Mechanistic population models for ecological risk assessment and decision support: The importance of good conceptual model diagrams

Author:

Forbes Valery E.1,Accolla Chiara2,Banitz Thomas3,Crouse Kristin4,Galic Nika5,Grimm Volker3,Raimondo Sandy6,Schmolke Amelie2,Vaugeois Maxime7

Affiliation:

1. Department of Biological Sciences Florida Atlantic University Boca Raton Florida USA

2. Waterborne Environmental Inc Leesburg Virginia USA

3. Department of Ecological Modelling Helmholtz Centre for Environmental Research‐UFZ Leipzig Germany

4. Department of Ecology, Evolution and Behavior University of Minnesota St. Paul Minnesota USA

5. Syngenta Crop Protection AG Basel Switzerland

6. United States Environmental Protection Agency Office of Research and Development Gulf Breeze Florida USA

7. Syngenta Crop Protection LLC Greensboro North Carolina USA

Abstract

AbstractThe use of mechanistic population models as research and decision‐support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision‐support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;00:1–9. © 2023 SETAC

Publisher

Wiley

Subject

General Environmental Science,General Medicine,Geography, Planning and Development

Reference32 articles.

1. A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent‐Based Population Models for Ecological Risk Assessment

2. Visualization of causation in social‐ecological systems;Banitz T.;Ecology and Society,2022

3. Selecting parameters for calibration via sensitivity analysis: An individual-based model of mosquitofish population dynamics

4. Scientific opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products;European Food Safety Authority (EFSA);EFSA Journal,2014

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