AI in grassland mapping, suggesting new collaborative frameworks.

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GU et al. (2026) studied this question.

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