RATIONALE: Stable isotopes are a prominent tool in animal ecology where data is obtained from analyzing animal tissues, which are typically stored prior to analysis. However, the effect of decomposition on the reliability of stable isotope ratios from animal tissue prior to storage has been seldom studied. Here, we examine the long-term effects of freezing and decomposition of animal tissue on δ13 C and δ15 N values across three different aquatic species of varying lipid content. METHODS: Ringed seal, lake trout and Greenland shark muscle were divided into different treatment groups and analyzed for their δ13 C values, carbon content (%C), δ15 N values, and nitrogen content (%N) at specific time intervals. The intervals included days 0, 128 and 700 for the frozen storage treatment and at days 0, 1, 2, 4, 8, 16, 32, 64, 128 and 256 for the tissue decomposition treatment in open and closed vials at room temperature. RESULTS: The difference in δ13 C and δ15 N values between the control and days 128 and 700 for the frozen treatment was minimal and not significant for any species. Generally, significant decreases in carbon (%C) and nitrogen (%N) content and significant increases (>0.5‰) in δ13 C and δ15 N values occurred for muscle of each species left to decompose for 256 days, probably due to the preferential uptake of lighter isotopes during decomposition by microbes. However, the magnitude of change in the δ13 C and δ15 N values up to 8 days in both treatments was low (generally ≤0.1‰) and not significant across most species. CONCLUSIONS: Freezing for extended time periods (up to 700 days) is a viable storage technique for stable isotope analysis of aquatic animal muscle tissue across a range of lipid contents. Muscle tissue left to decompose at room temperature showed no significant change in δ13 C and δ15 N values after 8 days, and such tissues would still be reliable for ecological interpretations. However, caution should be used for decomposed tissue for >8 days as the δ13 C and δ15 N values will probably be artificially high.
RATIONALE: Stable isotopes are a prominent tool in animal ecology where data is obtained from analyzing animal tissues, which are typically stored prior to analysis. However, the effect of decomposition on the reliability of stable isotope ratios from animal tissue prior to storage has been seldom studied. Here, we examine the long-term effects of freezing and decomposition of animal tissue on δ13 C and δ15 N values across three different aquatic species of varying lipid content. METHODS:Ringed seal, lake trout and Greenland shark muscle were divided into different treatment groups and analyzed for their δ13 C values, carbon content (%C), δ15 N values, and nitrogen content (%N) at specific time intervals. The intervals included days 0, 128 and 700 for the frozen storage treatment and at days 0, 1, 2, 4, 8, 16, 32, 64, 128 and 256 for the tissue decomposition treatment in open and closed vials at room temperature. RESULTS: The difference in δ13 C and δ15 N values between the control and days 128 and 700 for the frozen treatment was minimal and not significant for any species. Generally, significant decreases in carbon (%C) and nitrogen (%N) content and significant increases (>0.5‰) in δ13 C and δ15 N values occurred for muscle of each species left to decompose for 256 days, probably due to the preferential uptake of lighter isotopes during decomposition by microbes. However, the magnitude of change in the δ13 C and δ15 N values up to 8 days in both treatments was low (generally ≤0.1‰) and not significant across most species. CONCLUSIONS: Freezing for extended time periods (up to 700 days) is a viable storage technique for stable isotope analysis of aquatic animal muscle tissue across a range of lipid contents. Muscle tissue left to decompose at room temperature showed no significant change in δ13 C and δ15 N values after 8 days, and such tissues would still be reliable for ecological interpretations. However, caution should be used for decomposed tissue for >8 days as the δ13 C and δ15 N values will probably be artificially high.
Authors: Matthew J Perkins; Yanny K Y Mak; Lily S R Tao; Archer T L Wong; Jason K C Yau; David M Baker; Kenneth M Y Leung Journal: PLoS One Date: 2018-07-18 Impact factor: 3.240
Authors: Chelsea W Koch; Lee W Cooper; Ryan J Woodland; Jacqueline M Grebmeier; Karen E Frey; Raphaela Stimmelmayr; Cédric Magen; Thomas A Brown Journal: PLoS One Date: 2021-08-19 Impact factor: 3.240