Metabolic Scaling Research Articles

Tallo: A global tree allometry and crown architecture database.

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non‐forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC‐BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

Abstract 481: Biophysical models of pattern formation in bone marrow endothelial networks

Abstract In this work we aim to understand how cellular aggregation and angiogenic pattern formation develop in bone marrow endothelial networks by integrating spatial-temporal mathematical models with theory regarding how cellular metabolism scales with cell number. Presently, efforts to model angiogenic pattern formation fail to accurately predict spatial characteristics often observed. Biological allometries, such as the scaling of metabolism to mass or cell number, have been hypothesized to result from natural selection to maximize how vascular networks fill space yet minimize internal transport distances and resistance to motion. Metabolic scaling theory argues that two guiding principles—optimization of motion and space-filling fractal distributions—describe a diversity of biological networks and predict how the geometry of these networks influences organismal metabolism. Recently, metabolic scaling theory has been applied to study tumor growth rates, offering a mechanistic link between tumor growth and vascular patterning. Remarkably, there exists two classes of spatial-temporal mathematical models where equivalent angiogenic pattern formation occurs. These two classes are determined primarily by either cellular interactions as proposed by Hillen and Painter, or biomechanical forces as proposed by Manoussaki and Murray. Examples of underlying mechanisms are chemotactic quorum-sensing and resource competition for the former, and advection-diffusion driven stresses and strains in the extra-cellular matrix for the latter. We compare these models by examining theoretical predictions for pattern forming criteria with numerical simulations. Furthermore, we identify experimentally testable predictions for angiogenic pattern formation related to the spatial configuration of the extra-cellular matrix. We test these predictions against in vitro confocal microscopy imaging data for bone marrow endothelial networks with experimental control over adhesion molecules and the resulting network structure. Specifically, we measure time-dependent geometric features in the highly reticulated endothelial networks related to steady-state equilibration, connectivity and space-filling. Example metrics are the scaling of network edge lengths and enclosed areas within the extra-cellular matrix that indicate changes to network morphology as adhesion molecules are present or absent. These metrics are informed by metabolic scaling theory and are predicted by the steady-state solutions of the underlying models. By conducting metric and model selection, this work identifies data-driven mechanisms for angiogenic pattern formation and quantifies normality in bone-marrow endothelial networks. This is an essential step for future work in quantifying and understanding abnormality in bone marrow endothelial networks. Citation Format: Alexander B. Brummer, Young-Woong Kim, Nadia Carlesso, Russell C. Rockne. Biophysical models of pattern formation in bone marrow endothelial networks [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 481.

Factors affecting gestation periods in elasmobranch fishes.

ABSTRACTGestation periods vary greatly across elasmobranch species. Differences in body size and body temperature (i.e. major determinants of metabolic rates) might explain such variation. Although temperature effects have been demonstrated for captive animals, body size effects remain undocumented. Moreover, whether metabolic rates of mothers or those of embryos affect gestation periods remains unclear. Because biological times generally scale with mass1−β, where β is metabolic scaling exponent (0.8–0.9 in fishes), we hypothesized that elasmobranch gestation periods would scale with mass0.1–0.2. We also hypothesized that regionally endothermic species with elevated metabolic rates should have shorter gestation periods than similar-sized ectothermic species if the metabolic rates of mothers are responsible. We compiled data on gestation periods for 36 elasmobranch species to show that gestation periods scale with M0.11 and m0.17, where M and m are adult female mass and birth mass, respectively. Litter size and body temperature also affected gestation periods. Our findings suggest that the body-mass dependence of metabolic rate explains some variations in elasmobranch gestation periods. Unexpectedly, regionally endothermic sharks did not have shorter gestation periods than their ectothermic counterparts, suggesting that the metabolic rates of embryos, which are likely ectothermic in all elasmobranch species, may be responsible. This article has an associated First Person interview with the first author of the paper.

Ontogenetic Changes in Body Shape and the Scaling of Metabolic Rate in the American Eel (Anguilla rostrata).

AbstractThe body mass (M) scaling of resting metabolic rate (RMR) may vary significantly throughout ontogeny for multiple reasons that are not perfectly understood. To compare two major geometric theories of metabolic scaling, surface area (SA) theory and resource transport network (RTN) theory, we tested whether ontogenetic shifts in metabolic scaling relate to changes in body shape in the American eel (Anguilla rostrata). To do so, we compared the log-linear scaling exponents of RMR to M (bR) and M to body length (bL) in juvenile and subadult eels (glass and yellow eel life stages, respectively). Glass eels exhibited a and bR significantly <2/3, as predicted by SA theory. Yellow eels also had a , but their bR was not significantly different from 2/3 or 3/4. We hypothesize that two developmental changes contribute to bR being higher for yellow eels: (1) a greater reliance on branchial respiration than body-surface-dependent cutaneous respiration and (2) a lower rate of thickening during subadult growth. An ontogenetic decrease in the ratio of cutaneous to gill respiration may have increased the relative importance of the physical constraints of a single-pump, closed circulatory system on the body-size-dependent rate of resource supply to metabolizing tissues (as predicted by RTN theory) in subadult eels. Future research is needed to quantify these developmental changes and their potential mechanistic effects on metabolic scaling, especially in the elver, a critical life stage between the glass and yellow eel stages, that was not analyzed in this study.

The Evolution of Offspring Size: a Metabolic Scaling Perspective.

Size at the start of life reflects the initial per offspring parental investment - including both the embryo and the nutrients supplied to it. Initial offspring size can vary substantially both within and among species. Within species, increasing offspring size can enhance growth, reproduction, competitive ability, and reduce susceptibility to predation and starvation later in life, that can ultimately increase fitness. Previous work has suggested that the fitness benefits of larger offspring size may be driven by energy expenditure during development - or how offspring metabolic rate scales with offspring size. Despite the importance of early life energy expenditure in shaping later life fitness trajectories, consideration of among-species scaling of metabolic rate at the time of birth as a potential source of general metabolic scaling patterns has been overlooked by theory. Here we review the patterns and processes of energy expenditure at the start of life when mortality is often greatest. We compile existing data on metabolic rate and offspring size for 191 ectotherm species spanning eight phyla and use phylogenetically-controlled methods to quantify among-species scaling patterns. Across a 109-fold mass range, we find that offspring metabolic rate scales hypometrically with size, with an overall scaling exponent of 0.66. This exponent varies across ontogenetic stage and feeding activity, but is consistently hypometric, including across environmental temperatures. Despite differences in parental investment, life history and habitat, large-offspring species use relatively less energy as a proportion of size, compared with small-offspring species. Greater residual energy can be used to fuel the next stages of life, particularly in low resource environments. Based on available evidence, we conclude that, while large knowledge gaps remain, the evolution of offspring size is likely shaped by context-dependent selection acting on correlated traits, including metabolic rates maintaining hypometric scaling, that operates within broader physical constraints.

Declining metabolic scaling parallels an ontogenetic change from elongate to deep-bodied shapes in juvenile Brown trout.

Body shape and metabolic rate can be important determinants of animal performance, yet often their effects on influential traits are evaluated in a non-integrated way. This creates an important gap because the integration between shape and metabolism may be crucial to evaluate metabolic scaling theories. Here, we measured standard metabolic rate in 1- and 2-years old juvenile brown trout Salmo trutta, and used a geometric morphometrics approach to extricate the effects of ontogeny and size on the link between shape and metabolic scaling. We evidenced near-isometric ontogenetic scaling of metabolic rate with size, but also a biphasic pattern driven by a significant change in metabolic scaling, from positive to negative allometry. Moreover, the change in metabolic allometry parallels an ontogenetic change from elongate to deep-bodied shapes. This is consistent with the dynamic energy budget (DEB) and surface area (SA) theories, but not with the resource transport network theory which predicts increasing allometric exponents for trends towards more robust, three-dimensional bodies. In addition, we found a relationship between body shape and size independent metabolic rate, with a positive correlation between robustness and metabolic rate, which fits well within the view of Pace-of-Life Syndromes (POLS). Finally, our results align with previous studies that question the universality of metabolic scaling exponents and propose other mechanistic models explaining the diversity of metabolic scaling relationships or emphasizing the potential contribution of ecological factors.

Social Brain Energetics: Ergonomic Efficiency, Neurometabolic Scaling, and Metabolic Polyphenism in Ants.

Metabolism, a metric of the energy cost of behavior, plays a significant role in social evolution. Body size and metabolic scaling are coupled, and a socioecological pattern of increased body size is associated with dietary change and the formation of larger and more complex groups. These consequences of the adaptive radiation of animal societies beg questions concerning energy expenses, a substantial portion of which may involve the metabolic rates of brains that process social information. Brain size scales with body size, but little is understood about brain metabolic scaling. Social insects such as ants show wide variation in worker body size and morphology that correlates with brain size, structure, and worker task performance, which is dependent on sensory inputs and information-processing ability to generate behavior. Elevated production and maintenance costs in workers may impose energetic constraints on body size and brain size that are reflected in patterns of metabolic scaling. Models of brain evolution do not clearly predict patterns of brain metabolic scaling, nor do they specify its relationship to task performance and worker ergonomic efficiency, two key elements of social evolution in ants. Brain metabolic rate is rarely recorded and therefore the conditions under which brain metabolism influences the evolution of brain size are unclear. We propose that studies of morphological evolution, colony social organization, and worker ergonomic efficiency should be integrated with analyses of species-specific patterns of brain metabolic scaling to advance our understanding of brain evolution in ants.

Racing Time: Physiological Rates and Metabolic Scaling in Marine Mammals.

Reinvasion of the oceans beginning 10-60 million years ago by ancient mammals instigated one of the most remarkable metabolic transitions across evolutionary time. A consequence of marine living, especially in colder waters, has been a 1.4 to 2.9-fold increase in resting metabolic rate (RMR) for otters, pinnipeds and cetaceans over predicted levels for terrestrial mammals of similar body mass. Notably, the greatest metabolic elevation occurred in the smallest marine mammals, suggesting an underlying thermal causative mechanism. Superimposed on these resting costs are the metabolic demands of locomotion. Collectively termed the field metabolic rate, such active costs consistently approach three times the resting rates of individuals regardless of locomotor style, species, foraging patterns, habitat or geographic location. In wild non-reproducing mammals, the FMR/RMR ratio averages 2.6-2.8 for both terrestrial and marine species, with the latter group maintaining larger absolute daily metabolic rates supported by comparatively higher food ingestion rates. Interestingly, the limit for habitual (multi-day), sustained maximal energy expenditure in human endurance athletes averages<3.0 times resting metabolic levels, with a notable exception in Tour de France cyclists. Importantly, both athletes and wild mammals seem similarly constrained; that is, by the ability to process enough calories in a day to support exceptional metabolic performance.

Long-term experimental evolution decouples size and production costs in Escherichia coli

Body size covaries with population dynamics across life’s domains. Metabolism may impose fundamental constraints on the coevolution of size and demography, but experimental tests of the causal links remain elusive. We leverage a 60,000-generation experiment in which Escherichia coli populations evolved larger cells to examine intraspecific metabolic scaling and correlations with demographic parameters. Over the course of their evolution, the cells have roughly doubled in size relative to their ancestors. These larger cells have metabolic rates that are absolutely higher, but relative to their size, they are lower. Metabolic theory successfully predicted the relations between size, metabolism, and maximum population density, including support for Damuth’s law of energy equivalence, such that populations of larger cells achieved lower maximum densities but higher maximum biomasses than populations of smaller cells. The scaling of metabolism with cell size thus predicted the scaling of size with maximum population density. In stark contrast to standard theory, however, populations of larger cells grew faster than those of smaller cells, contradicting the fundamental and intuitive assumption that the costs of building new individuals should scale directly with their size. The finding that the costs of production can be decoupled from size necessitates a reevaluation of the evolutionary drivers and ecological consequences of biological size more generally.

Growth and Mortality as Causes of Variation in Metabolic Scaling Among Taxa and Taxonomic Levels.

Metabolic rate (MR) usually changes (scales) out of proportion to body mass (BM) as MR=aBMb, where a is a normalisation constant and b is the scaling exponent that reflects how steep this change is. This scaling relationship is fundamental to biology, but over a century of research has provided little consensus on the value of b, and why it appears to vary among taxa and taxonomic levels. By analysing published data on fish and taking an individual-based approach to metabolic scaling, I show that variation in growth of fish under naturally restricted food availability can explain variation in within-individual (ontogenetic) b for standard (maintenance) metabolic rate (SMR) of brown trout (Salmo trutta), with the fastest growers having the steepest metabolic scaling (b≈1). Moreover, I show that within-individual b can vary much more widely than previously assumed from work on different individuals or different species, from -1 to 1 for SMR among individual brown trout. The negative scaling of SMR for some individuals was caused by reductions in metabolic rate in a food limited environment, likely to maintain positive growth. This resulted in a mean within-individual b for SMR that was significantly lower than the across-individual ("static") b, a difference that also existed for another species, cunner (Tautogolabrus adspersus). Interestingly, the wide variation in ontogenetic b for SMR among individual brown trout did not exist for maximum (active) metabolic rate (MMR) of the same fish, showing that these two key metabolic traits (SMR and MMR) can scale independently of one another. I also show that across-species ("evolutionary") b for SMR of 134 fishes is significantly steeper (b approaching 1) than the mean ontogenetic b for the brown trout and cunner. Based on these interesting findings, I hypothesise that evolutionary and static metabolic scaling can be systematically different from ontogenetic scaling, and that the steeper evolutionary than ontogenetic scaling for fishes arises as a by-product of natural selection for fast-growing individuals with steep metabolic scaling (b≈1) early in life, where size-selective mortality is high for fishes. I support this by showing that b for SMR tends to increase with natural mortality rates of fish larvae within taxa.

Metabolic shifts of oceans: Summoning bacterial interactions

Metabolic scaling can pinpoint monitoring priorities for anomalous communities and inform local eco-engineering restoration enhancing ecosystem function. We discovered an entropic Kleiber’s Law between bacterioplankton phylum total directed interactions and population and community abundane, with an average exponent Φ≃23 in striking accordance with theoretical expectations. The taxa-independent allometric relationship largely varies by habitat (shifting from 2/3 to 3/4 as power-exponent) and is better explained by the community abundance spectrum and its organization than by the envirome defined by environmental interactions. Yet, greater envirome disorganization meant higher environmental impacts causing larger bacteriome disorganization toward random interaction topologies and higher Kleiber’s Law exponents. Habitat-related bacteriome differences revealed that keystone phyla were highly interacting and rare (like Acidobacteria, SBR1093, and ZB3) maintaining weak but salient interactions with both rare (like Spirochaetes and Firmicutes) and dominant phyla. Consistent with their small divergence from main Kleiber’s law and abundance spectrum patterns cosmopolitan phyla, like Bacteroidetes and Proteobacteria, were dominant but weakly interacting (in magnitude) emphasizing the importance of weak ties in collective dynamics. The most salient interactions were always between phyla with high and low node centrality defined by their total directed interactions and abundance. Envirome network centrality shows temperature and nutrient concentrations (total and dissolved organic phosphorus) as central in estuarine habitats impacted by both global ocean factors and near-shore river effluxes; salinity and suspended particle matter were central in more off-shore habitats. Our results emphasize the importance of a probabilistic assessment of community interactions over individual bacterial abundance analyses when searching for collective patterns informative of ecosystem state and their environmental determinants.

Reshaping the Gut Microbiota Through Lifestyle Interventions in Women with PCOS: A Review.

Polycystic ovary syndrome (PCOS) is an endocrine disorder evolving as a global threat to women's health. However, its multifactorial etiology causes difficulty in eliminating it. The interrelation between the gut microbiota and metabolic disorders has been trending recently, giving rise to new opportunities on the etiology and pathogenesis of PCOS. Lifestyle interventions such as healthy diet, physical exercises, and behavioral interventions such as regulation of stress and sleep cycles have been identified to improve the symptoms of PCOS across the endocrinological, metabolic and psychological scales and are recommended as the first line of treatment for PCOS. The impact of the unhealthy lifestyle factors on intestinal dysbiosis that cause PCOS is summarized in this review. This review also provides an insight on the therapeutic approaches that primarily target the gut microbiota and offers novel gut microflora-associated treatment strategies for PCOS. Further, this survey also highlights the need for the implementation of lifestyle management strategies and strongly recommends a healthy and stress-free lifestyle to promote gut health and manage PCOS.

Comparison of absorbed dose extrapolation methods for mouse-to-human translation of radiolabelled macromolecules

BackgroundExtrapolation of human absorbed doses (ADs) from biodistribution experiments on laboratory animals is used to predict the efficacy and toxicity profiles of new radiopharmaceuticals. Comparative studies between available animal-to-human dosimetry extrapolation methods are missing. We compared five computational methods for mice-to-human AD extrapolations, using two different radiopharmaceuticals, namely [111In]CHX-DTPA-scFv78-Fc and [68Ga]NODAGA-RGDyK. Human organ-specific time-integrated activity coefficients (TIACs) were derived from biodistribution studies previously conducted in our centre. The five computational methods adopted are based on simple direct application of mice TIACs to human organs (M1), relative mass scaling (M2), metabolic time scaling (M3), combined mass and time scaling (M4), and organ-specific allometric scaling (M5), respectively. For [68Ga]NODAGA-RGDyK, these methods for mice-to-human extrapolations were tested against the ADs obtained on patients, previously published by our group. Lastly, an average [68Ga]NODAGA-RGDyK-specific allometric parameter αnew was calculated from the organ-specific biological half-lives in mouse and humans and retrospectively applied to M3 and M4 to assess differences in human AD predictions with the α = 0.25 recommended by previous studies.ResultsFor both radiopharmaceuticals, the five extrapolation methods showed significantly different AD results (p < 0.0001). In general, organ ADs obtained with M3 were higher than those obtained with the other methods. For [68Ga]NODAGA-RGDyK, no significant differences were found between ADs calculated with M3 and those obtained directly on human subjects (H) (p = 0.99; average M3/H AD ratio = 1.03). All other methods for dose extrapolations resulted in ADs significantly different from those calculated directly on humans (all p ≤ 0.0001). Organ-specific allometric parameters calculated using combined experimental [68Ga]NODAGA-RGDyK mice and human biodistribution data varied significantly. ADs calculated with M3 and M4 after the application of αnew = 0.17 were significantly different from those obtained by the application of α = 0.25 (both p < 0.001).ConclusionsAvailable methods for mouse-to-human dosimetry extrapolations provided significantly different results in two different experimental models. For [68Ga]NODAGA-RGDyK, the best approximation of human dosimetry was shown by M3, applying a metabolic scaling to the mouse organ TIACs. The accuracy of more refined extrapolation algorithms adopting model-specific metabolic scaling parameters should be further investigated.

Multigenerational exposure to increased temperature reduces metabolic rate but increases boldness in Gambusia affinis.

Acute exposure to warming temperatures increases minimum energetic requirements in ectotherms. However, over and within multiple generations, increased temperatures may cause plastic and evolved changes that modify the temperature sensitivity of energy demand and alter individual behaviors. Here, we aimed to test whether populations recently exposed to geothermally elevated temperatures express an altered temperature sensitivity of metabolism and behavior. We expected that long‐term exposure to warming would moderate metabolic rate, reducing the temperature sensitivity of metabolism, with concomitant reductions in boldness and activity. We compared the temperature sensitivity of metabolic rate (acclimation at 20 vs. 30°C) and allometric slopes of routine, standard, and maximum metabolic rates, in addition to boldness and activity behaviors, across eight recently divergent populations of a widespread fish species (Gambusia affinis). Our data reveal that warm‐source populations express a reduced temperature sensitivity of metabolism, with relatively high metabolic rates at cool acclimation temperatures and relatively low metabolic rates at warm acclimation temperatures compared to ambient‐source populations. Allometric scaling of metabolism did not differ with thermal history. Across individuals from all populations combined, higher metabolic rates were associated with higher activity rates at 20°C and bolder behavior at 30°C. However, warm‐source populations displayed relatively bolder behavior at both acclimation temperatures compared to ambient‐source populations, despite their relatively low metabolic rates at warm acclimation temperatures. Overall, our data suggest that in response to warming, multigenerational exposure (e.g., plasticity, adaptation) may not result in trait change directed along a simple “pace‐of‐life syndrome” axis, instead causing relative decreases in metabolism and increases in boldness. Ultimately, our data suggest that multigenerational warming may produce a novel combination of physiological and behavioral traits, with consequences for animal performance in a warming world.

Good, Better, Best: How Evolution Optimizes Anatomy and Action

Good, Better, Best: How Evolution Optimizes Anatomy and Action

Life in the slow lane: field metabolic rate and prey consumption rate of the Greenland shark (Somniosus microcephalus) modelled using archival biologgers.

Field metabolic rate (FMR) is a holistic measure of metabolism representing the routine energy utilization of a species living within a specific ecological context, thus providing insight into its ecology, fitness and resilience to environmental stressors. For animals that cannot be easily observed in the wild, FMR can also be used in concert with dietary data to quantitatively assess their role as consumers, improving understanding of the trophic linkages that structure food webs and allowing for informed management decisions. Here, we modelled the FMR of Greenland sharks (Somniosus microcephalus) equipped with biologger packages or pop-up archival satellite tags (PSATs) in two coastal inlets of Baffin Island (Nunavut) using metabolic scaling relationships for mass, temperature and activity. We estimated that Greenland sharks had an overall mean (±s.d.) FMR of 21.67±2.30 mg O2 h-1 kg-0.84 (n=30; 1-4 day accelerometer package deployments) while residing inside these cold-water fjord systems in the late summer, and 25.48±0.47 mg O2 h-1 kg-0.84 (n=6; PSATs) over an entire year. When considering prey consumption rate, an average shark in these systems (224 kg) requires a maintenance ration of 61-193 g of fish or marine mammal prey daily. As Greenland sharks are a lethargic polar species, these low FMR estimates, and corresponding prey consumption estimates, suggest they require very little energy to sustain themselves under natural conditions. These data provide the first characterization of the energetics and consumer role of this vulnerable and understudied species in the wild, which is essential given growing pressures from climate change and expanding commercial fisheries in the Arctic.

Seeing the forest for the trees through metabolic scaling.

We demonstrate that when power scaling occurs for an individual tree and in a forest, there is great resulting simplicity notwithstanding the underlying complexity characterizing the system over many size scales. Our scaling framework unifies seemingly distinct trends in a forest and provides a simple yet promising approach to quantitatively understand a bewilderingly complex many-body system with imperfectly known interactions. We show that the effective dimension, D tree , of a tree is close to 3, whereas a mature forest has D forest approaching 1. We discuss the energy equivalence rule and show that the metabolic rate-mass relationship is a power law with an exponent D/(D + 1) in both cases leading to a Kleiber's exponent of 3/4 for a tree and 1/2 for a forest. Our work has implications for understanding carbon sequestration and for climate science.

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

Widely observed allometric scaling (log-log slope<1) of metabolic rate (MR) with body mass (BM) in animals has been frequently explained using functional mechanisms, but rarely studied from the perspective of multivariate quantitative genetics. This is unfortunate, given that the additive genetic slope (bA) of the MR-BM relationship represents the orientation of the 'line of least genetic resistance' along which MR and BM may most likely evolve. Here, we calculated bA in eight species. Although most bA values were within the range of metabolic scaling exponents reported in the literature, uncertainty of each bA estimate was large (only one bA was significantly lower than 3/4 and none were significantly different from 2/3). Overall, the weighted average for bA (0.667±0.098 95% CI) is consistent with the frequent observation that metabolic scaling exponents are negatively allometric in animals (b<1). Although bA was significantly positively correlated with the phenotypic scaling exponent (bP) across the sampled species, bP was usually lower than bA, as reflected in a (non-significantly) lower weighted average for bP (0.596±0.100). This apparent discrepancy between bA and bP resulted from relatively shallow MR-BM scaling of the residuals [weighted average residual scaling exponent (be)=0.503±0.128], suggesting regression dilution (owing to measurement error and within-individual variance) causing a downward bias in bP. Our study shows how the quantification of the genetic scaling exponent informs us about potential constraints on the correlated evolution of MR and BM, and by doing so has the potential to bridge the gap between micro- and macro-evolutionary studies of scaling allometry.

Idea paper: Effects of gonad type and body mass on the time required for sex change in fishes

AbstractSex change is a well‐known phenomenon in teleost fishes, and it takes several days to a few months depending on the species and direction of sex change. However, the underlying factors influencing the time required for sex change (TS) remain unclear. Given that the time for producing a new gonad largely determines TS, the gonad type (i.e., whether fish retain the gonad of opposite sex or not [delimited or non‐delimited]) and metabolic rate may affect TS. This study sought to test two hypotheses: (1) the delimited gonad shortens TS and (2) TS scales with mass0.1−0.2, because the metabolic scaling exponent (β) in fishes is 0.8–0.9 and biological times scale with mass1−β in general. We compiled data on TS for 12 female‐to‐male and 14 male‐to‐female sex‐changing species from the literature. Results of individual examinations of the effects of gonad type and mass were consistent with our hypotheses. However, upon simultaneous examination of the effects of gonad type and mass, these effects became unclear because of their strong multicollinearity. The compiled data for delimited and non‐delimited gonads were biased toward the smaller and larger species, respectively, precluding us from being able to statistically distinguish between these effects. Small species with non‐delimited gonads and large species with delimited gonads exist; however, their TS has not been measured with high temporal resolution thus far. Therefore, additional experiments on these species are required to statistically distinguish between, as well as to better understand, the effects of gonad type and mass on TS.

Deriving Population Scaling Rules from Individual-Level Metabolism and Life History Traits.

AbstractIndividual metabolism generally scales with body mass with an exponent around 3/4. From dimensional arguments it follows that maximum population growth rate (rmax) scales with a -1/4 exponent. However, the dimensional argument implicitly assumes that offspring size is proportional to adult size. Here, we calculate rmax from metabolic scaling at the level of individuals within size-structured populations while explicitly accounting for offspring size. We identify four general patterns of how rmax scales with adult mass based on four empirical life history patterns employed by groups of species. These life history patterns are determined by how traits of somatic growth rate and/or offspring mass relate to adult mass. One life history pattern-constant adult-to-offspring mass ratio and somatic growth rate independent of adult mass-leads to the classic -1/4 scaling of rmax. The other three life history patterns either lead to nonmetabolic population growth scaling with adult mass or do not follow a power-law relationship at all. Using life history data on five marine taxa and terrestrial mammals, we identify species groups that belong to one of each case. We predict that elasmobranchs, copepods, and mammals follow standard -1/4 power-law scaling, whereas teleost fish and bivalves do not have a pure power-law scaling. Our work highlights how taxa may deviate from the classic -1/4 metabolic scaling pattern of maximum population growth. The approach is generic and can be applied to any taxa.