Seasonal paleoecological records from antler collagen δ <sup>13</sup> C and δ <sup>15</sup> N
Bibliographic record
Abstract
Abstract Cervids living in high latitudes have evolved to thrive in ecosystems that experience dramatic seasonal changes. Understanding these seasonal adaptations is important for reconstructing cervid life histories, ecosystem dynamics, and responses in the distant and not-so-distant past to changing seasonality caused by climate change. Cervid antlers provide a rare opportunity for insight into faunal seasonal ecology, as they are grown and shed each year. Stable isotopes of carbon and nitrogen measured directly from antlers have the potential to provide seasonal dietary data for individuals. If the isotopic signals in bone and antler are controlled by the same metabolic processes, then the stable carbon and nitrogen isotope compositions of collagen (δ 13 C Coll and δ 15 N Coll ) from incrementally grown antler tissue provide time-constrained dietary signals from the spring and summer growth season. Bone, by comparison, provides an average signal over several years. The amino acid (glutamate and phenylalanine) δ 15 N in antlers from modern captive caribou showed similar trophic discrimination factors to earlier results for other collagenous tissues (bone, tooth dentin, and cementum). Hence, growth rate was not the primary control on the stable isotope composition of antler collagen. We applied this knowledge to assess seasonal shifts in Quaternary fossils of three Cervidae species: elk ( Cervus elaphus ), moose ( Alces alces ), and caribou ( Rangifer tarandus ). Paired antler–bone δ 13 C Coll and δ 15 N Coll from the same individual were used to identify differences between summer and annual diet and ecology. Intra-antler isotopic variability from serially sampled antlers was used to examine seasonal dietary shifts and specialization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.056 | 0.003 |
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; both teacher heads agree on what is shown here.
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".