Inter-individual variation within social groups: how metabolic rate shapes the pace of life
Date
2020
Authors
Mugel, Stephen G., author
Naug, Dhruba, advisor
Florant, Gregory L., committee member
Ode, Paul, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
Metabolic rate (MR) is often cited as the fundamental rate which determines the rate of all biological processes by shaping energetic availability for the various physiological, behavioral, and life-history traits that contribute to performance. Furthermore, the metabolic theory of ecology posits that performance at any level of biological organization is a function of the MR of its constituent units. It has therefore been suggested that MR drives the widely observed covariance among these different levels of phenotypic traits. However, much of the work on this topic has relied on pairwise correlational analysis on a handful of traits at a time, leaving an important gap in our understanding regarding the functional links that shape this phenotypic covariance, often referred to as pace-of-life. Furthermore, at a collective level, this has led to significant attention regarding how MR scales across group size, but considerably less attention has been paid to how heterogeneity in MR among constituent units shapes collective outputs. Using honeybees as a model, we measured a large number of behavioral, physiological, and life-history traits in individual bees and used a path analysis to demonstrate that variation in metabolic rate plays a fundamental proximate role in driving the covariance among these traits. We combined this with a factor analysis in a structural equation model framework to characterize the overall phenotypic covariance or the pace-of-life axis in honeybees. We discuss the importance of these findings in the context of how interindividual variation in terms of slow–fast phenotypes may drive the phenotype of a group and the functional role metabolic rate might play in shaping division of labor and social evolution. Building on this work, we leveraged the well-characterized differences in MR associated with 'F' ('fast') and 'S' ('slow') malate dehydrogenase (MDH) alleles to breed homozygous genotypes of bees expressing high (FF) and low (SS) MR in addition to heterozygotes (SF), thought to express an intermediate phenotype. We then mixed progeny from these lines to create experimental groups with four different phenotype compositions: monomorphic FF, monomorphic SS, monomorphic SF, and a polymorphic group type at a 1 FF: 1 SS ratio. We then measured MR, energetic intake, thermoregulation in cold and heat stress, and survival of these groups in a high and low resource environment. Monomorphic fast groups outperformed monomorphic slow and polymorphic groups, which performed worse than expected on most traits. We quantified the effect of heterogeneity on polymorphic group performance using the 'diversity effect,' an analytical technique often used in ecosystem ecology to compare the productivity of diverse ecosystem assemblages to null expectations set by the constituent species when living alone. Diversity effects can be partitioned selection and complementarity effects and understand the mechanisms through which biodiversity acts on ecosystem productivity. We applied this technique in a novel way to show how each group-level performance trait is influenced by MR morph diversity through different processes. We also found that MR was strongly correlated to the other traits, especially in the low resource environment. We discuss these results in the context of how MR plays an important role in shaping division of labor and social evolution. These studies provide empirical support for the theoretical idea that metabolic rate acts as a proximate driver of phenotypic covariance among a number of physiological, behavioral, and life-history traits at the individual level, and that behavior acts as a mediator for how metabolic rate affects life history. In addition, using honeybees as an experimental model for these studies establishes a framework for asking questions regarding how these individual-level phenotypic covariance patterns lead to observed phenotypic covariance patterns at the colony level that have functional consequences for division of labor and social evolution. The results of these studies therefore contribute toward a better understanding of the rules of life that shape processes across different levels of biological organization. Our use of different structural equation modeling approaches for inferring heuristics and proximate causal relationships among multiple phenotypic traits also informs future research efforts on this topic. We also present a novel approach to experiments that explore functional group level performance traits through partitioning the effects of inter-individual heterogeneity.