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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

Fitting the model to Dry Matter Intake (DMI) and Milk Fat Content (MFC) in goats before, during and after a 2 days nutritional challenge (grey rectangle).Data (observed values ± SE) are expressed as fold changes. The inverse of DMI is illustrated since DMI is decreasing during the challenge. Stiffness (K) and resistance to change (C) parameters of the model were fitted on the mean of the DMI (K = 0.04, C = 0.06) and MFC (K = 0.72, C = 0.97) measures.
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pone.0137333.g009: Fitting the model to Dry Matter Intake (DMI) and Milk Fat Content (MFC) in goats before, during and after a 2 days nutritional challenge (grey rectangle).Data (observed values ± SE) are expressed as fold changes. The inverse of DMI is illustrated since DMI is decreasing during the challenge. Stiffness (K) and resistance to change (C) parameters of the model were fitted on the mean of the DMI (K = 0.04, C = 0.06) and MFC (K = 0.72, C = 0.97) measures.

Mentions: To illustrate its genericity, the model was tested on data obtained from a different type of challenge, in a different species; a nutritional challenge in goats [26]. In this study, 16 lactating goats were followed every day for dry matter intake (DMI) and milk fat content (MFC). Goats initially fed a standard diet were suddenly subjected to a 100% straw diet during 2 days. The measures were recorded before, during and after the nutritional challenge. The present model was fitted to MFC and DMI measures as described in the Materials and Methods. Fig 9 shows that the model was able to correctly fit the responses to the challenge providing values of resistance and recovery for MFC. However, the fitting of the recovery period for DMI was not totally satisfactory since the temporal pattern of DMI seems to display a rebound phenomenon that the model cannot capture in its present form. This type of phenomenon has been observed in other measures [23,27] and could be captured by adapting the damped spring model to include a mass during the recovery phase. However, this and the possible elaborations of the model would require further work, to explore the conceptual value of such modifications.


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)

Fitting the model to Dry Matter Intake (DMI) and Milk Fat Content (MFC) in goats before, during and after a 2 days nutritional challenge (grey rectangle).Data (observed values ± SE) are expressed as fold changes. The inverse of DMI is illustrated since DMI is decreasing during the challenge. Stiffness (K) and resistance to change (C) parameters of the model were fitted on the mean of the DMI (K = 0.04, C = 0.06) and MFC (K = 0.72, C = 0.97) measures.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0137333.g009: Fitting the model to Dry Matter Intake (DMI) and Milk Fat Content (MFC) in goats before, during and after a 2 days nutritional challenge (grey rectangle).Data (observed values ± SE) are expressed as fold changes. The inverse of DMI is illustrated since DMI is decreasing during the challenge. Stiffness (K) and resistance to change (C) parameters of the model were fitted on the mean of the DMI (K = 0.04, C = 0.06) and MFC (K = 0.72, C = 0.97) measures.
Mentions: To illustrate its genericity, the model was tested on data obtained from a different type of challenge, in a different species; a nutritional challenge in goats [26]. In this study, 16 lactating goats were followed every day for dry matter intake (DMI) and milk fat content (MFC). Goats initially fed a standard diet were suddenly subjected to a 100% straw diet during 2 days. The measures were recorded before, during and after the nutritional challenge. The present model was fitted to MFC and DMI measures as described in the Materials and Methods. Fig 9 shows that the model was able to correctly fit the responses to the challenge providing values of resistance and recovery for MFC. However, the fitting of the recovery period for DMI was not totally satisfactory since the temporal pattern of DMI seems to display a rebound phenomenon that the model cannot capture in its present form. This type of phenomenon has been observed in other measures [23,27] and could be captured by adapting the damped spring model to include a mass during the recovery phase. However, this and the possible elaborations of the model would require further work, to explore the conceptual value of such modifications.

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