bioRxivEcologyPreprint
Filling a metabolism data gap in marine fish reveals dual pace-of-life and reproductive strategy axes
Marine BeneatiD, Alaia MorelliD, Fabien MoulleciD, Nicolas BarrieriD, Yunne‐Jai ShiniD, Bruno ErnandeiD
Abstract
Resting metabolic rate, the basal energy required for an organism's maintenance, is central to predicting the eco-evolutionary consequences of environmental and anthropogenic pressures on marine ectotherms. Yet, direct measurements remain extremely scarce, covering less than 1% of marine fish species. Building on the Pace Of Life Syndrome (POLS) hypothesis, which posits a positive correlation between metabolism and life-history speed, we inferred temperature- and mass-specific resting metabolic rate for 18,214 fish species (16,998 Teleostei and 1,216 Elasmobranchii). Estimates were derived from relationships with 15 functional traits and phylogeny using phylogenetic structural equation modelling, a novel approach combining phylogenetic comparative methods with structural equation models. Cross-validations indicated high predictive performance, although some clades require cautious interpretation due to limited empirical data. In line with expectations from life-history theory, ecological niche and morphology, species with the highest metabolic rates were small, narrow, shallow-bodied, and long-jawed pelagic fish with high mortality, short lifespan and rapid growth - traits typical of small epipelagics. The metabolic rate variation aligned with the slow-fast life-history continuum, supporting the POLS hypothesis, but was equally explained by reproductive strategy: highly fecund, fast species exhibited the highest metabolic rate independent of mass and temperature, whereas low-fecundity slow species had the lowest. By filling a critical physiological data gap, our dataset provides a foundation to test long-standing ecological and evolutionary hypotheses such as POLS, and offers a powerful resource to improve models of species and community responses to climate change and exploitation, ultimately supporting physiology-informed ecosystem management.
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