A quantitative genetics perspective on the body-mass scaling of metabolic rate

Does death drive the scaling of life?

The magnitude of many kinds of biological structures and processes scale with organismal size, often in regular ways that can be described by power functions. Traditionally, many of these "biological scaling" relationships have been explained based on internal geometric, physical, and energetic constraints according to universal natural laws, such as the "surface law" and "3/4-power law". However, during the last three decades it has become increasingly apparent that biological scaling relationships vary greatly in response to various external (environmental) factors. In this review, I propose and provide several lines of evidence supporting a new ecological perspective that I call the "mortality theory of ecology" (MorTE). According to this viewpoint, mortality imposes time limits on the growth, development, and reproduction of organisms. Accordingly, small, vulnerable organisms subject to high mortality due to predation and other environmental hazards have evolved faster, shorter lives than larger, more protected organisms. A MorTE also includes various corollary, size-related internal and external causative factors (e.g. intraspecific resource competition, geometric surface area to volume effects on resource supply/transport and the protection of internal tissues from environmental hazards, internal homeostatic regulatory systems, incidence of pathogens and parasites, etc.) that impact the scaling of life. A mortality-centred approach successfully predicts the ranges of body-mass scaling slopes observed for many kinds of biological and ecological traits. Furthermore, I argue that mortality rate should be considered the ultimate (evolutionary) driver of the scaling of life, that is expressed in the context of other proximate (functional) drivers such as information-based biological regulation and spatial (geometric) and energetic (metabolic) constraints.

An allometry perspective on crops

Understanding trait-trait coordination is essential for successful plant breeding and crop modeling. Notably, plant size drives variation in morphological, physiological, and performance-related traits, as described by allometric laws in ecology. Yet, as allometric relationships have been limitedly studied in crops, how they influence and possibly limit crop performance remains unknown. Here, we review how an allometry perspective on crops gains insights into the phenotypic evolution during crop domestication, the breeding of varieties adapted to novel conditions, and the prediction of crop yields. As allometry is an active field of research, modeling and manipulating crop allometric relationships can help to develop more resilient and productive agricultural systems to face future challenges.

Modelling ASthma TrEatment Responses (MASTER): Effect of individual patient characteristics on the risk of exacerbation in moderate or severe asthma: A time-to-event analysis of randomized clinical trials

AIMS

There is limited understanding of how clinical and demographic characteristics are associated with exacerbation risk in patients with moderate-to-severe asthma, and how these factors correlate with symptom control and treatment response. Here we assess the relationship between baseline characteristics and exacerbation risk during regular dosing with inhaled corticosteroids (ICS) monotherapy or in combination with long-acting beta2-agonists (ICS/LABA) in clinical trial patients with varying levels of symptom control, as assessed by the asthma control questionnaire (ACQ-5).

METHODS

A time-to-event model was developed using pooled patient data (N = 16 282) from nine clinical studies [Correction added on 26 July 2023, after first online publication: The N value in the preceding sentence has been corrected in this version.]. A parametric hazard function was used to describe the time-to-first exacerbation. Covariate analysis included the assessment of the effect of seasonal variation, clinical and demographic baseline characteristics on baseline hazard. Predictive performance was evaluated by standard graphical and statistical methods.

RESULTS

An exponential hazard model best described the time-to-first exacerbation in moderate-to-severe asthma patients. Body mass index, smoking status, sex, ACQ-5, % predicted forced expiratory volume over 1 s (FEV1 p) and season were identified as statistically significant covariates affecting baseline hazard irrespective of ICS or ICS/LABA use. Fluticasone propionate/salmeterol (FP/SAL) combination therapy resulted in a significant reduction in the baseline hazard (30.8%) relative to FP monotherapy.

CONCLUSIONS

Interindividual differences at baseline and seasonal variation affect the exacerbation risk independently from drug treatment. Moreover, it appears that even when a comparable level of symptom control is achieved in a group of patients, each individual may have a different exacerbation risk, depending on their baseline characteristics and time of the year. These findings highlight the importance of personalized interventions in moderate-to-severe asthma patients.

Spatial variation in the evolutionary potential and constraints of basal metabolic rate and body mass in a wild bird

An organism's energy budget is strongly related to resource consumption, performance, and fitness. Hence, understanding the evolution of key energetic traits, such as basal metabolic rate (BMR), in natural populations is central for understanding life-history evolution and ecological processes. Here we used quantitative genetic analyses to study evolutionary potential of BMR in two insular populations of the house sparrow (Passer domesticus). We obtained measurements of BMR and body mass (M_b ) from 911 house sparrows on the islands of Leka and Vega along the coast of Norway. These two populations were the source populations for translocations to create an additional third, admixed 'common garden' population in 2012. With the use of a novel genetic group animal model concomitant with a genetically determined pedigree, we differentiate genetic and environmental sources of variation, thereby providing insight into the effects of spatial population structure on evolutionary potential. We found that the evolutionary potential of BMR was similar in the two source populations, whereas the Vega population had a somewhat higher evolutionary potential of M_b than the Leka population. BMR was genetically correlated with M_b in both populations, and the conditional evolutionary potential of BMR (independent of body mass) was 41% (Leka) and 53% (Vega) lower than unconditional estimates. Overall, our results show that there is potential for BMR to evolve independently of M_b , but that selection on BMR and/or M_b may have different evolutionary consequences in different populations of the same species.

Variable metabolic scaling breaks the law: from 'Newtonian' to 'Darwinian' approaches

Life's size and tempo are intimately linked. The rate of metabolism varies with body mass in remarkably regular ways that can often be described by a simple power function, where the scaling exponent (b, slope in a log-linear plot) is typically less than 1. Traditional theory based on physical constraints has assumed that b is 2/3 or 3/4, following natural law, but hundreds of studies have documented extensive, systematic variation in b. This overwhelming, law-breaking, empirical evidence is causing a paradigm shift in metabolic scaling theory and methodology from ‘Newtonian’ to ‘Darwinian’ approaches. A new wave of studies focuses on the adaptable regulation and evolution of metabolic scaling, as influenced by diverse intrinsic and extrinsic factors, according to multiple context-dependent mechanisms, and within boundary limits set by physical constraints.

Can Sex-Specific Metabolic Rates Provide Insight Into Patterns of Metabolic Scaling?

Females and males can exhibit striking differences in body size, relative trait size, physiology and behavior. As a consequence the sexes can have very different rates of whole-body energy use, or converge on similar rates through different physiological mechanisms. Yet many studies that measure the relationship between metabolic rate and body size only pay attention to a single sex (more often males), or do not distinguish between sexes. We present four reasons why explicit attention to energy-use between the sexes can yield insight into the physiological mechanisms that shape broader patterns of metabolic scaling in nature. First, the sexes often differ considerably in their relative investment in reproduction which shapes much of life-history and rates of energy use. Second, males and females share a majority of their genome but may experience different selective pressures. Sex-specific energy profiles can reveal how the energetic needs of individuals are met despite the challenge of within-species genetic constraints. Third, sexual selection often pushes growth and behavior to physiological extremes. Exaggerated sexually selected traits are often most prominent in one sex, can comprise up to 50% of body mass and thus provide opportunities to uncover energetic constraints of trait growth and maintenance. Finally, sex-differences in behavior such as mating-displays, long-distance dispersal and courtship can lead to drastically different energy allocation among the sexes; the physiology to support this behavior can shape patterns of metabolic scaling. The mechanisms underlying metabolic scaling in females, males and hermaphroditic animals can provide opportunities to develop testable predictions that enhance our understanding of energetic scaling patterns in nature.