Abstract

AbstractFew studies have attempted to understand how fish growth scales at community and macroecological levels. This study evaluated the drivers of reef fish growth across a large gradient of environmental variables and a range of morphological and behavioural traits. We compiled Von Bertalanffy Growth parameters for reef fishes and standardized K relative to species maximum sizes, obtaining Kmax. We then modelled the response of Kmax to body size, diet, body shape, position relative to the reef, schooling behaviour, sea surface temperature, pelagic net primary productivity and ageing method, while accounting for phylogenetic structure in the data. The final model explained 61.5% of the variation in Kmax and contained size, temperature, diet, method and position. Body size explained 64% of the modelled Kmax variability, while the other variables explained between 6% (temperature) and 2.5% (position). Kmax steadily decreased with body size and increased with temperature. All else being equal, herbivores/macroalgivores and pelagic reef fishes had higher growth rates than the other groups. Moreover, length–frequency ageing tended to overestimate Kmax compared to other methods (e.g. otolith's rings). Our results are consistent with (a) metabolic theory that predicts body size and temperature dependence of physiological rates; and (b) ecological theory that implies influence of resource availability and acquisition on growth. At last, we use machine learning to accurately predict growth coefficients for combinations of traits and environmental settings. Our study helps to bridge the gap between individual and community growth patterns, providing insights into the role of fish growth in the ecosystem process of biomass accumulation.

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