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A statistical framework for genetic association studies of power curves in bird flight.

Lin M, Zhao W, Wu R - Biol Proced Online (2006)

Bottom Line: In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population.Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy.The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, University of Florida, Gainesville, FL 32611, USA.

ABSTRACT
How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

No MeSH data available.


Comparative mass-specific pectoralis power as a function of flight velocity in cockatiels, doves and magpies. Bird silhouettes are shown to scale, digitized from video. These different power curves can be described by equation (1), with different parameters combinations (α,β,γ). Adapted from Tobalske et al. (2003).
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Figure 1: Comparative mass-specific pectoralis power as a function of flight velocity in cockatiels, doves and magpies. Bird silhouettes are shown to scale, digitized from video. These different power curves can be described by equation (1), with different parameters combinations (α,β,γ). Adapted from Tobalske et al. (2003).

Mentions: The mechanical power required to fly in relation to forward velocity is the sum of three main drag components: induced, parasite and profile drag (Appendix; 8). According to aerodynamic theory applied to flying birds, mechanical power (P, W) should vary as a function of forward speed (V, ms-1 ) in a U-shaped curve (9, 10). But many empirical observations in different birds, such as the black-billed magpie and hummingbirds, suggest that the power curves of bird flight may also be J- or L-shaped (5, 6, 11). Figure 1 presents an excellent example, recently published in Nature (7), in which dramatic differences exist in power curve among different bird species. Some physiological and biomechanical explanations are offered about the deviation of the shape of biological power curves from that expected aerodynamic theory (1, 4). It is likely that these different shapes of power curves that have been identified both between and within species (4) include the genetic basis, although little genetic data have been collected.


A statistical framework for genetic association studies of power curves in bird flight.

Lin M, Zhao W, Wu R - Biol Proced Online (2006)

Comparative mass-specific pectoralis power as a function of flight velocity in cockatiels, doves and magpies. Bird silhouettes are shown to scale, digitized from video. These different power curves can be described by equation (1), with different parameters combinations (α,β,γ). Adapted from Tobalske et al. (2003).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC1622763&req=5

Figure 1: Comparative mass-specific pectoralis power as a function of flight velocity in cockatiels, doves and magpies. Bird silhouettes are shown to scale, digitized from video. These different power curves can be described by equation (1), with different parameters combinations (α,β,γ). Adapted from Tobalske et al. (2003).
Mentions: The mechanical power required to fly in relation to forward velocity is the sum of three main drag components: induced, parasite and profile drag (Appendix; 8). According to aerodynamic theory applied to flying birds, mechanical power (P, W) should vary as a function of forward speed (V, ms-1 ) in a U-shaped curve (9, 10). But many empirical observations in different birds, such as the black-billed magpie and hummingbirds, suggest that the power curves of bird flight may also be J- or L-shaped (5, 6, 11). Figure 1 presents an excellent example, recently published in Nature (7), in which dramatic differences exist in power curve among different bird species. Some physiological and biomechanical explanations are offered about the deviation of the shape of biological power curves from that expected aerodynamic theory (1, 4). It is likely that these different shapes of power curves that have been identified both between and within species (4) include the genetic basis, although little genetic data have been collected.

Bottom Line: In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population.Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy.The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, University of Florida, Gainesville, FL 32611, USA.

ABSTRACT
How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

No MeSH data available.