Stable Isotopes and Radiocarbon Assess Variable Importance of Plants and Fungi in Diets of Arctic Ground Squirrels
Bibliographic record
Abstract
Arctic ground squirrels (Urocitellus parryii) rely primarily on dietary protein derived from plants to fuel gluconeogenesis during hibernation, yet fungal sporocarps may be an important, yet overlooked, protein source. Fungivory levels depend on sporocarp productivity, which varies with the dominant plant species and is higher on acidic than on non-acidic soils. To test whether these factors altered fungal consumption, we used stable isotopes to investigate arctic ground squirrel diets at two sites in northern Alaska, Toolik (primarily moist acidic tundra) and Atigun (primarily moist non-acidic tundra). Radiocarbon estimates can also indicate fungivory levels because ectomycorrhizal fungi assimilate soil-derived organic nitrogen whose 14C levels are higher than current photosynthesis. We measured radiocarbon in hair and δ13C and δ15N in hair, feces, ectomycorrhizal sporocarps, graminoids, and dicots. Feces were higher in δ13C and δ15N at Toolik than at Atigun, and fecal δ15N increased in August at Toolik, coincident with sporocarp production and fungal spores in feces. Mixing models indicated that graminoids contributed 64%, dicots 35%, and sporocarps 1% to Atigun hair protein, whereas graminoids contributed 37%, dicots 16%, and sporocarps 47% to Toolik hair protein. Acidic soils appeared to correlate with higher sporocarp production and fungivory at Toolik than at Atigun. Atigun hair resembled atmospheric CO2 in 14C, whereas Toolik hair had higher 14C, consistent with greater fungal consumption at Toolik. Late-season sporocarps may be a key protein source for some squirrels and may provide an integrated signal of the soil organic nitrogen assimilated by ectomycorrhizal fungi.
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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 | 0.003 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".