You are here:
Mechanistic Population Models for Decision Support: The Importance of Good Conceptual Model Diagrams
Citation:
Forbes, V., C. Accolla, T. Banitz, N. Galic, V. Grimm, Sandy Raimondo, A. Schmolke, AND M. Vaugeois. Mechanistic Population Models for Decision Support: The Importance of Good Conceptual Model Diagrams. SETAC Europe 32nd Annual Meeting, Copenhagen, DENMARK, May 15 - 19, 2022.
Impact/Purpose:
The use of mechanistic models as research and decision-support tools in ecology and ecological risk assessment is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as standardized approaches for model development (e.g., Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE). Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Here we define a conceptual model as a verbal description of the key state variables, processes, interactions, and external drivers in the model. The verbal description is often summarized in a conceptual model diagram (CMD), the purpose of which is to facilitate communication of the model to a variety of audiences. Because model steps are embedded within the model code, potential model users may not be familiar with the computer language used to implement the model to understand and translate what is happening inside the “black box”. As a result, it can be a challenge for such models to be trusted to support real-world decision making. Consistent model documentation, which can be clearly articulated in the decision steps following Pop-GUIDE, and a well constructed conceptual model (verbal and diagrammatic) should improve model transparency and consistency. A good CMD can serve as an Executive Summary of the model and is a helpful tool when communicating model development and functionality it to different audiences and stakeholders.
Description:
The use of mechanistic models as research and decision-support tools in ecology and ecological risk assessment is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as standardized approaches for model development (e.g., Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE). Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Here we define a conceptual model as a verbal description of the key state variables, processes, interactions, and external drivers in the model. The verbal description is often summarized in a conceptual model diagram (CMD), the purpose of which is to facilitate communication of the model to a variety of audiences. Because model steps are embedded within the model code, potential model users may not be familiar with the computer language used to implement the model to understand and translate what is happening inside the “black box”. As a result, it can be a challenge for such models to be trusted to support real-world decision making. Consistent model documentation, which can be clearly articulated in the decision steps following Pop-GUIDE, and a well constructed conceptual model (verbal and diagrammatic) should improve model transparency and consistency. A good CMD can serve as an Executive Summary of the model and is a helpful tool when communicating model development and functionality it to different audiences and stakeholders.
