Non-universal interspecific allometric scaling of metabolism

Silva, J. Kamphorst Leal da; Barbosa, Lauro A.

doi:10.1590/s0103-97332009000600014

Cited by 5 publications

(7 citation statements)

References 35 publications

(64 reference statements)

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“…This law, one of the few that appears to be well established in biology, has attracted much attention from both biological and physical scientists. Not surprisingly, frequent attempts have been made to use the quantitative methods of physics, a field which focuses largely on natural laws, to explain Kleiber's law (e.g., [6][7][8][9][10][11][12][13][14][15][16][17]). However, these mostly deterministic explanations (but see [18][19][20]) have failed to explain fully the marked diversity of metabolic scaling relationships that actually exists in the living world (b ranging between ~0 to >1, but mostly between 2/3 and 1 [21][22][23][24][25]).…”

Section: Introductionmentioning

confidence: 99%

Scaling of Metabolic Scaling within Physical Limits

Glazier

2014

Systems

197

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Both the slope and elevation of scaling relationships between log metabolic rate and log body size vary taxonomically and in relation to physiological or developmental state, ecological lifestyle and environmental conditions. Here I discuss how the recently proposed metabolic-level boundaries hypothesis (MLBH) provides a useful conceptual framework for explaining and predicting much, but not all of this variation. This hypothesis is based on three major assumptions: (1) various processes related to body volume and surface area exert state-dependent effects on the scaling slope for metabolic rate in relation to body mass; (2) the elevation and slope of metabolic scaling relationships are linked; and (3) both intrinsic (anatomical, biochemical and physiological) and extrinsic (ecological) factors can affect metabolic scaling. According to the MLBH, the diversity of metabolic scaling relationships occurs within physical boundary limits related to body volume and surface area. Within these limits, specific metabolic scaling slopes can be predicted from the metabolic level (or scaling elevation) of a species or group of species. In essence, metabolic scaling itself scales with metabolic level, which is in turn contingent on various intrinsic and extrinsic conditions operating in physiological or evolutionary time. The MLBH represents a "meta-mechanism" or collection of multiple, specific mechanisms that have contingent, state-dependent effects. As such, the MLBH is Darwinian in approach (the theory of natural selection is also meta-mechanistic), in contrast to currently influential metabolic scaling theory that is Newtonian in approach (i.e., based on unitary deterministic laws). Furthermore, the MLBH can be viewed as part of a more general theory that includes other mechanisms that may also affect metabolic scaling.

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Section: Introductionmentioning

confidence: 99%

Scaling of Metabolic Scaling within Physical Limits

Glazier

2014

Systems

197

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“…and the process of mass transport is different for different molecules in an organism [20]. da Silva et al explained the variation of 1  with the help of physical processes like diffusion, convection and anomalous diffusion for different organisms [21,22]. According to the study of Economos [23], the geometry of body surface, which is different for different organisms, is related with energy intake of the organism.…”

Section:  mentioning

confidence: 99%

“…According to the study of Economos [23], the geometry of body surface, which is different for different organisms, is related with energy intake of the organism. da Silva et al [22] compared the exponent of basal metabolic rates for different organisms and proposed a theoretical explanation for the different values of that exponent. So, growth process can be studied using different values of these scaling exponents.…”

Section:  mentioning

confidence: 99%

“…If only the metabolic maintenance costs are included, this difference is an energy surplus, used mainly for growth and reproduction. Experimental observations suggest that the energy allocated for reproduction has an allometric dependence on mass [7,21,30]. Therefore, the rate of energy allocation for reproduction   p E can be expressed as…”

Section: Model Formulationmentioning

confidence: 99%

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A theoretical analysis of the growth process of an organism and its dependence on various allometric relations

Roy¹,

Majumdar²,

Ghosh³

2011

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A new mathematical model regarding the growth process of an organism is proposed, based on the role of surplus power (<i>i.e.</i> power intake minus metabolic cost) and having an allometric dependence on mass. Considering its use in growth, a differential equation has been formed, similar to the von Bertalanffy growth function (VBGF). The time dependence of mass and growth rate, obtained from this equation, has been shown graphically to illustrate the roles played by scaling exponents and other parameters. Concepts of optimum mass, saturation mass and the mass corresponding to the highest growth rate have been discussed under the proposed theoretical framework. Information regarding the dependence of effective growth duration on various parameters has been found graphically. The time of occurrence of the highest growth rate and its dependence on various parameters have been explored graphically. A new parameter (<i>ρ</i>) has been defined, which determines the availability of surplus power at different stages of the growth process of an organism. Depending on its value, there can be three distinctly different modes of growth phenomenon, reflected in the change of surplus power with time. The variations of growth and reproduction efficiencies with time and mass have been shown for different values of the scaling exponent. The limitation regarding the practical measurement of growth rate has been discussed using the present model. Some aspects of length-biomass allometry have been explored theoretically and the results have been depicted graphically

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“…Lately, it has been determined that many real-world networks show cluster structures [11][12][13]. Cluster networks are relevant to many social and biological phenomena [14][15][16][17][18]. Cluster networks consist of a number of clusters, where nodes within each group are densely connected, while the linkage among the groups is sparse.…”

Section: Introductionmentioning

confidence: 99%

Efficiency dynamics on two coupled small-world networks

Zhang¹,

Shao²,

Yang³

2010

Braz. J. Phys.

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We investigate the effect of clusters in complex networks on efficiency dynamics by studying a simple efficiency model in two coupled small-world networks. It is shown that the critical network randomness corresponding to transition from a stagnant phase to a growing one decreases to zero as the connection strength of clusters increases. It is also shown for fixed randomness that the state of clusters transits from a stagnant phase to a growing one as the connection strength of clusters increases. This work can be useful for understanding the critical transition appearing in many dynamic processes on the cluster networks.

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Non-universal interspecific allometric scaling of metabolism

Cited by 5 publications

References 35 publications

Scaling of Metabolic Scaling within Physical Limits

Scaling of Metabolic Scaling within Physical Limits

A theoretical analysis of the growth process of an organism and its dependence on various allometric relations

Efficiency dynamics on two coupled small-world networks

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