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From theory to practice in pattern-oriented modelling : identifying and using empirical patterns in predictive models

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Gallagher_2021_BR_theory_practice_CC.pdf (1.469Mb)
Date
12/05/2021
Author
Gallagher, Cara A.
Chudzinska, Magda
Larsen-Gray, Angela
Pollock, Christopher J.
Sells, Sarah N.
White, Patrick J. C.
Berger, Uta
Keywords
Agent-based
Individual-based
Modelling
Pattern-oriented
Complex systems
Predictions
Ecology
Theory development
Predictive ecology
QA Mathematics
QH301 Biology
T-NDAS
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Abstract
To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern‐oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent‐based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM‐ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM‐ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.
Citation
Gallagher , C A , Chudzinska , M , Larsen-Gray , A , Pollock , C J , Sells , S N , White , P J C & Berger , U 2021 , ' From theory to practice in pattern-oriented modelling : identifying and using empirical patterns in predictive models ' , Biological Reviews , vol. Early View . https://doi.org/10.1111/brv.12729
Publication
Biological Reviews
Status
Peer reviewed
DOI
https://doi.org/10.1111/brv.12729
ISSN
1464-7931
Type
Journal article
Rights
Copyright © 2021 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Description
This manuscript was developed as part of the PhD project of C.A.G. funded by Aarhus University. M.C. was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement No 746602. Open access funding enabled and organized by Projekt DEAL.
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  • University of St Andrews Research
URL
https://onlinelibrary.wiley.com/doi/10.1111/brv.12729#support-information-section
URI
http://hdl.handle.net/10023/23172

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