Regional variation in mineral contents of plants and its significance for migration by Arctic reindeer and caribou.
Bibliographic record
Abstract
Ten minerals, 6 macro (Na, K, Ca, P, Mg, Cl) and 4 trace elements (Co, Cu, Mo, Mn), were analysed in 13 forage plants of reindeer and caribou (Rangifer tarandus) to compare differences between coastal and interior areas. Samples were collected in northern Norway (coastal and interior regions), southern Norway (interior), and Alaska, USA (interior). We tested the hypothesis that the domestic herding practice of moving reindeer to spring-summer pasture on the coast is to allow reindeer to make up mineral balances that are negative during winter. This hypothesis was supported by data for Na and Cl, which were higher in 12 of 13 forage plants from the coastal region compared with inland areas. Analyses of other minerals, however, indicated a higher variability among plants than between regions. Aquatic plants from the coast and inland were higher in Na and Cl that terrestrial species. A high concentration of Co in willows was independent of region. Graminoids were low in Na and Cl, independent of region. Lichens were low in all macro minerals but were high in trace minerals. This study supported hypotheses based on salt hunger; namely, that the primary reason to move in coastal regions was to compensate for Na deficiency in winter. We suggest this movement also would maximize milk synthesis, which would otherwise be limited because of high Na content of reindeer milk. Selective foraging within coastal vegetation allows animals to meet requirements of macrominerals. Selective use of willows not only supports the high protein requirements of lactation and growth, but an adequate Co intake is required for synthesis of vitamin B12, critical for animal growth and rapid development of rumen function in young reindeer and caribou.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".