Biotic and abiotic plant–soil feedback depends on nitrogen‐acquisition strategy and shifts during long‐term ecosystem development
Bibliographic record
Abstract
Abstract Feedback between plants and soil is an important driver of plant community structure, but it remains unclear whether plant–soil feedback (PSF): (i) reflects changes in biotic or abiotic properties, (ii) depends on environmental context in terms of soil nutrient availability, and (iii) varies among plant functional groups. As soil nutrient availability strongly affects plant distribution and performance, soil chemical properties and plant nutrient‐acquisition strategies might serve as important drivers of PSF. We used soils from young and old stages of a long‐term soil chronosequence to represent sites where productivity is limited by nitrogen (N) and phosphorus (P) availability, respectively. We grew three N‐fixing and three non‐N‐fixing plant species in soils conditioned by co‐occurring conspecific or heterospecific species from each of these two stages. In addition, three soil treatments were used to distinguish biotic and abiotic effects on plant performance, allowing measurements of overall, biotic, and abiotic PSF. In young, N‐poor soils, non‐N‐fixing plants grew better in soils from N‐fixing plants than in their own soils (i.e., negative PSF). However, this difference was not only associated with improved abiotic conditions in soils from N‐fixing plants but also with changes in soil biota. By contrast, no significant PSF was observed for N‐fixing plants grown in young soils. Moreover, we did not observe any significant PSF for either N‐fixing or non‐N‐fixing plants growing in old, P‐impoverished soils. Synthesis . The direction and strength of plant‐soil feedback (PSF) varied among N‐acquisition strategies and soils differing in nutrient availability, with stronger plant‐soil feedback in younger, N‐poor soils compared to older, P‐impoverished soils. Our results highlight the importance of considering soil nutrient availability, plant‐mediated abiotic and biotic soil properties, and plant nutrient‐acquisition strategies when studying plant‐soil feedback, thereby advancing our mechanistic understanding of plant‐soil feedback during long‐term ecosystem development.
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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) | 0.001 | 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 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".