Effect of diet quality on carbon and nitrogen turnover and isotopic discrimination in blood of a New World nectarivorous bat
Bibliographic record
Abstract
Diet composition of carbon and nitrogen (C:N) could affect diet-tissue isotopic discrimination and elemental turnover rate in consumers but studies that test the nature of these changes are scarce. We compared carbon and nitrogen isotopic discrimination and turnover rates in individuals of Pallas' long-tongued bats Glossophaga soricina fed diets with protein soya isolate or amaranth grains as their main source of protein. Diets were of similar protein biological value but the soya diet had higher nitrogen content (2.2%N) and lower C:N ratio (39.6) than the amaranth diet (1.3%N, C:N=40.5). Most bats on the soya diet gained body mass whereas most bats on the amaranth diet lost body mass. Half-lives of carbon (24.3+/-3.8 days) and nitrogen (25.6+/-4.4 days) in bats switched to the soya diet were very similar. In contrast, in the bats switched to the amaranth diet, carbon half-life (39.7+/-3.4 days) was longer than that of nitrogen (25.0+/-6.0 days). The enrichment in 15N between diet and blood was higher when bats were fed the amaranth diet (4.4+/-0.2 per thousand) than when they were fed the soya diet (3.3+/-0.2 per thousand). Similarly, bats on the amaranth diet had higher 13C enrichment (2.0+/-0.2 per thousand) than bats on the soya diet (0.1+/-0.1 per thousand). Our results support recent hypotheses of the effect of nutrition on diet-tissue isotopic discrimination and turnover rate, and further shows that blood stable isotope analysis is an adequate approach to track seasonal dietary shifts in wild bats.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".