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Record W1946897962 · doi:10.1139/z11-073

Arctic herbivore diet can be inferred from stable carbon and nitrogen isotopes in C<sub>3</sub> plants, faeces, and wool

2011· article· en· W1946897962 on OpenAlexvenueno aff
D. Kristensen, Erik Kristensen, Mads C. Forchhammer, Anders Michelsen, Niels Martin Schmidt

Bibliographic record

VenueCanadian Journal of Zoology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsHerbivoreBiologyArcticWoolStable isotope ratioFecesIsotopes of nitrogenEcologyNitrogenδ15NIsotopes of carbonCarbon fibersEnvironmental chemistryδ13CTotal organic carbon

Abstract

fetched live from OpenAlex

The use of stable isotopes in diet analysis usually relies on the different photosynthetic pathways of C 3 and C 4 plants, and the resulting difference in carbon isotope signature. In the Arctic, however, plant species are exclusively C 3 , and carbon isotopes alone are therefore not suitable for studying arctic herbivore diets. In this study, we examined the potential of both stable carbon and nitrogen isotopes to reconstruct the diet of an arctic herbivore, here the muskox ( Ovibos moschatus (Zimmermann, 1780)), in northeast Greenland. The isotope composition of plant communities and functional plant groups was compared with those of muskox faeces and shed wool, as this is a noninvasive approach to obtain dietary information on different temporal scales. Plants with different root mycorrhizal status were found to have different δ 15 N values, whereas differences in δ 13 C, as expected, were less distinct. As a result, our examination mainly relied on stable nitrogen isotopes. The interpretation of stable isotopes from faeces was difficult because of the large uncertainty in diet–faeces fractionation, whereas isotope signatures from wool suggested that the muskox summer diet consists of around 80% graminoids and up to 20% willows. In conclusion, the diet composition of an arctic herbivore can indeed be inferred from stable isotopes in arctic areas, despite the lack of C 4 plants.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.184
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations66
Published2011
Admission routes1
Has abstractyes

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