4.4 Article

Carbon:nitrogen ratio as a proxy for tissue nonpolar lipid content and condition in black sea bass Centropristis striata along the Middle Atlantic Bight

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MARINE BIOLOGY
卷 167, 期 6, 页码 -

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SPRINGER HEIDELBERG
DOI: 10.1007/s00227-020-03688-9

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  1. NOAA project [NA15NMF4270289]
  2. Chesapeake Biological Laboratory Graduate Education Committee

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Spatial and temporal variability in fish tissue lipid content may reflect resource availability, reproductive or maturity state, or environmental suitability. Here, we analyzed nonpolar (storage) lipid and morphometric condition indices of black sea bass (Centropristis striata) collected from coastal waters of the Northwest Atlantic Ocean from New Jersey to North Carolina, USA. We hypothesized that the elemental ratio of carbon to nitrogen (C:N) within C. striata white muscle and liver tissue would be a robust proxy for nonpolar lipid content (NPLC) and that NPLC would predictably covary with traditional condition indices. Further, we analyzed our NPLC tissue indices to determine how regional and biological patterns in muscle and liver NPLC aligned with traditional condition indices. Our results indicated that muscle tissue NPLC was low compared to liver tissue, and regression analysis revealed strong positive relationships between C:N and NPLC for both tissues (muscle-best fit was linear; liver-best fit was asymptotic nonlinear). Correlations of muscle and liver NPLC with other condition indices were index and region dependent (e.g., a reproductive index was positively correlated with muscle NPLC, but negatively correlated with liver NPLC). Tissue NPLC and standard condition indices differed significantly as a function of region, sex, and fish length, although the patterns were not consistent across the different indices. Our results support the use of muscle and liver C:N values to estimate tissue-specific C. striata NPLC. Further, our results indicate that NPLC indices provide additional insight into C. striata physiological condition and could assist studies examining habitat suitability across large spatial or temporal scales.

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