Metabolic rate, context-dependent selection, and the competition-colonization trade-off

Abstract

Metabolism is linked with the pace-of-life, co-varying with survival, growth, and reproduction. Metabolic rates should therefore be under strong selection and, if heritable, become less variable over time. Yet intraspecific variation in metabolic rates is ubiquitous, even after accounting for body mass and temperature. Theory predicts variable selection maintains trait variation, but field estimates of how selection on metabolism varies are rare. We use a model marine invertebrate to estimate selection on metabolic rates in the wild under different competitive environments. Fitness landscapes varied among environments separated by a few centimeters: interspecific competition selected for higher metabolism, and a faster pace-of-life, relative to competition-free environments. Populations experience a mosaic of competitive regimes; we find metabolism mediates a competition-colonization trade-off across these regimes. Although high metabolic phenotypes possess greater competitive ability, in the absence of competitors, low metabolic phenotypes are better colonizers. Spatial heterogeneity and the variable selection on metabolic rates that it generates is likely to maintain variation in metabolic rate, despite strong selection in any single environment.

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

“…Other studies have found strong selection on metabolic rate in our species (Pettersen et al 2016(Pettersen et al , 2020, whereas we did not. These differences may be due to the measurements of metabolic phenotypes at different life-history stages, which differ in the potential for the environment to affect metabolic rates (Withers et al 2006, White et al 2007, Jetz et al 2008, Alton et al 2012, Naya et al 2018.…”

“…For example, Pettersen et al (2016Pettersen et al ( , 2020 measured metabolic rates during the larval stage, whereas we determined metabolic rates of three weeks old colonies that had been in the field prior to measurements. Although metabolic rate is generally repeatable, especially over short timescales (White et al 2013), estimates of repeatability are usually lower under field conditions due to greater environmental variability (Auer et al 2016b).…”

Incubation Temperature and Maternal Resource Provisioning, but Not Contaminant Exposure, Shape Hatchling Phenotypes in a Species with Temperature-Dependent Sex Determination

“…Recently, researchers developed a simple model to describe the temperature dependence of developmental energet-ics in ectotherms that may provide insight into this phenomenon (Marshall et al, 2020;Pettersen et al, 2020). Under this model, the energetic cost of development is represented as the product of metabolic rate and incubation duration.…”

Geographical bias in physiological data limits predictions of global change impacts

“…We gathered a total of 5,329 spatially explicit measurements of the physiological traits likely to dictate the responses of terrestrial animals to climate change: critical upper and lower thermal limits, supercooling temperature, optimal temperatures for performance, rates of metabolism, patterns of gas exchange and acclimation capacity (Table 1). The physiological traits we chose as means to identify studied environments define the range of temperatures over which animals can survive (critical upper and lower thermal limits, supercooling temperature), the rates at which they utilise energy and the demands they place on their environment (metabolic rate, which exhibits associations with survival and fitness that vary among environmental and ecological contexts: Boratyński & Koteja, 2009; Boyce et al., 2020; Pettersen et al., 2016, 2020), their susceptibility to desiccation stress (gas exchange patterns: Schimpf et al., 2012; White, Blackburn, Terblanche, et al., 2007), the temperatures at which functional performance (development, growth, and locomotion) is maximised, and their capacity to compensate physiologically for changes in the thermal environmental (acclimation capacity). The dataset includes records for 2,637 species, including insects, arachnids, fish, amphibians, reptiles, birds and mammals (Table 1).…”

“…supercooling temperature), the rates at which they utilise energy and the demands they place on their environment (metabolic rate, which exhibits associations with survival and fitness that vary among environmental and ecological contexts: Boratyński & Koteja, 2009;Boyce et al, 2020;Pettersen et al, 2016Pettersen et al, , 2020, their susceptibility to desiccation stress (gas exchange patterns: Schimpf et al, 2012;White, Blackburn, Terblanche, et al, 2007), the temperatures at which functional performance (development, growth, and locomotion) is maximised, and their capacity to compensate physiologically for changes in the thermal environmental (acclimation capacity). The dataset includes records for 2,637 species, including insects, arachnids, fish, amphibians, reptiles, birds and mammals (Table 1).…”