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On the Use of a Simple Physical System Analogy to Study Robustness Features in Animal Sciences.

Sadoul B, Martin O, Prunet P, Friggens NC - PLoS ONE (2015)

Bottom Line: The model has proven to properly fit the different responses measured in this study and to quantitatively describe the different temporal patterns for each statistical individual in the study.It provides therefore a new way to explicitly describe, analyze and compare responses of individuals facing an acute perturbation.This study suggests that such physical models may be usefully applied to characterize robustness in many other biological systems.

View Article: PubMed Central - PubMed

Affiliation: INRA, LPGP Fish Physiology and Genomics UR1037, Rennes, France.

ABSTRACT
Environmental perturbations can affect the health, welfare, and fitness of animals. Being able to characterize and phenotype adaptive capacity is therefore of growing scientific concern in animal ecology and in animal production sciences. Terms borrowed from physics are commonly used to describe adaptive responses of animals facing an environmental perturbation, but no quantitative characterization of these responses has been made. Modeling the dynamic responses to an acute challenge was used in this study to facilitate the characterization of adaptive capacity and therefore robustness. A simple model based on a spring and damper was developed to simulate the dynamic responses of animals facing an acute challenge. The parameters characterizing the spring and the damper can be interpreted in terms of stiffness and resistance to the change of the system. The model was tested on physiological and behavioral responses of rainbow trout facing an acute confinement challenge. The model has proven to properly fit the different responses measured in this study and to quantitatively describe the different temporal patterns for each statistical individual in the study. It provides therefore a new way to explicitly describe, analyze and compare responses of individuals facing an acute perturbation. This study suggests that such physical models may be usefully applied to characterize robustness in many other biological systems.

No MeSH data available.


Related in: MedlinePlus

Sensitivity analysis of the model where the parameter Fpert varies and a continuous perturbation occurs between time 20 and 60.For this analysis, perc was set to 1, K to 0.1 and C to 2. Fpert varies between 1 and 10. We define the value T = C/K as the decay constant, characterizing the recovery capacity of the system, xmax the value of x at the end of the perturbation and xinf the value of x if the perturbation continues.
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pone.0137333.g006: Sensitivity analysis of the model where the parameter Fpert varies and a continuous perturbation occurs between time 20 and 60.For this analysis, perc was set to 1, K to 0.1 and C to 2. Fpert varies between 1 and 10. We define the value T = C/K as the decay constant, characterizing the recovery capacity of the system, xmax the value of x at the end of the perturbation and xinf the value of x if the perturbation continues.

Mentions: The sensitivity analysis showed that varying C and K in the model resulted in a strong diversity of dynamics (Figs 4 and 5). As expected, the parameter K has a strong effect on the amplitude of the response (Fig 4). The relationship between the maximum of the amplitude and K is approximately hyperbolic, with low values of K strongly increasing the amplitude of the response. Similarly, the time of recovery T is approximately hyperbolic to parameter K, with a strong decrease when K increases. Globally, parameter C has a strong impact on the shape of the response since it influences the speed of the deformation (Fig 5). This parameter has no impact on the asymptotic x (xinf), however it impacts the xmax value if the time of perturbation is not long enough to enable the system to reach xinf. When the time of perturbation is low, the value xmax and C are negatively correlated. The relationship between the time of recovery and C is proportional. The variable Fpert has a positive linear impact on the amplitude of response xmax and xinf (Fig 6). However, it has no impact on the recovery. The effect of K on the response is highly dependent on C (Fig 7). Globally, K has a stronger impact on the amplitude of the response when C is low. The parameter K defines therefore the asymptote value that a given perturbation would produce if it continued for long enough. We call K the “deformation potential” or the stiffness of the system. On the contrary, C has a strong effect on the shape of the response. The C effect is less impacted by the value of K, and can be defined as the “capacity to impede the deformation” or the resistance of the system to the deformation.


On the Use of a Simple Physical System Analogy to Study Robustness Features in Animal Sciences.

Sadoul B, Martin O, Prunet P, Friggens NC - PLoS ONE (2015)

Sensitivity analysis of the model where the parameter Fpert varies and a continuous perturbation occurs between time 20 and 60.For this analysis, perc was set to 1, K to 0.1 and C to 2. Fpert varies between 1 and 10. We define the value T = C/K as the decay constant, characterizing the recovery capacity of the system, xmax the value of x at the end of the perturbation and xinf the value of x if the perturbation continues.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4554989&req=5

pone.0137333.g006: Sensitivity analysis of the model where the parameter Fpert varies and a continuous perturbation occurs between time 20 and 60.For this analysis, perc was set to 1, K to 0.1 and C to 2. Fpert varies between 1 and 10. We define the value T = C/K as the decay constant, characterizing the recovery capacity of the system, xmax the value of x at the end of the perturbation and xinf the value of x if the perturbation continues.
Mentions: The sensitivity analysis showed that varying C and K in the model resulted in a strong diversity of dynamics (Figs 4 and 5). As expected, the parameter K has a strong effect on the amplitude of the response (Fig 4). The relationship between the maximum of the amplitude and K is approximately hyperbolic, with low values of K strongly increasing the amplitude of the response. Similarly, the time of recovery T is approximately hyperbolic to parameter K, with a strong decrease when K increases. Globally, parameter C has a strong impact on the shape of the response since it influences the speed of the deformation (Fig 5). This parameter has no impact on the asymptotic x (xinf), however it impacts the xmax value if the time of perturbation is not long enough to enable the system to reach xinf. When the time of perturbation is low, the value xmax and C are negatively correlated. The relationship between the time of recovery and C is proportional. The variable Fpert has a positive linear impact on the amplitude of response xmax and xinf (Fig 6). However, it has no impact on the recovery. The effect of K on the response is highly dependent on C (Fig 7). Globally, K has a stronger impact on the amplitude of the response when C is low. The parameter K defines therefore the asymptote value that a given perturbation would produce if it continued for long enough. We call K the “deformation potential” or the stiffness of the system. On the contrary, C has a strong effect on the shape of the response. The C effect is less impacted by the value of K, and can be defined as the “capacity to impede the deformation” or the resistance of the system to the deformation.

Bottom Line: The model has proven to properly fit the different responses measured in this study and to quantitatively describe the different temporal patterns for each statistical individual in the study.It provides therefore a new way to explicitly describe, analyze and compare responses of individuals facing an acute perturbation.This study suggests that such physical models may be usefully applied to characterize robustness in many other biological systems.

View Article: PubMed Central - PubMed

Affiliation: INRA, LPGP Fish Physiology and Genomics UR1037, Rennes, France.

ABSTRACT
Environmental perturbations can affect the health, welfare, and fitness of animals. Being able to characterize and phenotype adaptive capacity is therefore of growing scientific concern in animal ecology and in animal production sciences. Terms borrowed from physics are commonly used to describe adaptive responses of animals facing an environmental perturbation, but no quantitative characterization of these responses has been made. Modeling the dynamic responses to an acute challenge was used in this study to facilitate the characterization of adaptive capacity and therefore robustness. A simple model based on a spring and damper was developed to simulate the dynamic responses of animals facing an acute challenge. The parameters characterizing the spring and the damper can be interpreted in terms of stiffness and resistance to the change of the system. The model was tested on physiological and behavioral responses of rainbow trout facing an acute confinement challenge. The model has proven to properly fit the different responses measured in this study and to quantitatively describe the different temporal patterns for each statistical individual in the study. It provides therefore a new way to explicitly describe, analyze and compare responses of individuals facing an acute perturbation. This study suggests that such physical models may be usefully applied to characterize robustness in many other biological systems.

No MeSH data available.


Related in: MedlinePlus