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Organisms vary widely in size from microbes weighing 0.1 picograms to trees weighing thousands of megagrams, a 10 21-fold range similar to the difference in mass between an elephant and the Earth. Mass has a pervasive influence on biological processes but the effect is usually non-proportional; for example, a 10-fold increase in mass is typically accompanied by just a 4-to-7-fold increase in metabolic rate. Understanding the cause of allometric scaling has been a long-standing problem in biology. Here, we examine the evolution of metabolic allometry in animals by linking microevolutionary processes to macroevolutionary patterns. We show that the genetic correlation between mass and metabolic rate is strong and positive in insects, birds, and mammals. We then use these data to simulate the macroevolution of mass and metabolic rate, and show that the interspecific relationship between these traits in animals is consistent with evolution under persistent multivariate selection on mass and metabolic rate over long periods of time.

Summary1. Environmental variability and perturbations can influence population persistence. It is therefore important to understand whether and how animals can compensate for environmental variability and thereby increase resilience of natural populations. Evolutionary theory predicts that in fluctuating environments, selection should favour developmental modifiers that reduce phenotypic expression of genetic variation. The expected result is that phenotypes are buffered from environmental variation across generations. 2. Our aim was to determine whether phenotypes of mosquitofish (Gambusia holbrooki) remain stable across generations in which individuals were born into different thermal environments. We predicted that the spring generation (cool environment) would acclimate by increasing the concentration of regulatory transcription factor mRNA and activities of rate-limiting enzymes (hierarchical regulation) to compensate for the negative thermodynamic effects of lower temperatures on metabolic and locomotor performance. In contrast, the summer-born generation (warm environment) would show less capacity for acclimation and hierarchical regulation. 3. We show that fish from both generations acclimated, but that there were significant differences in the phenotypic consequences of acclimation. The overall result was that burst performance, metabolic scope, and the activities of cytochrome c oxidase and lactate dehydrogenase were buffered from environmental change and did not differ between spring and summer fish at their natural water temperatures of 15°C and 25°C, respectively. However, there were differences between generations in sustained swimming performance and citrate synthase activity. 4. We used metabolic control analysis to show that modes of regulation of metabolic scope and locomotor performance differed between generations. Spring-born fish relied to a greater extent on rate-limiting enzymes and transcriptional regulator (PGC-1a and b) mRNA concentrations than summer-born fish. 5. We suggest that developmental modifiers are favoured in fluctuating environments to maximize phenotypic fitness of each generation. We show that the interaction between developmental and reversible acclimation can increase the resilience of physiological performance in a natural population to climate variation.

Anthropogenic climate change and invasive species are two of the greatest threats to biodiversity, affecting the survival, fitness and distribution of many species around the globe. Invasive species are often expected to have broad thermal tolerances, be highly plastic, or have high adaptive potential when faced with novel environments. Tropical island ectotherms are expected to be vulnerable to climate change as they often have narrow thermal tolerances and limited plasticity. In Fiji, only one species of endemic bee, Homalictus fijiensis, is commonly found in the lowland regions, but two invasive bee species, Braunsapis puangensis and Ceratina dentipes, have recently been introduced to Fiji. These introduced species pollinate invasive plants and might compete with H. fijiensis and other native pollinators for resources. To test whether certain performance traits promote invasiveness of some species, and to determine which species are the most vulnerable to climate change, we compared the thermal tolerance, desiccation resistance, metabolic rate, and seasonal performance adjustments of endemic and invasive bees in Fiji. The two invasive species tended to be more resistant to thermal and desiccation stress than H. fijiensis, while H. fijiensis had greater capacity to adjust their CTMAX with season, and H. fijiensis females tended to have higher metabolic rates, than B. puangensis females. These findings provide mixed support for current hypotheses for the functional basis of the success of invasive species, however, we expect the invasive bees in Fiji to be more resilient to climate change due to their increased thermal tolerance and desiccation resistance.

1. The current policy has the world on track to experience around 3°C of warming by 2100. The responses of organisms to our warming world will be mediated by changes in physiological processes, including metabolic rate. Metabolic rate represents the energetic cost of living, and is fundamental to understanding the energy required to sustain populations. Current evidence indicates that animals have a limited capacity to adapt to warmer environments by reducing their metabolic rate. Consequently, animals may be more reliant on metabolic plasticity to ameliorate the thermodynamic effect of rising temperatures on physiological rates. However, metabolic plasticity is influenced by other environmental factors, including the nutritional quality of food. Elevated levels of atmospheric CO 2 are expected to reduce the protein and increase the carbohydrate concentration in plants, but we do not know how this will affect the response of metabolic rate to climate warming. 2. Here we test the interactive effects of developmental dietary protein and carbohydrate concentrations on the metabolic plasticity of adult Drosophila melanogaster in response to a 3°C increase in temperature while accounting for variation associated with body mass and activity (resting metabolic rate). 3. We show that the thermal sensitivity of resting metabolic rate is modulated by developmental nutrition with animals reared on nutritionally poor, low-protein diets showing the greatest increase in resting metabolic rate in response to simulated climate warming. We also show that if the nutritional quality of resources is unaffected by climate change, then temperature-induced increases in resting metabolic rate will be offset by decreases in mass, but the absolute energy requirements of animals will be elevated relative to current conditions despite this. If, on the other hand, temperatures rise and resources become more calorie-dense and carbohydrate-rich, then the resting metabolic rate of animals will remain relatively unchanged, but decreases in mass and activity may drive down the absolute energy requirements of animals. 4. In the absence of evolutionary adaptation, these findings suggest that the combined plastic response of physiological, morphological and behavioural traits to temperature and nutrition may be an important determinant of the ultimate outcome of climate change for populations. | 2489 Functional Ecology ALTON eT AL.

31Metabolic rate scales disproportionally with body mass, such that the energetic cost of living is 32 relatively lower in larger organisms. Theory emphasises the importance of fixed physical 75 drift and natural selection contribute to the variation in metabolic allometry across the tree of life 76 (White et al., 2019, Fossen et al., 2019. 77 4 78 Figure 1. Variation in metabolic allometry at different scales of biological organisation. A: the 79 inter-specific metabolic scaling relationship varies between endothermic and ectothermic taxa. B: 80 the ontogenetic metabolic scaling relationship varies among individual fish (cunner, 81 Tautogolabrus adspersus). The inset in B shows the probability density function for the value of 82 the ontogenetic scaling exponent calculated from the mean effect of mass on metabolic rate (0.062, 83 black line) and the standard deviation (0.0036) of individual-level variation in scaling exponents. 84 Data reproduced from publicly available data sets from (A) Uyeda et al. (2017) and (B) Norin and 85 Gamperl (2018).86 87 88 When the developmental, structural or functional bases of traits are closely shared, such as 89 between mass and metabolic rate, this can generate strong constraints on trait evolution (Blows & 90 Hoffmann 2005). Developmental and functional constraints exert proximate effects on the 91 phenotype and, in doing so, mediate the genetic constraints (Connallon and Hall, 2018) on 92 phenotypic evolution (Arnold 1992). Genetically correlated traits do not evolve independently, 93 which can either restrict or enhance short-term evolutionary responses to phenotypic selection 94 . Yet while 95 genetic correlations among traits constrain short-term evolutionary change, at the long timescales 96 over which lineages diverge, the genetic associations among traits can themselves be altered by 97 persistent patterns of directional and stabilising selection (Maynard-Smith et al., 1985; Zeng 1988; 98 Sinervo and Svenson, 2002; Hunt et al. 2007). Hence, documenting patterns of genetic variation in 99the association between mass and metabolic rate is not only a prerequisite for identifying the 100 evolutionary constraints on the metabolic scaling relationship within populations, but will also 101 5 help to understand how microevolutionary processes contribute to the origin and maintenance of 102 metabolic allometry. 103There are now numerous published estimates of additive genetic variance for metabolic rate 104 and mass as separate traits, with heritability estimates for each trait ranging widely from 0 to about 105 ~0.7 (Pettersen et al., 2018). Mass and metabolic rate also usually exhibit a strong and positive 106 genetic correlation (Tieleman et al., 2009, Schimpf et al., 2013, Mathot et al., 2013, and the genetic 107 association between mass and metabolic rate is present in diverse lineages that diverged up to 800 108 million years ago (White et al., 2019). The widespread and persistent association between mass and 109 metabolic rate suggests that these traits either share many...

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