Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1002/ieam.4362
Document Shareable Link
Title (Primary) A review of key features and their implementation in unstructured, structured, and agent‐based population models for ecological risk assessment
Author Accolla, C.; Vaugeois, M.; Grimm, V.; Moore, A.P.; Rueda‐Cediel, P.; Schmolke, A.; Forbes, V.E.
Source Titel Integrated Environmental Assessment and Management
Year 2021
Department OESA
Volume 17
Issue 3
Page From 521
Page To 540
Language englisch
Topic T5 Future Landscapes
Supplements https://setac.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fieam.4362&file=ieam4362-sup-0001-Database.xlsx
https://setac.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fieam.4362&file=ieam4362-sup-0002-SI_Statistical_analyses.docx
Keywords Good modeling practice; ecological risk assessment; matrix models; agent‐based models; ODE models
Abstract Population models can provide valuable tools for Ecological Risk Assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life‐history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate three broadly defined population model types (unstructured, structured, and agent‐based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model‐type choice, how features are implemented, and, possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent‐based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=23850
Accolla, C., Vaugeois, M., Grimm, V., Moore, A.P., Rueda‐Cediel, P., Schmolke, A., Forbes, V.E. (2021):
A review of key features and their implementation in unstructured, structured, and agent‐based population models for ecological risk assessment
Integr. Environ. Assess. Manag. 17 (3), 521 - 540