Metabolic rate associates with, but does not generate covariation between, behaviours in western stutter-trilling crickets, Gryllus integer

Abstract

The causes and consequences of among-individual variation and covariation in behaviours are of substantial interest to behavioural ecology, but the proximate mechanisms underpinning this (co)variation are still unclear. Previous research suggests metabolic rate as a potential proximate mechanism to explain behavioural covariation. We measured the resting metabolic rate (RMR), boldness and exploration in western stutter-trilling crickets, , selected differentially for short and fast development over two generations. After applying mixed-effects models to reveal the sign of the covariation, we applied structural equation models to an individual-level covariance matrix to examine whether the RMR generates covariation between the measured behaviours. All traits showed among-individual variation and covariation: RMR and boldness were positively correlated, RMR and exploration were negatively correlated, and boldness and exploration were negatively correlated. However, the RMR was not a causal factor generating covariation between boldness and exploration. Instead, the covariation between all three traits was explained by another, unmeasured mechanism. The selection lines differed from each other in all measured traits and significantly affected the covariance matrix structure between the traits, suggesting that there is a genetic component in the trait integration. Our results emphasize that interpretations made solely from the correlation matrix might be misleading.

Evidence of phenotypic correlation between exploration activity and resting metabolic rate among populations across an elevation gradient in a small rodent species

“…The lack of a significant covariance at the population level in the second approach, despite strong effects of elevation on both traits, is most likely explained by low statistical power coming from the fact that only nine populations from two elevations were sampled. Our results in voles are in line with recent findings in western stutter-trilling cricket (Gryllus integer) suggesting that correlations between physiological, behavioral, and life history traits could have occurred due to environmental factors rather than due to genetic constraints (Niemelä et al 2013; see also Krams et al 2017).…”

Spontaneous activity rates and resting metabolism: Support for the allocation model of energy management at the among‐individual level

“…This provides evidence for the "allocation" model of energy management (Daan et al, 1990, Ricklefs et al, 1996, Nilsson, 2002, see also reviews in Careau et al, 2008, Auer et al, 2017. This is a seemingly rare observation in the literature given that most correlations are very low but in the positive direction, whereas very few studies show evidence of a negative correlation (Careau, Beauchamp, Bouchard, & Morand-Ferron, 2019;Krams et al, 2017Krams et al, , 2018Royauté et al, 2018). Given that the observed negative covariance between RMR and activity did not match our expectations under the performance model, this…”

“…This provides evidence for the “allocation” model of energy management (Daan et al, , Ricklefs et al, , Nilsson, , see also reviews in Careau et al, , Auer et al, ). This is a seemingly rare observation in the literature given that most correlations are very low but in the positive direction, whereas very few studies show evidence of a negative correlation (Careau, Beauchamp, Bouchard, & Morand‐Ferron, ; Krams et al, , ; Royauté et al, ). Given that the observed negative covariance between RMR and activity did not match our expectations under the performance model, this suggests that activity and underlying metabolic variation are not always linked together in ways as predicted by the majority of recent theoretical advances in this area (Biro et al, ; Biro & Stamps, , ; Burton et al, ; Réale et al, ; Sih & Bell, ).…”

“…Another reason is that we should not simply expect all behaviors to be similarly correlated with metabolism, as not all behaviors necessarily have substantial energy costs nor clear effects on energy intake (Biro & Stamps, 2010;Mathot, Nicolaus, Araya-Ajoy, Dingemanse, & Kempenaers, 2014). Variable environmental conditions if not accounted for can confound relationships between behavior and metabolism (Biro & Stamps, 2010;Killen et al, 2013), and if trials are short in duration shy individuals may not achieve a non-stressed resting metabolism (Biro et al, 2016;Careau et al, 2008;Krams et al, 2017).…”

Meta-analysis reveals weak associations between intrinsic state and personality

“…Empirical tests of theory have recently focused on measuring behavioural and intrinsic state variables within the same set of individuals, typically focusing on 'risky' behaviours (defined as behaviours affecting resource acquisition at the cost of increased mortality [20,33]) and state variables such as metabolic rate (e.g. [34][35][36][37]), plasma hormone levels (e.g. [38 -41]), body mass (e.g.…”