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Implementing realistic biological variability in an individual-based Dynamic Energy Budget model

Josef Koch (UGent) and Karel De Schamphelaere (UGent)
(2019)
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Abstract
One of the biggest advantages of individual-based population models (IBMs) is the possibility to simulate biological variation among individual animals. Inter-individual variation is known to promote the ecological success of populations by making them more resilient to environmental changes and stress events. While inter-individual variation can be measured in virtually all populations, reproducing such variation in population models accurately is not always straightforward. That is mainly because variation can be measured in apical endpoints like development time, size at a certain age or life stage, or reproduction success, but not on the underlying physiological parameters of the organism. In IBMs that make use of the Dynamic Energy Budget (DEB) theory, the development of an organism depends on 12 primary parameters, all of which potentially vary among individuals to some extent. While previous studies included stochastic scatter for individual parameters (one at a time), the degree of variation in this parameter has always been chosen rather arbitrarily. In this study we used experimental data on the development time and brood sizes of the copepod Nitocra spinipes reared at control conditions to make realistic estimates of the variability in DEB parameters for this species. As a first step, a global sensitivity analysis was performed to identify the parameters that are linked most closely to the observed endpoints. Subsequently, stochastic scatter was introduced to these parameters by drawing them from a probability distribution (multiple distribution types were tested and compared ranging from uniform to log-normal distributions). The degree of variation per parameter was adjusted by means of an optimisation algorithm that makes use Monte Carlo simulations. The Kolmogorov-Smirnov test statistic was used to assess the difference between measured versus simulated data. A simulated annealing approach was then used to optimise the variation parameters.

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Citation

Please use this url to cite or link to this publication:

Chicago
Koch, Josef, and Karel De Schamphelaere. 2019. “Implementing Realistic Biological Variability in an Individual-based Dynamic Energy Budget Model.” In .
APA
Koch, J., & De Schamphelaere, K. (2019). Implementing realistic biological variability in an individual-based Dynamic Energy Budget model. Presented at the SETAC Europe 29th Annual Meeting.
Vancouver
1.
Koch J, De Schamphelaere K. Implementing realistic biological variability in an individual-based Dynamic Energy Budget model. 2019.
MLA
Koch, Josef, and Karel De Schamphelaere. “Implementing Realistic Biological Variability in an Individual-based Dynamic Energy Budget Model.” 2019. Print.
@inproceedings{8625063,
  abstract     = {One of the biggest advantages of individual-based population models (IBMs) is the possibility to simulate biological variation among individual animals. Inter-individual variation is known to promote the ecological success of populations by making them more resilient to environmental changes and stress events. While inter-individual variation can be measured in virtually all populations, reproducing such variation in population models accurately is not always straightforward. That is mainly because variation can be measured in apical endpoints like development time, size at a certain age or life stage, or reproduction success, but not on the underlying physiological parameters of the organism. In IBMs that make use of the Dynamic Energy Budget (DEB) theory, the development of an organism depends on 12 primary parameters, all of which potentially vary among individuals to some extent. While previous studies included stochastic scatter for individual parameters (one at a time), the degree of variation in this parameter has always been chosen rather arbitrarily. In this study we used experimental data on the development time and brood sizes of the copepod Nitocra spinipes reared at control conditions to make realistic estimates of the variability in DEB parameters for this species. As a first step, a global sensitivity analysis was performed to identify the parameters that are linked most closely to the observed endpoints. Subsequently, stochastic scatter was introduced to these parameters by drawing them from a probability distribution (multiple distribution types were tested and compared ranging from uniform to log-normal distributions). The degree of variation per parameter was adjusted by means of an optimisation algorithm that makes use Monte Carlo simulations. The Kolmogorov-Smirnov test statistic was used to assess the difference between measured versus simulated data. A simulated annealing approach was then used to optimise the variation parameters.},
  author       = {Koch, Josef and De Schamphelaere, Karel},
  language     = {eng},
  location     = {Helsinki },
  title        = {Implementing realistic biological variability in an individual-based Dynamic Energy Budget model},
  url          = {http://dx.doi.org/10.13140/RG.2.2.20484.27522},
  year         = {2019},
}

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