A systematic review of the recent ecological literature on cushion plants: champions of plant facilitation
Bibliographic record
Abstract
Abstract. Cushion-forming plant species are found in alpine and polar environments around the world. They modify the microclimate, thereby facilitating other plant species. Similar to the effectiveness of shrubs as a means to study facilitation in arid and semi-arid environments, we explore the potential for cushion plant species to expand the generality of research on this contemporary ecological interaction. A systematic review was conducted to determine the number of publications and citation frequency on relevant ecological topics whilst using shrub literature as a baseline to assess relative importance of cushions as a focal point for future ecological research. Although there are forty times more shrub articles, mean citations per paper is comparable between cushion and shrub literature. Furthermore, the scope of ecological research topics studied using cushions is broad including facilitation, competition, environmental gradients, life history, genetics, reproduction, community, ecosystem and evolution. The preliminary ecological evidence to date also strongly suggests that cushion plants can be keystone species in their ecosystems. Hence, ecological research on net interactions including facilitation and patterns of diversity can be successfully examined using cushion plants, and this is particularly timely given expectations associated with a changing climate in these regions.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".