Lipid extraction has little effect on the δ<sup>15</sup>N of aquatic consumers
Why this work is in the frame
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Bibliographic record
Abstract
Proper application of stable isotopes (e.g., δ 15 N and δ 13 C) to food web analysis requires an understanding of all nondietary factors that contribute to isotopic variability. Lipid extraction is often used during stable isotope analysis (SIA), because synthesized lipids have a low δ 13 C and can mask the δ 13 C of a consumer's diet. Recent studies indicate that lipid extraction intended to adjust δ 13 C may also cause shifts in δ 15 N, but the magnitude of and reasons for the shift are highly uncertain. We examined a large data set ( n = 854) for effects of lipid extraction (using Bligh and Dyer's [1959] chloroform‐methanol solvent mixtures) on the δ 15 N of aquatic consumers. We found no effect of chemically extracting lipids on the δ 15 N of whole zooplankton, unionid mussels, and fish liver samples, and found a small increase in fish muscle δ 15 N of ~0.4‰. We also detected a negative relationship between the shift in δ 15 N following extraction and the C:N ratio in muscle tissue, suggesting that effects of extraction were greater for tissue with lower lipid content. As long as appropriate techniques such as those from Bligh and Dyer (1959) are used, effects of lipid extraction on δ 15 N of aquatic consumers need not be a major consideration in the SIA of food webs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it