Joint Special Issue on Good Modelling Practice

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

The issue remains open for submissions.

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 Modelling6, 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 Modelling6, 18701. https://doi.org/10.18174/sesmo.18701

How to use the impossible map – Considerations for a rigorous exploration of Digital Twins of the Earth
Robert Reinecke, Francesca Pianosi, Thorsten Wagener (2024)
Socio-Environmental Systems Modelling6, 18786. https://doi.org/10.18174/sesmo.18786

Promoting scientific software quality through transition to continuous integration and continuous
Anja Schubert, Robert Argent delivery (2024)
Socio-Environmental Systems Modelling6, 18779. https://doi.org/10.18174/sesmo.18779

Increasing behavioral richness and managing structural uncertainty in social-ecological system agent-based models
Nicholas Magliocca, Ruchie Pathak, Ashleigh Price, Hashir Tanveer, Mukesh Kumar, Hamid Moradkhani (2024)
Socio-Environmental Systems Modelling6, 18749. https://doi.org/10.18174/sesmo.18749

“Knowledge Strength”: maximising the reliability of evidence derived from environmental modelling in the face of uncertainty – the case of the salmon louse (Lepeophtheirus salmonis)
Alexander Murray, Lars Asplin, Gunnvor a Nordi, Sissal Erenbjerg, Alejandro Gallego, Stephen C. Ives, Erin King, Trondur Kragesteen, Joanne Murphy, Berit Rabe, Anne D. Sandvik, Jofrid Skardhamar, Meadhbh Moriarty (2025)
Socio-Environmental Systems Modelling, 7, 18750. https://doi.org/10.18174/sesmo.18750

Applying an ethical lens for more responsible modelling practice
Katrina Szetey, Delphi Ward, Sabrina Chakori, David Douglas, Elizabeth A. Fulton, Nicola Grigg, Emma Ligtermoet, Claudia Munera-Roldan, Esther Onyango, Erinne Stirling, Roshni Subramaniam (2025)
Socio-Environmental Systems Modelling, 7, 18753. https://doi.org/10.18174/sesmo.18753

Eliciting psychosocial factors using search query data to improve conceptual modeling: A case study of Japanese food supply chains during the COVID-19 pandemic
Akinori Komaki, Mizuho Sato, Madoka Nakajima, Naohiko Kohtake (2025)
Socio-Environmental Systems Modelling, 7, 18751. https://doi.org/10.18174/sesmo.18751

Community-informed Decisions for Equitable, Cost-effective, and Inclusive Disaster Resilience Planning (Co-DECIDR): A modeling approach
Mahdi Zareei, Carissa Knox, Jennifer Helgeson, Steven A. Gray, Richard C. Sadler, Laura Schmitt Olabisi, Chelsea Wentworth
Socio-Environmental Systems Modelling, 7, 18759. https://doi.org/10.18174/sesmo.18759

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

Integrating the theory of planned behavior in agent-based models: A systematic review of applications of pro-environmental behaviors
Mahdi Taraghi, Landon Yoder (2025)
Ecological Modelling, 508, 111231. https://doi.org/10.1016/j.ecolmodel.2025.111231

Mathematical validation of cleaning symbiosis between Macrobrachium lamarrei and Labeo rohita as an effective bio-control method against Argulus bengalensis
Netri Datta, Fahad Al Basir, Sagar Adhurya, Samar Kumar Saha, Santanu Ray (2025)
Ecological Modelling, 508, 111205. https://doi.org/10.1016/j.ecolmodel.2025.111205

How well do SDMs calibrated at large extents predict distribution in sub-areas: A case study
Moritz Fallgatter, Stefan Dullinger, Karl Hülber, Dietmar Moser, ... Johannes Wessely (2025)
Ecological Modelling, 507, 111170. https://doi.org/10.1016/j.ecolmodel.2025.111170

Environmental system dynamics: Current development and applications
Sihui Xin, Zhouyuan Li, Junsong Nong, Jiaxin Wu, ... Shaopeng Wang (2025)
Ecological Modelling, 506, 111135. https://doi.org/10.1016/j.ecolmodel.2025.111135

Forest insect populations: Modeling of critical events as first- and second-order phase transitions
V.G. Soukhovolsky, O.V. Tarasova, A.V. Kovalev, Yu.D. Ivanova, ... V.V. Martemyanov (2025)
Ecological Modelling, 504, 111090. https://doi.org/10.1016/j.ecolmodel.2025.111090

Model perpetuation by designing and documenting models and workflows so that they can be reused and further developed by others: The case of multiple stressors in ecology
Laura Meier, Volker Grimm, Karin Frank (2025)
Ecological Modelling, 501, 111029. https://doi.org/10.1016/j.ecolmodel.2025.111029

Particle tracking modelling in coastal marine environments: Recommended practices and performance limitations
Soizic Garnier, Rory O'Hara Murray, Philip A. Gillibrand, Alejandro Gallego, ... Meadhbh Moriarty (2025)
Ecological Modelling, 501, 110999. https://doi.org/10.1016/j.ecolmodel.2024.110999

A protocol for implementing parameter sensitivity analyses in complex ecosystem models
Criscely Luján, Yunne-Jai Shin, Nicolas Barrier, Paul Leadley, Ricardo Oliveros-Ramos (2025)
Ecological Modelling, 501, 110990. https://doi.org/10.1016/j.ecolmodel.2024.110990

Bayesian networks facilitate updating of species distribution and habitat suitability models
Adam Duarte, Robert S. Spaan, James T. Peterson, Christopher A. Pearl, Michael J. Adams (2025)
Ecological Modelling, 501, 110982. https://doi.org/10.1016/j.ecolmodel.2024.110982

Using the ODD protocol and NetLogo to replicate agent-based models
Volker Grimm, Uta Berger, Justin M. Calabrese, Ainara Cortés-Avizanda, ... Steven F. Railsback (2025)
Ecological Modelling, 501, 110967. https://doi.org/10.1016/j.ecolmodel.2024.110967

Machine learning emulators of dynamical systems for understanding ecosystem behaviour
Oriol Pomarol Moya, Siamak Mehrkanoon, Madlene Nussbaum, Walter W. Immerzeel, Derek Karssenberg (2025)
Ecological Modelling, 501, 110956. https://doi.org/10.1016/j.ecolmodel.2024.110956

The different ways to operationalise the social in applied models and simulations of sustainability science: A contribution for the enhancement of good modelling practices
Ronald B. Bialozyt, Martina Roß-Nickoll, Richard Ottermanns, Jens Jetzkowitz (2025)
Ecological Modelling, 500, 110952. https://doi.org/10.1016/j.ecolmodel.2024.110952

A model-based policy analysis framework for social-ecological systems: Integrating uncertainty and participation in system dynamics modelling
Henry Amorocho-Daza, Janez Sušnik, Pieter van der Zaag, Jill H. Slinger (2025)
Ecological Modelling, 499, 110943. https://doi.org/10.1016/j.ecolmodel.2024.110943

Structural differences across hydrological models affect certainty of predictions of nature-based solution benefits
Alanna J. Rebelo, Julia Glenday, Petra B. Holden, Shaeden Gokool, ... Jane Tanner (2025)
Ecological Modelling, 501, 110940. https://doi.org/10.1016/j.ecolmodel.2024.110940

A general DDE framework to describe insect populations: Why delays are so important?
Luca Rossini, Nicolás Bono Rosselló, Ouassim Benhamouche, Mario Contarini, ... Emanuele Garone (2025)
Ecological Modelling, 499, 110937. https://doi.org/10.1016/j.ecolmodel.2024.110937

Cracking the code: Linking good modeling and coding practices for new ecological modelers
Todd M. Swannack, Kiara C. Cushway, Carra C. Carrillo, Clementina Calvo, ... Waverly E. Wadsworth (2025)
Ecological Modelling, 499, 110926. https://doi.org/10.1016/j.ecolmodel.2024.110926

Uncertainty analysis of hydrological parameters of the APEXgraze model for grazing activities
Mahesh L. Maskey, Amanda M. Nelson, Daniel N. Moriasi, Brian K. Northup (2025)
Ecological Modelling, 499, 110917. https://doi.org/10.1016/j.ecolmodel.2024.110917

Models vetted against prediction error and parameter sensitivity standards can credibly evaluate ecosystem management options
Timothy C. Haas (2025)
Ecological Modelling, 498, 110900. https://doi.org/10.1016/j.ecolmodel.2024.110900

More transparent and explainable machine learning algorithms are required to provide enhanced and sustainable dataset understanding
David A. Wood (2025)
Ecological Modelling, 498, 110898. https://doi.org/10.1016/j.ecolmodel.2024.110898

Model-based experiments as epistemic evidence in paleoecology
Wolfgang Traylor (2025)
Ecological Modelling, 498, 110895. https://doi.org/10.1016/j.ecolmodel.2024.110895

Good modelling software practices
Carsten Lemmen, Philipp Sebastian Sommer
Ecological Modelling, 498, 110890. https://doi.org/10.1016/j.ecolmodel.2024.110890

When to add a new process to a model – and when not: A marine biogeochemical perspective
Adrian P. Martin, Angela Bahamondes Dominguez, Chelsey A. Baker, Chloé M.J. Baumas, ... Andrew Yool (2025)
Ecological Modelling, 498, 110870. https://doi.org/10.1016/j.ecolmodel.2024.110870

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

Atlantis end-to-end modeling to explore ecosystem dynamics in the Strait of Sicily, Central Mediterranean Sea
Matteo Sinerchia, Fabio Fiorentino, Francesco Colloca, Andrea Cucco, ... Elizabeth A. Fulton (2025)
Environmental Modelling & Software, 183, 106237. https://doi.org/10.1016/j.envsoft.2024.106237

An R package to partition observation data used for model development and evaluation to achieve model generalizability
Yiran Ji, Feifei Zheng, Jinhua Wen, Qifeng Li, ... Hoshin V. Gupta (2025)
Environmental Modelling & Software, 183, 106238. https://doi.org/10.1016/j.envsoft.2024.106238

What is the optimal digital elevation model grid size to best capture hillslope gullies and contour drains?
D. Dimuth P. Welivitiya, G.R. Hancock (2025)
Environmental Modelling & Software, 188, 106404. https://doi.org/10.1016/j.envsoft.2025.106404

Towards good practice In engaging users In evaluation of computer model Software: Introducing the critical appraisal approach (CAA)
Caroline Rosello, Joseph H.A. Guillaume, Peter Taylor, Susan M. Cuddy, ... Anthony J. Jakeman (2025)
Environmental Modelling & Software, 190, 106469. https://doi.org/10.1016/j.envsoft.2025.106469

Urban flood modelling: Challenges and opportunities - A stakeholder-informed analysis
Muhammad Qasim Mahmood, Xiuquan Wang, Farhan Aziz, Nilay Dogulu (2025)
Environmental Modelling & Software, 191, 106507. https://doi.org/10.1016/j.envsoft.2025.106507

Improving the consistency of hydrologic event identification
Mohammad Masoud Mohammadpour Khoie, Danlu Guo, Conrad Wasko (2025)
Environmental Modelling & Software, 191, 106521. https://doi.org/10.1016/j.envsoft.2025.106521