| Title: | How to build Dynamic Energy Budget models : practical guidelines for model development |
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| Authors: | ID Oliveira, Diogo F. (Author)
ID Sulc, Anna (Author)
ID Le Moan, Eline (Author)
ID Dajčman, Urban (Author) |
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| Files: |  URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S0304380026002310?via%3Dihub
 PDF - Presentation file, download (2,89 MB)
MD5: F401750078C6A615D91E972C06DDB5F9
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  NIB - National Institute of Biology
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| Abstract: | Dynamic Energy Budget (DEB) theory provides a coherent framework to describe how organisms acquire and use energy and matter throughout the life cycle in response to environmental conditions. The wide applicability suggests the generality of DEB theory and is one of its main strengths. However, this same generality introduces a substantial degree of abstraction, which can make model development challenging, particularly for newcomers. This paper aims to support more transparent, biologically grounded, and reproducible DEB modeling by proposing guidelines to make the development process more explicit and accessible. We identify three main challenges: (1) how to link biological processes to their mathematical representation, (2) which observations are needed to inform key physiological processes, and (3) how to carry out parameter estimation and model validation in a transparent and reproducible way. To help overcome these issues, we briefly introduce core concepts and discuss the six main steps in the DEB modeling workflow: model design, data collection and assessment, implementation, calibration, validation, and publication. These steps are illustrated with a case study on zebrafish (Danio rerio) that demonstrates how data availability influences model development and the range of predictions that can be supported. By proposing a structured workflow, we hope to encourage researchers to explore the full potential of DEB theory. |
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| Keywords: | modeling development workflow, bioenergetics, good modeling practices, estimation in-context, model calibration, model validation, add-my-pet |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 24.06.2026 |
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| Year of publishing: | 2026 |
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| Number of pages: | str. 1-20 |
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| Numbering: | Vol. 521, [article no.] 111703 |
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| PID: | 20.500.12556/DiRROS-30932  |
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| UDC: | 57.01:51 |
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| ISSN on article: | 0304-3800 |
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| DOI: | 10.1016/j.ecolmodel.2026.111703 |
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| COBISS.SI-ID: | 283468547 |
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| Note: | Soavtorji: Anna Sulc, Eline Le Moan, Elisa Donati, Evridiki Klagkou, María-José Lagunes, Urban Dajčman, Tjui Yeuw Tan;
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| Publication date in DiRROS: | 08.07.2026 |
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| Views: | 29 |
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| Downloads: | 13 |
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