The importance of method selection when estimating diet composition with quantitative fatty acid signature analysis

PLoS ONE
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Abstract

Quantitative fatty acid signature analysis (QFASA) is a common method of estimating the composition of prey species in the diets of consumers from polar and temperate ecosystems in which lipids are an important source of energy. A key characteristic of QFASA is that the large number of fatty acids that typically comprise lipids permits the dietary contributions of a correspondingly large number of prey types to be estimated. Several modifications to the original QFASA methods have been suggested in the literature and a significant extension of the original model published in 2017 allows simultaneous estimation of both diet proportions and calibration coefficients, which are metabolic constants in the model whose values must otherwise be estimated in independent feeding experiments. However, comparisons of diet estimates obtained using different estimation options have been limited. QFASA has been used to estimate the diet composition of several polar bear (Ursus maritimus) subpopulations, including the Southern Beaufort Sea (SBS) subpopulation. Prior QFASA estimates of SBS polar bear diet composition have most often been obtained using variations of the original QFASA model. We investigated the influence of variations in QFASA analytical methods on diet estimates by re-estimating the diet composition of polar bears from the Alaska portion of the SBS using three different methods and found that differences among the three sets of estimates were substantial. Our results illustrate how important the careful and deliberate selection of QFASA methods can be and we provide some guidance on techniques one might use to evaluate options.

Publication type Article
Publication Subtype Journal Article
Title The importance of method selection when estimating diet composition with quantitative fatty acid signature analysis
Series title PLoS ONE
DOI 10.1371/journal.pone.0308283
Volume 20
Issue 1
Year Published 2025
Language English
Publisher PLoS
Contributing office(s) Alaska Science Center Ecosystems
Description e0308283, 15 p.
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