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.
Original language | English |
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Pages (from-to) | 1-8 |
Number of pages | 8 |
Journal | Journal of Theoretical Biology |
Volume | 448 |
Early online date | 14 Mar 2018 |
DOIs | |
Publication status | Published - 7 Jul 2018 |
Funding
We thanks SALM Kooijman and the participants of the 8th and 9th International Course and Symposia on DEB theory (Marseilles, France, 2015 and Tromsø, Norway, 2017). We acknowledge Mathias Gauduchon, Owen Petchey, Aurelie Garnier, and the two anonymous reviewers for discussion and comments. The PhD scholarship of CA was funded by the French Ministry of Higher Education and Research. CA, DN and JCP received funding from European FEDER Fund under project 1166-39417.
Funders | Funder number |
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FEDER Fund | 1166-39417 |
Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche |
Keywords
- Bifurcations
- Chemostat
- Functional response
- Metabolism
- Model sensitivity