Is structural sensitivity a problem of oversimplified biological models? Insights from nested Dynamic Energy Budget models. (7th July 2018)

• Record Type: Journal Article
• Authors: Aldebert, Clement; Kooi, Bob W; Nerini, David; Poggiale, Jean-Christophe
• Is Part Of: Journal of theoretical biology. Volume 448(2018)
• Page Start: 1
• Page End: 8
• Publication Date: 2018-07-07
• Subjects: Model sensitivity -- Functional response -- Metabolism -- Bifurcations -- Chemostat; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2018.03.019
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract : Four predator–prey models in chemostat are built from Dynamic Energy Budget theory. Structural sensitivity to functional response formulation is investigated. The less detailed metabolic model (Monod) leads to higher structural sensitivity. Structural sensitivity is lower in mass-balanced models including maintenance. Abstract: Many current issues in ecology require predictions made by mathematical models, which are built on somewhat arbitrary choices. Their consequences are quantified by sensitivity analysis to quantify how changes in model parameters propagate into an uncertainty in model predictions. An extension called structural sensitivity analysis deals with changes in the mathematical description of complex processes like predation. Such processes are described at the population scale by a specific mathematical function taken among similar ones, a choice that can strongly drive model predictions. However, it has only been studied in simple theoretical models. Here, we ask whether structural sensitivity is a problem of oversimplified models. We found in predator–prey models describing chemostat experiments that these models are less structurally sensitive to the choice of a specific functional response if they include mass balance resource dynamics and individual maintenance. Neglecting these processes in an ecological model (for instance by using the well-known logistic growth equation) is not only an inappropriate description of the ecological system, but also a source of more uncertain predictions.