Plastic but not adaptive: habitat‐driven differences in metabolic rate despite no differences in selection between habitats

Squamate metabolic rates decrease in winter beyond the effect of temperature

The reptilian form of hibernation (brumation) is much less studied than its mammalian and insect equivalents. Hibernation and brumation share some basic features but may differ in others. Evidence for hypometabolism in brumating reptiles beyond the effect of temperature is sporadic and often ignored. We calculated the standard metabolic rates (SMR, oxygen uptake during inactivity), in winter and/or summer, of 156 individuals representing 59 species of Israeli squamates across all 17 local families. For 32 species, we measured the same individuals during both seasons. We measured gas exchange continuously in a dark metabolic chamber, under the average January high and low temperatures (20°C and 12°C), during daytime and nighttime. We examined how SMR changes with season, biome, body size, temperature and time of day, using phylogenetic mixed models. Metabolic rates increased at sunrise in the diurnal species, despite no light or other external cues, while in nocturnal species the metabolic rates did not increase. Cathemeral species shifted from a diurnal-like diel pattern in winter to a nocturnal-like pattern in summer. Regardless of season, Mediterranean species SMRs were 30% higher than similar-sized desert species. Summer SMR of all species together scaled with body size with an exponent of 0.84 but dropped to 0.71 during brumation. Individuals measured during both seasons decreased their SMR between summer and winter by a 47%, on average, at 20°C and by 70% at 12°C. Q10 was 1.75 times higher in winter than in summer, possibly indicating an active suppression of metabolic processes under cold temperatures. Our results challenge the commonly held perception that squamate physiology is mainly shaped by temperature, with little role for intrinsic metabolic regulation. The patterns we describe indicate that seasonal, diel and geographic factors can trigger remarkable shifts in metabolism across squamate species.

White Paper: An Integrated Perspective on the Causes of Hypometric Metabolic Scaling in Animals

Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g. basal, resting, field, maximally-active). The scaling of metabolism is usually highly correlated with the scaling of many life history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to a) lower contents of expensive tissues (brains, liver, kidneys), and b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. A additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include: 1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries, 2) studies linking scaling to ecological or phylogenetic context, 3) studies that consider multiple, possibly interacting hypotheses, and 4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate and reproduction.

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.

Metabolic phenotype mediates the outcome of competitive interactions in a response-surface field experiment

Competition and metabolism should be linked. Intraspecific variation in metabolic rates and, hence, resource demands covary with competitive ability. The effects of metabolism on conspecific interactions, however, have mostly been studied under laboratory conditions. We used a trait-specific response-surface design to test for the effects of metabolism on pairwise interactions of the marine colonial invertebrate, Bugula neritina in the field. Specifically, we compared the performance (survival, growth, and reproduction) of focal individuals, both in the presence and absence of a neighbor colony, both of which had their metabolic phenotype characterized. Survival of focal colonies depended on the metabolic phenotype of the neighboring individual, and on the combination of both the focal and neighbor colony metabolic phenotypes that were present. Surprisingly, we found pervasive effects of neighbor metabolic phenotypes on focal colony growth and reproduction, although the sign and strength of these effects showed strong microenvironmental variability. Overall, we find that the metabolic phenotype changes the strength of competitive interactions, but these effects are highly contingent on local conditions. We suggest future studies explore how variation in metabolic rate affects organisms beyond the focal organism alone, particularly under field conditions.

Metabolism drives demography in an experimental field test

Metabolism should drive demography by determining the rates of both biological work and resource demand. Long-standing "rules" for how metabolism should covary with demography permeate biology, from predicting the impacts of climate change to managing fisheries. Evidence for these rules is almost exclusively indirect and in the form of among-species comparisons, while direct evidence is exceptionally rare. In a manipulative field experiment on a sessile marine invertebrate, we created experimental populations that varied in population size (density) and metabolic rate, but not body size. We then tested key theoretical predictions regarding relationships between metabolism and demography by parameterizing population models with lifetime performance data from our field experiment. We found that populations with higher metabolisms had greater intrinsic rates of increase and lower carrying capacities, in qualitative accordance with classic theory. We also found important departures from theory-in particular, carrying capacity declined less steeply than predicted, such that energy use at equilibrium increased with metabolic rate, violating the long-standing axiom of energy equivalence. Theory holds that energy equivalence emerges because resource supply is assumed to be independent of metabolic rate. We find this assumption to be violated under real-world conditions, with potentially far-reaching consequences for the management of biological systems.