Socio-Environmental Systems Modelling

Current Issue

Vol. 6
Published February 12, 2024
Sixth Issue (In Prep.)

Earlier Issues: Issue 1 (2019), Issue 2 (2020), Issue 3 (2021), Issue 4 (2022) and Issue 5 (2023).

Special Issue: Participatory & cross-scale modelling of SESs in the Anthropocene

Dominic A. Martin, Myriam Pham-Truffert, Lara Gillham, O. Ravaka Andriamihaja, R. Ntsiva N. Andriatsitohaina, Clara L. Diebold, Thio Rosin Fulgence, Elke Kellner, Jorge Claudio Llopis, Peter Messerli, Anjaharinony A. N. A. Rakotomalala, Estelle Raveloaritiana, Annemarie Wurz, Julie G. Zaehringer, Andreas Heinimann
18637
Interactive visual syntheses for social-ecological systems understanding
Article Full Text (PDF)
Pete Barbrook-Johnson, George van Voorn, Hsiao-Hsuan Wang, Fateme Zare, William E. Grant, Zach Posnik, Melvin Lippe
18616
Cross-scale feedbacks and tipping points in aggregated models of socio-ecological systems
Article Full Text (PDF)

Special Issue: Sensitivity Analysis of Model Output

Xifu Sun, Anthony J. Jakeman, Barry F.W. Croke, Stephen G. Roberts, John D. Jakeman
18678
Assessing convergence in global sensitivity analysis: a review of methods for assessing and monitoring convergence
Article Full Text (PDF)
View All Issues

About SESMO

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.