Metabolic Rate Interacts with Resource Availability to Determine Individual Variation in Microhabitat Use in the Wild

Abstract

Ecological pressures such as competition can lead individuals within a population to partition resources or habitats, but the underlying intrinsic mechanisms that determine an individual's resource use are not well understood. Here we show that an individual's own energy demand and associated competitive ability influence its resource use, but only when food is more limiting. We tested whether intraspecific variation in metabolic rate leads to microhabitat partitioning among juvenile Atlantic salmon (Salmo salar) in natural streams subjected to manipulated nutrient levels and subsequent per capita food availability. We found that individual salmon from families with a higher baseline (standard) metabolic rate (which is associated with greater competitive ability) tended to occupy fasterflowing water, but only in streams with lower per capita food availability. Faster-flowing microhabitats yield more food, but high metabolic rate fish only benefited from faster growth in streams with high food levels, presumably because in low-food environments the cost of a high metabolism offsets the benefits of acquiring a productive microhabitat. The benefits of a given metabolic rate were thus context dependent. These results demonstrate that intraspecific variation in metabolic rate can interact with resource availability to determine the spatial structuring of wild populations.

Trait-Based Variation in the Foraging Performance of Individuals

“…Metabolic rate is thought to be an integrative measure of energy use and ecological interactions (Brown et al, 2004). For example, standard metabolic rate in Atlantic salmon (Salmo salar) influenced habitat choice and was related to resource access (Auer et al, 2020). We therefore expected to find links between oxygen consumption and morphology, movement, and foraging in this experiment.…”

Differential sensitivity to warming and hypoxia during development and long-term effects of developmental exposure in early life stage Chinook salmon

“…Variation in metabolic rate can also underlie differences in foraging, swimming ability and behavioural traits such as dominance, aggression and risk-behaviours ( Metcalfe et al , 2015 ). It is difficult, however, to assess whether the reduced RMR observed in numerous treatments at the alevin stage and in fry that experienced chronic developmental stressors would be beneficial or harmful to later life stages because the effects of changes in metabolic rate can be highly context dependent in terms of the habitat, food availability and temperatures present ( Reid et al , 2012 ; Auer et al , 2018 ). Additionally, metabolic performance can vary depending on the measurement temperature.…”

Standard metabolic rate does not associate with age-at-maturity genotype in juvenile Atlantic salmon

“…Vgll3 genotype has been shown to have a strong effect on salmon life-history (Ayllon et al, 2015;Barson et al, 2015;Verta et al, 2020), and recent findings have suggested that this effect might be mediated by vgll3-induced differences in body condition (Debes et al, 2021). Taking this together with the connections between standard metabolic rate (SMR) and resource acquisition and assimilation (Armstrong et al, 2011;Auer, Bassar, et al, 2020;Auer, Solowey, et al, 2020;Bochdansky et al, 2005;Millidine et al, 2009;Rosenfeld et al, 2015), we hypothesized that vgll3 genotype might be asserting some of its effects through changes in energetic physiology that would be reflected in SMR. However, we did not detect any difference in either SMR or body condition between juvenile Atlantic salmon individuals of different homozygous vgll3 genotypes.…”

“…Metabolic phenotype is a multi-faceted set of traits, covering not just standard metabolic rate, but also the maximum metabolic rate, aerobic scope, and daily energy expenditure, to mention some. Additionally, the consequences of variation in metabolic traits are context-dependent and may change under different environmental conditions and life stages (Auer, Bassar, et al, 2020;Auer, Solowey, et al, 2020;Bochdansky et al, 2005;Millidine et al, 2009;Norin & Metcalfe, 2019). We initially planned to also measure metabolic rate under exhaustive swimming to obtain data on maximum metabolic rate (MMR), but had to abandon these trials as we were unable to motivate juvenile salmon of this age and size to do any exhaustive swimming, either by swim tunnel or by hand chasing.…”