Reindeer grazing reduces seed and propagule bank in the High Arctic
Bibliographic record
Abstract
It is commonly assumed that plant establishment in the High Arctic is limited by severe abiotic conditions and by a paucity of propagules and seeds. Heavy reindeer grazing may reduce plant allocation to reproduction and removes significant proportions of flowers and seeds, thus reducing contributions to seed rain and seed bank. In contrast, foraging and trampling may break up existing mature plants, increasing the vegetative propagules in the soil. To determine the effect of grazing on colonization potential in the High Arctic, two studies were carried out: (i) a comparison of seed bank inside and outside three long-term reindeer ( Rangifer tarandus platyrhnchus (Vrolic)) exclosures and (ii) an investigation of the germinable seed and propagule bank of two neighbouring peninsulas with contrasting reindeer grazing history in northwestern Svalbard (79°N, 12°E). Seed banks inside reindeer exclosures germinated significantly more seedlings (596 seedlings·m–2) than those outside (263 seedlings·m–2). Species composition and total plant cover was similar on both peninsulas, but forage-plant cover was lower on the heavily grazed peninsula (Brøggerhalvøya) than on the adjacent lightly grazed peninsula (Sarsøyra). Brøggerhalvøya had significantly lower species richness and density of seed and propagule bank (0.21 ± 0.02 germinating species per sample, 0.15 ± 0.02 propagule species per sample, 416 ± 103 seedlings·m–2, 283 ± 78 propagules·m–2) than did Sarsøyra (0.44 ± 0.40 germinating species per sample, 0.35 ± 0.03 propagule species per sample,1016 ± 188 seedlings·m–2, 782 ± 238 propagules·m–2). These results imply that reindeer depleted both the seed and the propagule banks, thus reducing the potential for colonization of disturbed areas. Grazing may, therefore, have a lasting impact on High Arctic plant communities.
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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 | 0.000 | 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) | 0.001 | 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".