SESMO is an Open Access, Community Driven, Scholarly Journal, that aims:
To progress our understanding, learning and decision making on major socio-environmental issues using advances in model-grounded processes that engage with institutional and governance contexts, cross-sectoral and scale challenges, and stakeholder perspectives.
Fit-for-purpose problem framing, model development and evaluation as well as eclectic uncertainty analysis are stressed so that the advantages and limitations of model-related assumptions are transparent. The aim is to advance model-grounded, learning and decision processes and their wider application to a new level that leads to innovations in thinking and practice to support resolution of grand challenge problems; including generating policy insights and evidence, and reducing and managing critical uncertainties (assumptions, model structure, parameterizations, inputs including future drivers, and boundary conditions). Papers may address how science can help identify and provide germane information and support required by managers, decision-makers and society at large.