Globally, plant‐soil feedbacks are weak predictors of plant abundance
Bibliographic record
Abstract
Abstract Plant‐soil feedbacks (PSFs) have been shown to strongly affect plant performance under controlled conditions, and PSFs are thought to have far reaching consequences for plant population dynamics and the structuring of plant communities. However, thus far the relationship between PSF and plant species abundance in the field is not consistent. Here, we synthesize PSF experiments from tropical forests to semiarid grasslands, and test for a positive relationship between plant abundance in the field and PSFs estimated from controlled bioassays. We meta‐analyzed results from 22 PSF experiments and found an overall positive correlation (0.12 ≤ ≤ 0.32) between plant abundance in the field and PSFs across plant functional types (herbaceous and woody plants) but also variation by plant functional type. Thus, our analysis provides quantitative support that plant abundance has a general albeit weak positive relationship with PSFs across ecosystems. Overall, our results suggest that harmful soil biota tend to accumulate around and disproportionately impact species that are rare. However, data for the herbaceous species, which are most common in the literature, had no significant abundance‐PSFs relationship. Therefore, we conclude that further work is needed within and across biomes, succession stages and plant types, both under controlled and field conditions, while separating PSF effects from other drivers (e.g., herbivory, competition, disturbance) of plant abundance to tease apart the role of soil biota in causing patterns of plant rarity versus commonness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".