Elemental Composition of Reindeer Pasture Plants and Lichens in Nadym District (Yamal-Nenets Autonomous Area)
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Bibliographic record
Abstract
Abstract—There are plans to expand reindeer husbandry in the Nadym District of the Yamal-Nenets Autonomous Area. For this purpose, we studied the elemental composition of the dominant species of the tundra and open boreal woodland vegetation cover. We analyzed leaves of dwarf birch (Betula nana L.), dwarf shrubs of bog blueberry (Vaccinium uliginosum L.), marsh Labrador tea (Ledum palustre L.), and leatherleaf (Chamaedaphne calyculata (L.) Moench); sphagnum moss (Sphagnum sp. L.); and fruticose lichens (Cladina stellaris (Opiz.) Brodo). The X-ray fluorescence analysis was used to obtain data on the content of Ca, K, P, Si, Mg, Na, S, Zn, Cu, Ni, Co, Fe, Mn, Cr, Ti, and Al. We defined the biogeochemical features of the reindeer forage plants. In vascular plants and sphagnum mosses, the content of almost all essential macroelements is low, while the content of most microelements (Cu, Ni, Co, Cr, and Mn) exceeds the world average values. The lichens are characterized by low concentration of Ca, K, Mg, and P, which is more than one order of magnitude lower than the world average values, and the deficiency of microelements. The results were compared with the results from similar studies in other geographical regions of the tundra zone, and it was found that tundra plants have a similar pattern of element accumulation. In particular, leaves of dwarf birch are distinguished by accumulation of Mg; the content of Al, Fe, and Si is increased in mosses; Mn is accumulated in dwarf shrubs and dwarf birch; lichens are characterized by the deficiency of most elements. Therefore, in order to prevent animal diseases, it is necessary to improve the elemental composition of reindeers feed by increasing the share of “green” forage in winter, when lichens dominate the diet.
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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 | 0.000 |
| 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) | 0.000 | 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 it