Literature DB >> 26443408

Fish tissue lipid-C:N relationships for correcting δ(13) C values and estimating lipid content in aquatic food-web studies.

Joel C Hoffman1, Michael E Sierszen1, Anne M Cotter1.   

Abstract

RATIONALE: Normalizing δ(13) C values of animal tissue for lipid content is necessary to accurately interpret food-web relationships from stable isotope analysis. To reduce the effort and expense associated with chemical extraction of lipids, various studies have tested arithmetic mass balance to mathematically normalize δ(13) C values for lipid content; however, the approach assumes that lipid content is related to the tissue C:N ratio.
METHODS: We evaluated two commonly used models for estimating tissue lipid content based on C:N ratio (a mass balance model and a stoichiometric model) by comparing model predictions to measure the lipid content of white muscle tissue. We then determined the effect of lipid model choice on δ(13) C values normalized using arithmetic mass balance. To do so, we used a collection of fish from Lake Superior spanning a wide range in lipid content (5% to 73% lipid).
RESULTS: We found that the lipid content was positively related to the bulk muscle tissue C:N ratio. The two different lipid models produced similar estimates of lipid content based on tissue C:N, within 6% for tissue C:N values <7. Normalizing δ(13) C values using an arithmetic mass-balance equation based on either model yielded similar results, with a small bias (<1‰) compared with results based on chemical extraction.
CONCLUSIONS: Among-species consistency in the relationship between fish muscle tissue C:N ratio and lipid content supports the application of arithmetic mass balance to normalize δ(13) C values for lipid content. The uncertainty associated with both lipid extraction quality and choice of model parameters constrains the achievable precision of normalized δ(13) C values to about ±1.0‰. Published in 2015. This article is a U.S. Government work and is in the public domain in the U.S.A.

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Year:  2015        PMID: 26443408     DOI: 10.1002/rcm.7367

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  8 in total

1.  Relative contributions of nearshore and wetland habitats to coastal food webs in the Great Lakes.

Authors:  Michael E Sierszen; Lee S Schoen; Jessica M Kosiara; Joel C Hoffman; Matthew J Cooper; Donald G Uzarski
Journal:  J Great Lakes Res       Date:  2019       Impact factor: 2.480

2.  Using carbon, nitrogen, and mercury isotope values to distinguish mercury sources to Alaskan lake trout.

Authors:  Ryan F Lepak; Jacob M Ogorek; Krista K Bartz; Sarah E Janssen; Michael T Tate; Yin Runsheng; James P Hurley; Daniel B Young; Collin A Eagles-Smith; David P Krabbenhoft
Journal:  Environ Sci Technol Lett       Date:  2022-03-21

3.  Geography, not human impact, is the predominant predictor in a 150-year stable isotope fish record from the coastal United States.

Authors:  Autumn Oczkowski; Betty Kreakie; M Nicole Gutierrez; Marguerite Pelletier; Mike Charpentier; Emily Santos; John Kiddon
Journal:  Ecol Indic       Date:  2020-04       Impact factor: 4.958

4.  Influence of demographics, exposure, and habitat use in an urban, coastal river on tumor prevalence in a demersal fish.

Authors:  Joel C Hoffman; Vicki S Blazer; Heather H Walsh; Cassidy H Shaw; Ryan Braham; Patricia M Mazik
Journal:  Sci Total Environ       Date:  2020-01-07       Impact factor: 7.963

Review 5.  Does lipid-correction introduce biases into isotopic mixing models? Implications for diet reconstruction studies.

Authors:  Martin C Arostegui; Daniel E Schindler; Gordon W Holtgrieve
Journal:  Oecologia       Date:  2019-10-30       Impact factor: 3.225

6.  Examining historical mercury sources in the Saint Louis River estuary: How legacy contamination influences biological mercury levels in Great Lakes coastal regions.

Authors:  Sarah E Janssen; Joel C Hoffman; Ryan F Lepak; David P Krabbenhoft; David Walters; Collin A Eagles-Smith; Greg Peterson; Jacob M Ogorek; John F DeWild; Anne Cotter; Mark Pearson; Michael T Tate; Roger B Yeardley; Marc A Mills
Journal:  Sci Total Environ       Date:  2021-03-13       Impact factor: 10.753

7.  Mercury source changes and food web shifts alter contamination signatures of predatory fish from Lake Michigan.

Authors:  Ryan F Lepak; Joel C Hoffman; Sarah E Janssen; David P Krabbenhoft; Jacob M Ogorek; John F DeWild; Michael T Tate; Christopher L Babiarz; Runsheng Yin; Elizabeth W Murphy; Daniel R Engstrom; James P Hurley
Journal:  Proc Natl Acad Sci U S A       Date:  2019-11-04       Impact factor: 11.205

8.  Foraging Ecology Differentiates Life Stages and Mercury Exposure in Common Terns (Sterna hirundo).

Authors:  Annie M Bracey; Matthew A Etterson; Frederick C Strand; Sumner W Matteson; Gerald J Niemi; Francesca J Cuthbert; Joel C Hoffman
Journal:  Integr Environ Assess Manag       Date:  2020-10-29       Impact factor: 3.084

  8 in total

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