Determining the appropriate pretreatment procedures and the utility of liver tissue for bulk stable isotope (<scp>δ<sup>13</sup>C</scp> and <scp>δ<sup>15</sup>N</scp>) studies in sharks
Bibliographic record
Abstract
Abstract Stable‐isotope analysis (SIA) provides a valuable tool to address complex questions pertaining to elasmobranch ecology. Liver, a metabolically active, high turnover tissue (~166 days for 95% turnover), has the potential to reveal novel insights into recent feeding/movement behaviours of this diverse group. To date, limited work has used this tissue, but ecological application of SIA in liver requires consideration of tissue preparation techniques given the potential for high concentrations of urea and lipid that could bias δ13C and δ15N values (i.e., result in artificially lower δ13C and δ15N values). Here we investigated the effectiveness of (a) deionized water washing (WW) for urea removal from liver tissue and (b) chloroform‐methanol for extraction of lipids from this lipid rich tissue. We then (a) established C:N thresholds for deriving ecologically relevant liver isotopic values given complications of removing all lipid and (b) undertook a preliminary comparison of δ13C values between tissue pairs (muscle and liver) to test if observed isotopic differences correlated with known movement behaviour. Tests were conducted on four large shark species: the dusky (DUS, Carcharhinus obscurus), sand tiger (RAG, Carcharias taurus), scalloped hammerhead (SCA, Sphyrna lewini) and white shark (GRE, Carcharodon carcharias). There was no significant difference in δ15N values between lipid‐extracted (LE) liver and lipid‐extracted/water washed (WW) treatments, however, WW resulted in significant increases in %N, δ13C and %C. Following lipid extraction (repeated three times), some samples were still biased by lipids. Our species‐specific “C:N thresholds” provide a method to derive ecologically viable isotope data given the complexities of this lipid rich tissue (C:N thresholds of 4.0, 3.6, 4.7 and 3.9 for DUS, RAG, SCA and GRE liverLEWW tissue, respectively). The preliminary comparison of C:N threshold corrected liver and muscle δ13C values corresponded with movement/habitat behaviours for each shark; minor differences in δ13C values were observed for known regional movements of DUS and RAG (δ13CDiffs = 0.24 ± 0.99‰ and 0.57 ± 0.38‰, respectively), while SCA and GRE showed greater differences (1.24 ± 0.63‰ and 1.08 ± 0.71‰, respectively) correlated to large‐scale movements between temperate/tropical and pelagic/coastal environments. These data provide an approach for the successful application of liver δ13C and δ15N values to examine elasmobranch ecology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".