Pulse grazing by reindeer (<i>Rangifer tarandus</i>) can increase the phylogenetic diversity of vascular plant communities in the Fennoscandian tundra
Bibliographic record
Abstract
) grazing on plant biodiversity and community composition in the Fennoscandian tundra are well studied, the impact of reindeer grazing on phylogenetic community structure is not. We used data from a multiyear quasi-experimental study in northern Fennoscandia to analyze the effect of reindeer grazing on plant community diversity including its phylogenetic structure. Our study design used a permanent fence constructed in the 1960s and temporary fences constructed along the permanent fence to expose plant communities to three different grazing regimes: light (almost never grazed), pulse (grazed every other year), and press (chronic grazing for over 40 years). Similar to previous studies on low productivity ecosystems in this region, the species richness and evenness of plant communities with pulse and press grazing did not differ from communities with light grazing. Also consistent with previous studies in this region, we observed a transition from shrub-dominated communities with light grazing to graminoid-dominated communities with pulse and press grazing. Interestingly, communities with pulse, but not press, grazing were more phylogenetically dispersed than communities with light grazing. If grazing pulses can increase the phylogenetic diversity of plant communities, our result suggests changes in reindeer management allowing for pulses of grazing to increase phylogenetic diversity of 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".