Arhonditsis, GeorgeBlanco Vaca, Juan AntonioWang, Hsiao-HsuanNeuman, AlexeyArnillas, Carlos A.Fath, Brian D.2025-07-152025-07-01Arhonditsis, G., Blanco, J. A., Wang, H. H., Neuman, A., Arnillas, C. A., Fath, B. D. (2025). Editorial: Ecological models for tomorrow's solutions. Ecological Modelling: International Journal of Ecological Modelling and Engineering and Sustems Ecology, 506, 1-4. https://doi.org/10.1016/j.ecolmodel.2025.111158.0304-380010.1016/j.ecolmodel.2025.111158https://academica-e.unavarra.es/handle/2454/54405A robust environmental policy analysis typically relies upon the following pillars: (i) defensible identification of the critical drivers of degradation, (ii) elucidation of the sources of controversy, and (iii) development of necessary tools to anticipate the unexpected. While management problems are rarely (if ever) solved completely and certain facets of environmental/ecological systems evolve over time (Davies et al., 2024), the core issues remain the same. It is thus critical to establish knowledge frameworks that ensure both continuity in the decision-making process but also iterative adjustments to accommodate the ubiquitous uncertainty surrounding the study of open ecosystems.application/pdfeng©2025 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0Adaptive managementEnvironmental modellingUncertaintyEcological policyinfo:eu-repo/semantics/other2025-07-15info:eu-repo/semantics/embargoedAccess