Energetic trade-offs and feedbacks between behavior and metabolism influence correlations between pace-of-life attributes
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Correlations between behavioral, physiological, and morphological traits linked to life history have been given the label “pace-of-life syndrome” (POLS), hypothesized to arise through variation in the resolution of a trade-off between present and future reproduction. However, other trade-offs over energy allocation may also have effects and influence the present-future trade-off. We analyzed an optimality model of basal metabolic rate (BMR) across variation in food availability and two types of mortality. The model contained three major features: (1) feedback between activity and energy acquisition, (2) links between BMR and the use of energy for other traits, and (3) allocation trade-offs between BMR and all other traits, between activity and defense, and between defense against activity-related risk and activity-independent risk. The model produced an intermediate optimal BMR that was usually highest at an intermediate level of food availability. Food availability and both types of mortality risk interacted to influence the exact value of optimal BMR. Trait correlations expected in the POLS existed under some environmental conditions, but these correlations flipped sign under different conditions and were not always strong. Our model reproduces trait correlations consistent with the POLS, but also generated a “sloppy” syndrome with considerable non-POLS-like variation. In addition, among-individual, non-adaptive variation in BMR produced adjustments of the other traits. These fit a best-of-a-bad job strategy, and the adjustments further weakened trait correlations. The results emphasize that variation in resources and mortality risk creates a diversity of correlation structures. This complexity means the POLS is likely to be a variable construct.
Many attributes important for reproduction and survival are associated. Such associations may arise through common physiological processes and correlated selection. We modeled metabolic rate within a system in which foraging behavior both depended on and mediated the acquisition of resources necessary for metabolism, while energy was allocated among multiple attributes. Variation in several environmental variables (food availability and two types of mortality risk) influenced basal metabolic rate, activity, and defenses against mortality risk. This variation affected the correlations between the traits in complex ways. When basal metabolic rate was non-optimal, evolution of the allocation of energy to other traits partially compensated, but this further eroded consistent trait correlations. Our results indicate that complexity in how energy is acquired and used can potentially disrupt trait correlations normally associated with the pace-of-life syndrome.
KeywordsLife history Syndrome Activity Energy allocation Conflicting demands Optimization
We thank the Westneat and Crowley labs for comments throughout the process and R. Fox, J. Wright, two anonymous reviewers, and a guest editor for suggestions on the manuscript. This project emerged from a class exercise in a graduate course taught by PHC.
We received support from the Department of Biology at the University of Kentucky, and DFW received additional support from the US National Science Foundation (IOS1257718).
Compliance with ethical standards
This research did not involve either humans or animals.
Conflict of interest
The authors declare that they have no conflicts of interest.
- Careau V, Garland Jr. T (2012) Performance, personality, and energetics: correlation, causation, and mechanism. Physiol Biochem Zool 85:543–571Google Scholar
- Daan S, Masman D, Groenewold A (1990) Avian basal metabolic rates: their association with body composition and energy expenditure in nature. Am J Phys 259:R333–R340Google Scholar
- Dawkins R (1976) The selfish gene, 2nd edn. Oxford University Press, New York CityGoogle Scholar
- Konarzewski M, Książek A (2013) Determinants of intra-specific variation in basal metabolic rate. J Comp Physiol B 183:27–41Google Scholar
- Krams I, Kivleniece I, Kuusik A, Krama T, Freeberg TM, Mänd R, Vrublevska J, Rantala MJ, Mänd M (2013) Predation selects for low resting metabolic rate and consistent individual differences in anti-predator behavior in a beetle. Acta Ethol 16:163–172Google Scholar
- Krams IA, Niemelä PT, Trakimas G, Krams R, Burghardt GM, Krama T, Kuusik A, Mänd M, Rantala MJ, Mänd R, Kekäläinen J, Sirkka I, Luoto S, Kortet R (2017) Metabolic rate associates with, but does not generate covariation between, behaviours in western stutter-trilling crickets, Gryllus integer. Proc R Soc B 284:20162481Google Scholar
- Mathot KJ, Frankenhuis W (2018) Models of pace-of-life syndromes (POLS): a systematic review. Behav Ecol Sociobiol. https://doi.org/10.1007/s00265-018-2459-9
- Montiglio P-O, Dammahn M, Messier G, Réale D (2018) The pace-of-life syndrome revisited: the role of ecological conditions and natural history on the slow-fast continuum. Behav Ecol Sociobiol. (in press)Google Scholar
- Ots I, Kerimov AB, Ivankina EV, Ilyina TA, Hõrak P (2001) Immune challenge affects basal metabolic activity in wintering great tits. Proc R Soc Lond B 268:1175–1181Google Scholar
- Pap PL, Vágási C, Vincze O, Osváth G, Veres-Szászka J, Czirják G (2015) Physiological pace of life: the link between constitutive immunity, developmental period, and metabolic rate in European birds. Oecologia 177:147–158Google Scholar
- Royauté R, Berdal M, Hickey C, Dochtermann NA (2018) Paceless life? A meta-analysis of the pace-of-life syndrome hypothesis. Behav Ecol. https://doi.org/10.1007/s00265-018-2472-z
- Selman C, Lumsden S, Bünger L, Hill WG, Speakman JR (2001) Resting metabolic rate and morphology in mice (Mus musculus) selected for high and low food intake. J Exp Biol 204:777–784Google Scholar
- Shearer TA, Pruitt JN (2014) Individual differences in boldness positively correlate with heart rate in orb-weaving spiders of genus Larinioides. Curr Zool 60:387–391Google Scholar
- Sih A (1987) Predator and prey lifestyles: an evolutionary and ecological overview. In: Predation: direct and indirect impacts on aquatic communities. (Ed. by WC Kerfoot & A Sih), pp 203–224. Hanover, New Hampshire: University Press of New England. Google Scholar
- Wengström N, Wahlqvist F, Näslund J, Aldvén D, Závorka L, Osterling ME, Höjesjö J (2016) Do individual activity patterns of brown trout (Salmo trutta) alter the exposure to parasitic freshwater pearl mussel (Margaritifera margaritifera) larvae? Ethology 122:769–778Google Scholar