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Dryad

Data from: Metabolism drives demography in an experimental field test

Cite this dataset

Schuster, Lukas; Cameron, Hayley; White, Craig; Marshall, Dustin (2021). Data from: Metabolism drives demography in an experimental field test [Dataset]. Dryad. https://doi.org/10.5061/dryad.vhhmgqntv

Abstract

Metabolism should drive demography by determining the rates of both biological work and resource demand. Long-standing ‘rules’ for how metabolism should covary with demography permeate biology, from predicting the impacts of climate change to managing fisheries. Evidence for these rules is almost exclusively indirect and in the form of among-species comparisons, while direct evidence is exceptionally rare. In a manipulative field experiment on a sessile marine invertebrate, we created experimental populations that varied systematically in population size (density) and metabolic rate, but not body size. We then tested key theoretical predictions regarding relationships between metabolism and demography by parameterising population models with lifetime performance data from our field experiment. We found populations with higher metabolisms had greater intrinsic rates of increase and lower carrying capacities, in qualitative accordance with classic theory, but we also found important departures from theory. In particular, carrying capacity declined less steeply than predicted, such that energy use at equilibrium increased with metabolic rate, violating the long-standing axiom of energy equivalence. Theory holds that energy equivalence emerges because resource supply is assumed to be independent of metabolic rate. We find this assumption to be violated under real world conditions – with potentially far-reaching consequences for the management of biological systems.

Methods

We created experimental populations that differed in their mean metabolic rates (MeanMR) at two different densities and then followed the survival, growth, onset of reproduction and fecundity (reproductive output) of each individual within a given population by checking colony absence/presence and counting the number of bifurcations (colony size) and the number of ovicells (external offspring bearing brood chambers; every ovicell contains a single larva) every two weeks over a period of six months (a total of 11 censuses). We then used the collected field data to parameterise integral projection models (IPMs) to investigate the effects of metabolic rate on population demography.

Funding

Australian Research Council