Commentary: On the Interpretation of the Normalization Constant in the Scaling Equation

Glazier, Douglas S.

doi:10.3389/fevo.2020.00090

Cited by 5 publications

(12 citation statements)

References 22 publications

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“…The straight lines fitted to logarithms in Figure 2C were back‐transformed, and the resulting two‐parameter power functions were displayed with the original data on a bivariate plot (Figure 2D). The curves were extended to the axes to facilitate comparison of the functions, which would be expected by many investigators to follow parallel courses (Glazier, 2020; Niklas & Hammond, 2019). The curves actually follow very different trajectories despite the parallel trajectories that the equivalent functions follow in the logarithmic plot (Figure 2C).…”

Section: Methods and Resultsmentioning

confidence: 99%

“…The curves were extended to the axes to facilitate comparison of the functions, which would be expected by many investigators to follow parallel courses (Glazier, 2020;Niklas & Hammond, 2019). The curves actually follow very different trajectories despite the parallel trajectories that the equivalent functions follow in the logarithmic plot (Figure 2C).…”

Section: Horro Sheepmentioning

confidence: 99%

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Is relative growth by the mammalian heart biphasic or monophasic?

Packard

2020

Journal of Anatomy

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I re‐examined data for relative growth by the heart in four species of mammal to reconcile divergent reports that appear in the literature. Raw data for heart and body mass for Horro sheep, humans, gray kangaroos, and tammar wallabies were studied by linear and nonlinear regression, thereby enabling me to avoid the confounding effects of logarithmic transformation and to evaluate multiple statistical models for describing pattern in each set of observations. My analyses indicate that relative growth by the heart is monophasic in all four species and either isometric or near isometric on the arithmetic scale. The heart in these mammals consequently grows in mass in approximate proportion to growth in mass by the body. The appearance of biphasic allometric growth in prior studies was an artifact resulting from logarithmic transformation. Although parturition in sheep and humans is accompanied by a change in the distribution of blood out of the heart and into pulmonary and systemic circuits, the challenge is met without marked increases in absolute or relative size of the heart.

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Section: Methods and Resultsmentioning

confidence: 99%

Section: Horro Sheepmentioning

confidence: 99%

Is relative growth by the mammalian heart biphasic or monophasic?

Packard

2020

Journal of Anatomy

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“…Other scaling parameters, such as the intercept (log a) and 'scaling elevation level' (L) (see Glossary), defined as the massspecific value of a trait at the pivotal midpoint of a log-log regression (following the concept of 'metabolic level' used in studies of body-mass scaling relationships of metabolic rate by Glazier, 2009, 2010, 2020band Killen et al, 2010; see Glossary) may also be compared to specific causal factors. The antilog of the intercept in a log-log plot (a) is standardized to 1-unit mass, but its use is complicated by mathematical autocorrelation with the slope (b) (see Gould, 1966;Peters, 1983;McNab, 1988;Glazier, 2009Glazier, , 2010Glazier, , 2020bNiklas and Hammond, 2019). By contrast, although L is not autocorrelated with b, it depends on the midpoint body mass at which it is estimated (Glazier, 2009;2010;2020b).…”

Section: 'Synthetic Allometry' (Sa) Methodsmentioning

confidence: 99%

“…The antilog of the intercept in a log-log plot (a) is standardized to 1-unit mass, but its use is complicated by mathematical autocorrelation with the slope (b) (see Gould, 1966;Peters, 1983;McNab, 1988;Glazier, 2009Glazier, , 2010Glazier, , 2020bNiklas and Hammond, 2019). By contrast, although L is not autocorrelated with b, it depends on the midpoint body mass at which it is estimated (Glazier, 2009;2010;2020b). Comparison of L among scaling relationships is most useful when their midpoint masses are most similar.…”

Section: 'Synthetic Allometry' (Sa) Methodsmentioning

confidence: 99%

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Complications with body-size correction in comparative biology: possible solutions and an appeal for new approaches

Glazier

2022

Journal of Experimental Biology

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The magnitude of many kinds of biological traits relates strongly to body size. Therefore, a first step in comparative studies frequently involves correcting for effects of body size on the variation of a phenotypic trait, so that the effects of other biological and ecological factors can be clearly distinguished. However, commonly used traditional methods for making these body-size adjustments ignore or do not completely separate the causal interactive effects of body size and other factors on trait variation. Various intrinsic and extrinsic factors may affect not only the variation of a trait, but also its covariation with body size, thus making it difficult to remove completely the effect of body size in comparative studies. These complications are illustrated by several examples of how body size interacts with diverse developmental, physiological, behavioral and ecological factors to affect variation in metabolic rate both within and across species. Such causal interactions are revealed by significant effects of these factors on the body-mass scaling slope of metabolic rate. I discuss five possible major kinds of methods for removing body-size effects that attempt to overcome these complications, at least in part, but I hope that my Review will encourage the development of other, hopefully better methods for doing so.

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Can metabolic traits explain animal community assembly and functioning?

et al. 2022

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All animals on Earth compete for free energy, which is acquired, assimilated, and ultimately allocated to growth and reproduction. Competition is strongest within communities of sympatric, ecologically similar animals of roughly equal size (i.e. horizontal communities), which are often the focus of traditional community ecology. The replacement of taxonomic identities with functional traits has improved our ability to decipher the ecological dynamics that govern the assembly and functioning of animal communities. Yet, the use of low‐resolution and taxonomically idiosyncratic traits in animals may have hampered progress to date. An animal's metabolic rate (MR) determines the costs of basic organismal processes and activities, thus linking major aspects of the multifaceted constructs of ecological niches (where, when, and how energy is obtained) and ecological fitness (how much energy is accumulated and passed on to future generations). We review evidence from organismal physiology to large‐scale analyses across the tree of life to propose that MR gives rise to a group of meaningful functional traits – resting metabolic rate (RMR), maximum metabolic rate (MMR), and aerobic scope (AS) – that may permit an improved quantification of the energetic basis of species coexistence and, ultimately, the assembly and functioning of animal communities. Specifically, metabolic traits integrate across a variety of typical trait proxies for energy acquisition and allocation in animals (e.g. body size, diet, mobility, life history, habitat use), to yield a smaller suite of continuous quantities that: (1) can be precisely measured for individuals in a standardized fashion; and (2) apply to all animals regardless of their body plan, habitat, or taxonomic affiliation. While integrating metabolic traits into animal community ecology is neither a panacea to disentangling the nuanced effects of biological differences on animal community structure and functioning, nor without challenges, a small number of studies across different taxa suggest that MR may serve as a useful proxy for the energetic basis of competition in animals. Thus, the application of MR traits for animal communities can lead to a more general understanding of community assembly and functioning, enhance our ability to trace eco‐evolutionary dynamics from genotypes to phenotypes (and vice versa), and help predict the responses of animal communities to environmental change. While trait‐based ecology has improved our knowledge of animal communities to date, a more explicit energetic lens via the integration of metabolic traits may further strengthen the existing framework.

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Commentary: On the Interpretation of the Normalization Constant in the Scaling Equation

Cited by 5 publications

References 22 publications

Is relative growth by the mammalian heart biphasic or monophasic?

Is relative growth by the mammalian heart biphasic or monophasic?

Complications with body-size correction in comparative biology: possible solutions and an appeal for new approaches

Can metabolic traits explain animal community assembly and functioning?

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