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Data from: Predicting rates of isotopic turnover across the animal kingdom: a synthesis of existing data

Citation

Thomas, Stephen M.; Crowther, Thomas W. (2015), Data from: Predicting rates of isotopic turnover across the animal kingdom: a synthesis of existing data, Dryad, Dataset, https://doi.org/10.5061/dryad.mf3sp

Abstract

The stable isotopes of carbon (13C /12C) and nitrogen (15N /14N) represent powerful tools in food-web ecology, providing a wide range of dietary information in animal consumers. However, identifying the temporal window over which a consumer's isotopic signature reflects its diet requires an understanding of elemental incorporation, a process that varies from days to years across species and tissue types. Though theory predicts body size and temperature are likely to control incorporation rates, this has not been tested empirically across a morphologically and phylogenetically diverse range of taxa. Readily available estimates of this relationship would, however, aid in the design of stable isotope food-web investigations and improve the interpretation of isotopic data collected from natural systems. Using literature-derived turnover estimates from animal species ranging in size from 1 mg to 2000 kg, we develop a predictive tool for stable isotope ecologists, allowing for estimation of incorporation rates in the structural tissues of entirely novel taxa. In keeping with metabolic scaling theory, we show that isotopic turnover rates of carbon and nitrogen in whole organisms and muscle tissue scale allometrically with body mass raised approximately to the power -0.19, an effect modulated by body temperature. This relationship did not, however, apply to incorporation rates in splanchnic tissues, which were instead dependent on the thermoregulation tactic employed by an organism, being considerably faster in endotherms than ectotherms. We believe the predictive turnover equations we provide can improve the design of experiments and interpretation of results obtained in future stable isotopic food-web studies.

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