CHEMICAL COMPOSITION OF LICK SOILS: FUNCTIONS OF SOIL INGESTION BY FOUR UNGULATE SPECIES
Bibliographic record
Abstract
Perspectives on the importance of natural salt licks to ungulates have been broadened beyond the role of providing sodium. This study examined the chemical compositions of wet and dry licks in north-central British Columbia, and defined the benefits of licks to elk (Cervus elaphus), moose (Alces alces), Stone's sheep (Ovis dalli stonei), and mountain goats (Oreamnos americanus). We analyzed soils for buffering compounds (carbonates) and estimated available elements from extractions with solutions at a low, digestive-tract pH. Even though the 2 types of licks are visually distinct, with different concentrations of chemical components, they serve similar functions as concentrated sources of sodium, carbonates, magnesium, and sulfate. Sodium and sulfate concentrations were typically higher at both wet and dry licks than control sites. Carbonates and magnesium were elevated in soils from dry licks and magnesium also was high in inflow waters to wet licks. We estimated elemental intake by ungulates from the composition of forage samples. Forages used by all 4 ungulate species were too low in sodium to meet requirements. Spring and summer forages contained high potassium levels. Licks in our study, therefore, provide ungulates with supplemental sources of sodium that are particularly beneficial to offset increasing demands during lactation and with carbonates to help stabilize rumen pH after forage changes in spring. Supplemental sources of magnesium may be actively sought by ungulates when high levels of dietary potassium affect absorption. To assess the importance of clay in soils ingested at licks, we determined the clay mineral types at licks and compared the buffering capacity of clay-filled fecal material collected at licks with fecal material collected away from licks. Further studies are needed to define the roles of clay in improving forage palatability and digestibility.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".