Open AccessEstimating δ15N fractionation and adjusting the lipid correction equation using Southern African freshwater fishes
Author(s) -
Geraldine C. Taylor,
Jaclyn M. Hill,
Michelle C. Jackson,
Richard A. Peel,
Olaf L. F. Weyl
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0178047
Subject(s) - trophic level , fractionation , freshwater fish , ecoregion , food web , isotope analysis , δ15n , stable isotope ratio , isotope fractionation , freshwater ecosystem , isotope , δ13c , environmental science , ecology , biology , environmental chemistry , ecosystem , chemistry , fish <actinopterygii> , fishery , chromatography , physics , quantum mechanics
Stable isotope analysis is an important tool for characterising food web structure; however, interpretation of isotope data can often be flawed. For instance, lipid normalisation and trophic fractionation values are often assumed to be constant, but can vary considerably between ecosystems, species and tissues. Here, previously determined lipid normalisation equations and trophic fractionation values were re-evaluated using freshwater fish species from three rivers in the Upper Zambezian floodplain ecoregion in southern Africa. The parameters commonly used in lipid normalisation equations were not correct for the 18 model species (new D and I parameters were estimated as D = 4.46‰ [95% CI: 2.62, 4.85] and constant I = 0 [95% CI: 0, 0.17]). We suggest that future isotopic analyses on freshwater fishes use our new values if the species under consideration do not have a high lipid content in their white muscle tissue. Nitrogen fractionation values varied between species and river basin; however, the average value closely matched that calculated in previous studies on other species (δ 15 N fractionation factor of 3.37 ± 1.30 ‰). Here we have highlighted the need to treat stable isotope data correctly in food web studies to avoid misinterpretation of the data.