A global analysis of bidirectional interactions in alpine plant communities shows facilitators experiencing strong reciprocal fitness costs
Bibliographic record
Abstract
Facilitative interactions are defined as positive effects of one species on another, but bidirectional feedbacks may be positive, neutral, or negative. Understanding the bidirectional nature of these interactions is a fundamental prerequisite for the assessment of the potential evolutionary consequences of facilitation. In a global study combining observational and experimental approaches, we quantified the impact of the cover and richness of species associated with alpine cushion plants on reproductive traits of the benefactor cushions. We found a decline in cushion seed production with increasing cover of cushion-associated species, indicating that being a benefactor came at an overall cost. The effect of cushion-associated species was negative for flower density and seed set of cushions, but not for fruit set and seed quality. Richness of cushion-associated species had positive effects on seed density and modulated the effects of their abundance on flower density and fruit set, indicating that the costs and benefits of harboring associated species depend on the composition of the plant assemblage. Our study demonstrates 'parasitic' interactions among plants over a wide range of species and environments in alpine systems, and we consider their implications for the possible selective effects of interactions between benefactor and beneficiary species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".