How and Why Does Metabolism Scale with Body Mass?

Most explanations for the relationship between body size and metabolism invoke physical constraints; such explanations are evolutionarily inert, limiting their predictive capacity. Contemporary approaches to metabolic rate and life history lack the pluralism of foundational work. Here, we call for reforging of the lost links between optimization approaches and physiology.

Allometric scaling of metabolic rate and cardiorespiratory variables in aquatic and terrestrial mammals

While basal metabolic rate (BMR) scales proportionally with body mass (Mb ), it remains unclear whether the relationship differs between mammals from aquatic and terrestrial habitats. We hypothesized that differences in BMR allometry would be reflected in similar differences in scaling of O2 delivery pathways through the cardiorespiratory system. We performed a comparative analysis of BMR across 63 mammalian species (20 aquatic, 43 terrestrial) with a Mb range from 10 kg to 5318 kg. Our results revealed elevated BMRs in small (>10 kg and <100 kg) aquatic mammals compared to small terrestrial mammals. The results demonstrated that minute ventilation, that is, tidal volume (VT )·breathing frequency (fR ), as well as cardiac output, that is, stroke volume·heart rate, do not differ between the two habitats. We found that the "aquatic breathing strategy", characterized by higher VT and lower fR resulting in a more effective gas exchange, and by elevated blood hemoglobin concentrations resulting in a higher volume of O2 for the same volume of blood, supported elevated metabolic requirements in aquatic mammals. The results from this study provide a possible explanation of how differences in gas exchange may serve energy demands in aquatic versus terrestrial mammals.

Metabolic rate and climate change across latitudes: evidence of mass-dependent responses in aquatic amphipods

Predictions of individual responses to climate change are often based on the assumption that temperature affects the metabolism of individuals independently of their body mass. However, empirical evidence indicates that interactive effects exist. Here, we investigated the response of individual standard metabolic rate (SMR) to annual temperature range and forecasted temperature rises of 0.6-1.2°C above the current maxima, under the conservative climate change scenario IPCC RCP2.6. As a model organism, we used the amphipod Gammarus insensibilis, collected across latitudes along the western coast of the Adriatic Sea down to the southernmost limit of the species' distributional range, with individuals varying in body mass (0.4-13.57 mg). Overall, we found that the effect of temperature on SMR is mass dependent. Within the annual temperature range, the mass-specific SMR of small/young individuals increased with temperature at a greater rate (activation energy: E=0.48 eV) than large/old individuals (E=0.29 eV), with a higher metabolic level for high-latitude than low-latitude populations. However, under the forecasted climate conditions, the mass-specific SMR of large individuals responded differently across latitudes. Unlike the higher-latitude population, whose mass-specific SMR increased in response to the forecasted climate change across all size classes, in the lower-latitude populations, this increase was not seen in large individuals. The larger/older conspecifics at lower latitudes could therefore be the first to experience the negative impacts of warming on metabolism-related processes. Although the ecological collapse of such a basic trophic level (aquatic amphipods) owing to climate change would have profound consequences for population ecology, the risk is significantly mitigated by phenotypic and genotypic adaptation.

Glucose tolerance predicts survival in old zebra finches

The capacity to deal with external and internal challenges is thought to affect fitness, and the age-linked impairment of this capacity defines the ageing process. Using a recently developed intra-peritoneal glucose tolerance test (GTT) in zebra finches, we tested for a link between the capacity to regulate glucose levels and survival. We also investigated for the effects of ambient factors, age, sex, and manipulated developmental and adult conditions (i.e. natal brood size and foraging cost, in a full factorial design) on glucose tolerance. Glucose tolerance was quantified using the incremental ‘area under the curve’ (AUC), with lower values indicating higher tolerance. Glucose tolerance predicted survival probability in old birds, above the median age, with individuals with higher glucose tolerance showing better survival than individuals with low or intermediate glucose tolerance. In young birds there was no association between glucose tolerance and survival. Experimentally induced adverse developmental conditions did not affect glucose tolerance, but low ambient temperature at sampling and hard foraging conditions during adulthood induced a fast return to baseline levels (i.e. high glucose tolerance). These findings can be interpreted as an efficient return to baseline glucose levels when energy requirements are high, with glucose presumably being used for energy metabolism or storage. Glucose tolerance was independent of sex. Our main finding that old birds with higher glucose tolerance had better survival supports the hypothesis that the capacity to efficiently cope with a physiological challenge predicts lifespan, at least in old birds.

Housing conditions modify seasonal changes in basal metabolism and body mass of the Siberian hamster, Phodopus sungorus

Proper housing conditions are important aspects of animal welfare. Animals housed in enriched environments show less stereotypic behaviours than animals kept in barren cages. However, different types of cage enrichment may affect the results of experimental studies and hinder comparative analyses of animal physiology and behaviour. We investigated whether access to a running wheel, availability of nesting material, and pair housing affect basal metabolic rate (BMR) of Siberian hamsters (Phodopus sungorus) under various acclimation conditions. We used 70 adult hamsters (35 males and 35 females) divided into five groups housed under different cage conditions. All individuals experienced the same acclimation procedure: first a winter (L8:D16) then a summer (L16:D8) photoperiod, at air temperatures of first 20 °C then 7 °C under both photoperiods. We found that nesting material and pair housing did not affect hamster BMR, while access to a running wheel increased BMR and body mass regardless of photoperiod and ambient temperature. Thus, we suggest that cage enrichment should be applied with caution, especially in studies on energetics or thermoregulation, particularly in seasonal animals.

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

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.

Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g., wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health, leading to the goal of precise phenotypic correlates for genotypes. Even though treatments and interventions are becoming more specific and datasets more abundant, measuring the causal impact of health interventions requires careful considerations of complex covariate structures, as well as knowledge of the temporal and spatial properties of the data. Thus, interpreting biomedical sensor data needs to make use of specialized statistical models. Here, we show how the Bayesian structural time series framework, widely used in economics, can be applied to these data. This framework corrects for covariates to provide accurate assessments of the significance of interventions. Furthermore, it allows for a time-dependent confidence interval of impact, which is useful for considering individualized assessments of intervention efficacy. We provide a customized biomedical adaptor tool, MhealthCI, around a specific implementation of the Bayesian structural time series framework that uniformly processes, prepares, and registers diverse biomedical data. We apply the software implementation of MhealthCI to a structured set of examples in biomedicine to showcase the ability of the framework to evaluate interventions with varying levels of data richness and covariate complexity and also compare the performance to other models. Specifically, we show how the framework is able to evaluate an exercise intervention’s effect on stabilizing blood glucose in a diabetes dataset. We also provide a future-anticipating illustration from a behavioral dataset showcasing how the framework integrates complex spatial covariates. Overall, we show the robustness of the Bayesian structural time series framework when applied to biomedical sensor data, highlighting its increasing value for current and future datasets.

In this paper, we propose and describe a robust and flexible modeling framework called MhealthCI based on the Bayesian structural time series, for which we have found to excel at analyzing diverse biosensor data. While Bayesian modeling is often employed in various fields such as finance, marketing, and weather forecasting, it is rarely used in biomedicine, specifically for biosensor and wearable data relating to human health and behavior. We use and apply this framework with the goal of interpreting and quantifying the causal impact of an intervention, a widespread goal of biomedicine. We describe the diversity of data types to which it could apply, provide intuition to its mechanics, collect relevant data in various fields, provide a wrapper tool around well-known R packages that prepares and registers diverse biosensor data to be analyzed, and finally apply the method to showcase its strength in quantifying the impact of interventions.

Energetic constraints on mammalian distribution areas

Energy is a universal resource essential for all life functions. The rate of transformation of energy into an organism, and the energetic investment into reproduction, determines population and ecological-level processes. Several hypotheses predicted that the ecological expansion and size of the geographic distribution of a species are shaped by, among other factors, metabolic performance. However, how organismal energetic characteristics contribute to species geographic range size is poorly understood. With phylogenetic comparative methods whether energetic maintenance costs (basal metabolic rate, BMR), aerobic capacity (maximum exercise metabolic rate, VO₂ max), summit thermoregulation (summit metabolic rate, VO₂ sum) and the ability to sustain energy provisioning (daily energy expenditure, DEE) determine the distribution of mammalian species range sizes was tested. Both basal and maximum exercise metabolic rates (accounting for body mass), but not summit thermogenic metabolic rate, were positively associated with species range sizes. Furthermore, daily energy expenditure (accounting for body mass) was positively associated with species ranges. Body mass (accounting for energetic maintenance) was negatively related to range sizes. High aerobic exercise capacity, aiding mobility such as running and dispersal, and high sustained energy provisioning, aiding reproductive effort such as pregnancy, lactation and natal dispersal, can facilitate the establishment of large mammalian geographic ranges. Consequently, the pace of organismal physiological processes can shape important ecological and biodiversity patterns by setting limits to species' range sizes.

Metabolic and behavioral adaptations of greater white-toothed shrews to urban conditions

The global trend of urbanization is creating novel challenges for many animal species. Studies investigating behavioral differences between rural and urban populations often report a general increase in risk-taking behaviors in urban populations. According to the most common energy management model (the performance model), behaviors that increase access to resources, such as aggression and boldness, and behaviors that consume net energy, like locomotion and stress responses, are both positively correlated to resting metabolic rate (RMR). Thus, we expect urban populations to not only exhibit a higher level of risk-taking behavior but also a higher RMR. However, these interactions remain poorly investigated. Our main goal was to analyze the relationship between RMR and risk-taking behaviors in the greater white-toothed shrew (Crocidura russula) in rural versus urban populations. Trapped shrews were brought to captivity where we measured RMR, boldness, and exploration rate three times in each individual. Our findings revealed that urban shrews were indeed bolder and more exploratory, but contrary to our expectations, their RMR was lower than that of rural shrews. This is likely explained by differences in the environmental conditions of these two habitats, such as higher ambient temperatures and/or lower prey availability in cities. When looking at each population separately, this relationship remained similar: urban shrews with a higher RMR were less bold, and rural shrews with a higher RMR showed a lower exploration rate. We conclude that the energetic strategy of C. russula is dependent on the environmental and observational context and cannot be explained by the performance model.

Climate Change and Thermoregulatory Consequences of Activity Time in Mammals

Activity times structure the thermal environments experienced by organisms. In mammals, species shift from being nocturnal to diurnal and vice versa, but the thermal consequences of variable activity patterns remain largely unexplored. Here we used theoretical thermoregulatory polygons bounded by estimates of basal metabolic rates (BMR), maximum metabolic rates (MMR), and thermal conductance (C) in small mammals to explore the metabolic consequences of exposure to global-scale daytime and nighttime temperatures. Model predictions indicated higher metabolic scope for activity for nocturnal species at low latitudes and that reduced minimum C and larger body size increased the geographic range in which nocturnality was advantageous. Consistent with predictions, within rodents nocturnal species have low C. However, nocturnal mammals tend to be smaller than diurnal species, likely reflecting the importance of additional factors driving body size. Projections of warming impacts on small mammals suggest that diurnal species could lose habitable space globally. Conversely, warming could lift cool temperature constraints on nocturnal species and increase habitable space, suggesting that a shift toward nocturnal niches might be favored in a warming world. Taken together, these findings demonstrate the importance of energetic considerations for endotherms in managing global change impacts on nocturnal and diurnal species.

The decoupled nature of basal metabolic rate and body temperature in endotherm evolution

The origins of endothermy in birds and mammals are important events in vertebrate evolution. Endotherms can maintain their body temperature (T_b) over a wide range of ambient temperatures primarily using the heat that is generated continuously by their high basal metabolic rate (BMR)¹. There is also an important positive feedback loop as T_b influences BMR^1-3. Owing to this interplay between BMRs and T_b, many ecologists and evolutionary physiologists posit that the evolution of BMR and T_b must have been coupled during the radiation of endotherms^3-5, changing with similar trends^6-8. However, colder historical environments might have imposed strong selective pressures on BMR to compensate for increased rates of heat loss and to keep T_b constant^9-12. Thus, adaptation to cold ambient temperatures through increases in BMR could have decoupled BMR from T_b and caused different evolutionary routes to the modern diversity in these traits. Here we show that BMR and T_b were decoupled in approximately 90% of mammalian phylogenetic branches and 36% of avian phylogenetic branches. Mammalian BMRs evolved with rapid bursts but without a long-term directional trend, whereas T_b evolved mostly at a constant rate and towards colder bodies from a warmer-bodied common ancestor. Avian BMRs evolved predominantly at a constant rate and without a long-term directional trend, whereas T_b evolved with much greater rate heterogeneity and with adaptive evolution towards colder bodies. Furthermore, rapid shifts that lead to both increases and decreases in BMRs were linked to abrupt changes towards colder ambient temperatures-although only in mammals. Our results suggest that natural selection effectively exploited the diversity in mammalian BMRs under diverse, often-adverse historical thermal environments.