Ecological research increasingly relies on the integration of heterogeneous knowledge sources, including field observations, experimental results, theoretical models, and socio-economic data. However, relevant knowledge remains highly fragmented across disciplines, conceptual frameworks, and data infrastructures, which limits the capacity for ecological synthesis. Recent advances in large language models, semantic knowledge graphs, and agent-based AI systems make it technically feasible to formalize and computationally integrate ecological and social-ecological knowledge. Yet the conceptual, methodological, and epistemological foundations required for such integration remain largely unresolved. Without addressing these issues, AI-based synthesis risks producing scientifically unreliable or non-interpretable results. Initial progress on these issues has emerged from recent interdisciplinary collaborations, including a research group[1] at the Center for Interdisciplinary Research (ZiF) in Bielefeld, which brought together scholars from ecology, computer science, and philosophy of science, among them the organizers of this workshop. This work has identified key open questions:
· What methodological limits and validation requirements arise when using AI-based approaches for ecological synthesis?
· Which conceptual and semantic frameworks are suitable for representing ecological and social-ecological knowledge in computational systems?
· How can ecological and social science knowledge be integrated in interoperable data and knowledge models?
· What epistemic standards are required to ensure transparency, interpretability, and scientific reliability in interdisciplinary knowledge integration?
Addressing these questions requires sustained dialogue between fields that rarely interact directly, including ecology, artificial intelligence, philosophy of science, and the social sciences. Existing disciplinary conferences rarely provide formats that allow such focused conceptual exchange. The workshop will therefore bring together an international group of researchers and structure an emerging research field on integrative social-ecological knowledge systems.
The primary scientific objectives are:
· clarifying conceptual and epistemological foundations for social-ecological knowledge integration;
· evaluating emerging computational approaches, including LLM-based and agentic AI systems;
· identifying methodological and epistemological challenges in interdisciplinary ecological research;
· developing priorities for future international research in integrative social-ecological knowledge systems.