TY - GEN A1 - Wang, Hsiao-Hsuan A1 - Van Voorn, George A1 - Grant, William E. A1 - Zare, Fateme A1 - Giupponi, Carlo A1 - Steinmann, Patrick A1 - Müller, Birgit A1 - Elsawah, Sondoss A1 - Van Delden, Hedwig A1 - Athanasiadis, Ioannis N. A1 - Sun, Zhanli A1 - Jager, Wander A1 - Little, John C. A1 - Jakeman, Anthony J. T1 - Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation T2 - Socio-Environmental Systems Modelling N2 - Models of socio-environmental or social-ecological systems (SES) commonly address problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders. In SES modelling multiple interactions occur on different scales among various phenomena. These scale phenomena include the technical, such as system variables, process detail, inputs and outputs, which most often require spatial, temporal, thematic and organisational choices. From a good practice and project efficiency perspective, the problem scoping and conceptual model formulation phase of modelling is the one to address well from the outset. During this phase, intense and substantive discussions should arise regarding appropriate scales at which to represent the different phenomena. Although the details of these discussions influence the path of model development, they are seldom documented and as a result often forgotten. We draw upon personal experience with existing protocols and communications in recent literature to propose preliminary guidelines for documenting these early discussions about the scale(s) of the studied phenomena. Our guidelines aim to aid modelling group members in building and capturing the richness of their rationale for scoping and scale decisions. The resulting transcripts are intended to promote transparency of modelling decisions and provide essential support for the justification of the final model for its intended use. They also facilitate adaptive modifications of the pathway of model development via retracing decisions and iterative reflection upon alternative scale options. Y1 - 2023 U6 - https://doi.org/10.18174/sesmo.18563 SN - 2663-3027 VL - 5 PB - Wageningen University and Research ER - TY - GEN A1 - Nóia-Júnior, Rogério de S. A1 - Ruane, Alex C. A1 - Athanasiadis, Ioannis N. A1 - Ewert, Frank A1 - Harrison, Matthew Tom A1 - Jägermeyr, Jonas A1 - Martre, Pierre A1 - Müller, Christoph A1 - Palosuo, Taru A1 - Salmerón, Montserrat A1 - Webber, Heidi A1 - Maccarthy, Dilys Sefakor A1 - Asseng, Senthold T1 - Crop models for future food systems T2 - One earth N2 - Global food systems face intensifying pressure from climate change, resource scarcity, and rising demand, making their transformation toward resilience and sustainability urgent. Process-based crop growth models (CMs) are critical for understanding cropping system dynamics and supporting decisions from crop breeding to adaptive management across diverse environments. Yet, current CMs struggle to capture extreme events, novel production systems, and rapidly evolving data streams, limiting their ability to inform robust and timely decisions. Here, we outline CM structure, identify key knowledge gaps, and propose six priorities for next-generation CMs: (1) expand applications to extremes and to diverse systems; (2) support climate-resilient breeding; (3) integrate with machine learning for better inputs and forecasts; (4) link with standardized sensor and database networks; (5) promote modular, open-source architectures; and (6) build capacity in under-resourced regions. These priorities will substantially enhance CM robustness, comparability, and usability, reinforcing their role in guiding sustainable food system transformation. Y1 - 2025 U6 - https://doi.org/10.1016/j.oneear.2025.101487 SN - 2590-3322 VL - 8 IS - 10 SP - 1 EP - 7 PB - Elsevier BV CY - Amsterdam ER -