Collaborating Journals: Socio-Environmental Systems Modelling (SESMO), Environmental Modelling and Software (EMS), and Ecological Modelling (ECOMOD)

Modelling, computational, conceptual or otherwise, has become an indispensable tool for dealing with complex socio-environmental systems (SES), whether the purpose be system understanding, prediction or social learning. It is crucial therefore that any modelling undertaken be adequate in its practices for the purposes. But despite early advances this century, guidance and protocols for good modelling practice (GMP) in different settings have been lacking.

This joint special issue intends to provide a platform for visible and ongoing attention to what ought to be the current standard(s) for an appropriate modelling protocol that considers uncertainty in all its facets and promotes transparency in the quest for robust and reliable results. It aims to bring together and highlight work that develops, applies, or evaluates procedures for a trustworthy modelling workflow or that investigates good modelling practices for particular aspects of the workflow. We invite research that aims to improve the scientific basis of the entire modelling chain and places good modelling practice in focus. Particular aspects of GMP might include (but are not limited to) contributions on:

1. Developing modelling conceptual maps, protocols and workflows
2. Benchmarking model results
3. Developing robust parameterization, calibration and evaluation frameworks
4. Going beyond common metrics in assessing model performance and realism, including qualitative methods
5. Conducting controlled model comparison studies
6. Investigating subjectivity and reflexivity along the modelling chain, and addressing model fitness for purpose
7. Identifying and prioritising sources of uncertainty and/or investigating uncertainty propagation along the modelling chain, and data acquisition planning for reducing uncertainty
8. Communicating model results and their uncertainty to end users of model results
9. Evaluating implications of model limitations and identifying priorities for future model development
10. Examples of developing FAIR principles for digital assets in the modelling chain (Findable, Accessible, Interoperable and Reusable – see https://www.comses.net/education/responsible-practices/)

Note that interpretation of what is an SES is considered widely. Systems for example may include ecological, hydrological, energy, policy, health and social sectors, often a combination of these or others. An aim is to share experiences of GMP across sectors and disciplines.

Which journal to publish in?

Authors can submit to one of the three journals but only one must be chosen. It is envisaged that manuscripts will be reviewed and assessed by the relevant journal selected by the author(s) and Guest Editors will be across all manuscript processes.

Guest editors: Hsiao-Hsuan (Rose) Wang,  Sondoss Elsawah, and Tony Jakeman

Manuscript submission information:

Deadlines for submission

Enquiries and Abstracts of 500 words as soon as possible to any of the three Guest Editors above. The deadline for full papers has been extended to the end of 2024. 

For any queries in submitting your manuscript please contact Tony Jakeman (tony.jakeman@anu.edu.au) for SESMO, Sondoss Elsawah (s.elsawah@adfa.edu.au) for EMS, and Hsiao-Hsuan (Rose) Wang (Hsiaohsuan.Wang@ag.tamu.edu) for ECOMOD, respectively.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript: SESMO submission guidelines 

Keywords:

Modelling practices; Integrated assessment and modelling; Socio-ecological systems; Decision support; uncertainty; scaling

Published Papers:

Towards normalizing good practice across the whole modeling cycle: its instrumentation and future research topics
Anthony J. Jakeman, Sondoss Elsawah, Hsiao-Hsuan Wang, Serena H. Hamilton, Lieke Melsen, Volker Grimm (2024)
Socio-Environmental Systems Modelling, 6, 18755. https://doi.org/10.18174/sesmo.18755

Model evaluation: The misuse of statistical techniques when evaluating observations versus predictions
Malcolm McPhee, Jonathan Richetti, Barry Croke, Brad Walmsley (2024)
Socio-Environmental Systems Modelling, 6, 18758. https://doi.org/10.18174/sesmo.18758

Developing multidisciplinary mechanistic models: challenges and approaches
Daniel Vedder, Samuel M. Fischer, Kerstin Wiegand, Guy Pe'er (2024) 
Socio-Environmental Systems Modelling, 6, 18701. https://doi.org/10.18174/sesmo.18701

Linking error measures to model questions
Bas Jacobs, Hilde Tobi, Geerten M. Hengeveld (2024)
Ecological Modelling, 487, 110562. https://doi.org/10.1016/j.ecolmodel.2023.110562

Bridging practice and science in socio-environmental systems research and modelling: A design science approach
Fateme Zare, Anthony J. Jakeman, Sondoss Elsawah, Joseph H.A. Guillaume (2024)
Ecological Modelling, 492, 110719. https://doi.org/10.1016/j.ecolmodel.2024.110719

A modeling framework of a territorial socio-ecosystem to study the trajectories of change in agricultural phytosanitary practices
Amélie Bourceret, Francesco Accatino, Corinne Robert (2024)
Ecological Modelling, 494, 110727. https://doi.org/10.1016/j.ecolmodel.2024.110727

The need for standardization in ecological modeling for decision support: Lessons from ecological risk assessment
Valery E. Forbes
Ecological Modelling, 492, 110736.  https://doi.org/10.1016/j.ecolmodel.2024.110736

Development of a fuzzy logic-embedded system dynamics model to simulate complex socio-ecological systems
Yongeun Kim, Minyoung Lee, Jinsol Hong, Yun-Sik Lee, June Wee, Kijong Cho (2024)
Ecological Modelling, 493, 110738. https://doi.org/10.1016/j.ecolmodel.2024.110738

Beyond guides, protocols and acronyms: Adoption of good modelling practices depends on challenging academia's status quo in ecology
Tatiane Micheletti, Marie-Christin Wimmler, Uta Berger, Volker Grimm, Eliot J. McIntire (2024)
Ecological Modelling, 493, 110829. https://doi.org/10.1016/j.ecolmodel.2024.110829

Good modelling practice in ecology, the hierarchical Bayesian perspective
Philip A. White, Alan E. Gelfand, Henry Frye, John A. Silander (2024)
Ecological Modelling, 496, 110847. https://doi.org/10.1016/j.ecolmodel.2024.110847

Useful properties of phenomenological-based models
Estefania Aguirre-Zapata, Laura Lema-Perez, Lina Gomez-Echavarria, Hector Botero-Castro, Juan C. Maya, Farid Chejne, Hernan Alvarez (2024)
Ecological Modelling, 496, 110850. https://doi.org/10.1016/j.ecolmodel.2024.110850

Real world data for real world problems: Importance of appropriate spatial resolution modelling to inform decision makers in marine management
Tanya G Riley, Beth Mouat, Rachel Shucksmith (2024)
Ecological Modelling, 498, 110864. https://doi.org/10.1016/j.ecolmodel.2024.110864

From formulae, via models to theories: Dynamic Energy Budget theory illustrates requirements
Sebastiaan A.L.M. Kooijman, Michael R. Kearney, Nina Marn, Tânia Sousa, Tiago Domingos, Romain Lavaud, Charlotte Récapet, Tin Klanjšček, Tan T. Yeuw, Gonçalo M. Marques, Laure Pecquerie, Konstadia Lika (2024)
Ecological Modelling, 497, 110869. https://doi.org/10.1016/j.ecolmodel.2024.110869

Quantifying ‘realistic’ uncertainty bounds as a part of sound hydrological modelling practice in data scarce regions of southern Africa
D.A. Hughes, D. Lawrence (2024)
Environmental Modelling & Software, 179, 106112. https://doi.org/10.1016/j.envsoft.2024.106112

A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware river basin, USA
P. Goodling, K. Belitz, P. Stackelberg, B. Fleming (2024)
Environmental Modelling & Software, 179, 106124. https://doi.org/10.1016/j.envsoft.2024.106124

Model linkage to assess forest disturbance impacts on water quality: A wildfire case study using LANDIS(II)-VELMA
Kar'retta Venable, John M. Johnston, Stephen D. LeDuc, Lourdes Prieto (2024)
Environmental Modelling & Software, 180, 106134. https://doi.org/10.1016/j.envsoft.2024.106134

A calibration protocol for soil-crop models
Daniel Wallach, Samuel Buis, Diana-Maria Seserman, Taru Palosuo, Peter J. Thorburn, Henrike Mielenz, Eric Justes, Kurt-Christian Kersebaum, Benjamin Dumont, Marie Launay,  Sabine Julia Seidel (2024)
Environmental Modelling & Software, 180, 106147. https://doi.org/10.1016/j.envsoft.2024.106147