Two alternatives to the stress‐gradient hypothesis at the edge of life: the collapse of facilitation and the switch from facilitation to competition
Bibliographic record
Abstract
Abstract New evidence demonstrates that facilitation plays a crucial role even at the edge of life in Maritime Antarctica. These findings are interpreted as support for the stress‐gradient hypothesis ( SGH ) – a dominant theory in plant community ecology that predicts that the frequency of facilitation directly increases with stress. A recent development to this theory, however, proposed that facilitation often collapses at the extreme end of stress and physical disturbance gradients. In this paper, we clarify the current debate on the importance of plant interactions at the edge of life by illustrating the necessity of separating the two alternatives to the SGH , namely the collapse of facilitation, and the switch from facilitation to competition occurring in water‐stressed ecosystems. These two different alternatives to the SGH are currently often amalgamated with each other, which has led to confusion in recent literature. We propose that the collapse of facilitation is generally due to a decrease in the effect of the nurse plant species, whilst the switch from facilitation to competition is driven by environmental conditions and strategy of the response species. A clear separation between those two alternatives is particularly crucial for predicting the role of plant–plant interactions in mediating species responses to global change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".