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Assessing the utility of C:N ratios for predicting lipid content in fishes

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Abstract:

Numerous researchers have attempted to find suitable proxies for the lipid content of fishes. Owing to the high carbon content of lipids, C:N ratios have been used as a predictor of lipid content both for the purposes of quantifying condition and for stable isotope analyses. Here we examine the utility of C:N ratios for predicting the lipid content within and among populations, and to validate commonly used published percent lipid – C:N ratio models. No common percent lipid – C:N ratio model was found to apply; instead, population-specific influences on lipid content were observed. Published lipid prediction models significantly underestimated lipid content, and often had worse prediction error than the error obtained by using measured mean lipids as the prediction for all samples. Maximum prediction error by population ranged from a low of 50.7% to a high of 65.0%. Our results provide no support for the idea that there is a predictable relationship between bulk C:N ratios and lipid content. We recommend that sample-specific relationships be developed in situations where lipid prediction is needed, rather than relying on published models.

De nombreux chercheurs ont essayé de trouver des variables de remplacement adéquates pour le contenu lipidique des poissons. À cause du fort contenu en carbone des lipides, les rapports C :N ont servi à prédire le contenu lipidique, tant pour la mesure de la condition que pour les analyses d'isotopes stables. Nous examinons ici l'utilité des rapports C :N pour la prédiction du contenu lipidique au sein des populations et entre les populations afin de valider les modèles % de lipides - rapport C :N les plus communément utilisés dans la littérature. Aucun des modèles communs % de lipides - rapport C :N n'est applicable; au contraire, on observe des influences spécifiques aux populations sur le contenu lipidique. Les modèles de prédiction des lipides dans la littérature sous-estiment significativement le contenu lipidique et souvent ils ont une erreur de prédiction plus importante que celle obtenue en utilisant la mesure des lipides moyens comme base de prédiction pour tous les échantillons. L'erreur de prédiction maximale par population varie d'un minimum de 50,7 % à un maximum de 65,0 %. Nos résultats n'appuient en aucune façon la proposition qu'il existe une relation prédictive entre les rapports globaux de C :N et le contenu lipidique. Nous recommandons d'établir des relations spécifiques aux échantillons pour obtenir des prédictions des lipides plutôt que de se fier aux modèles publiés.

Document Type: Research Article

Publication date: 2011-02-01

More about this publication?
  • Published continuously since 1901 (under various titles), this monthly journal is the primary publishing vehicle for the multidisciplinary field of aquatic sciences. It publishes perspectives (syntheses, critiques, and re-evaluations), discussions (comments and replies), articles, and rapid communications, relating to current research on cells, organisms, populations, ecosystems, or processes that affect aquatic systems. The journal seeks to amplify, modify, question, or redirect accumulated knowledge in the field of fisheries and aquatic science. Occasional supplements are dedicated to single topics or to proceedings of international symposia.
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