Prevailing Negative Soil Biota Effect and No Evidence for Local Adaptation in a Widespread Eurasian Grass
Bibliographic record
Abstract
BACKGROUND: Soil biota effects are increasingly accepted as an important driver of the abundance and distribution of plants. While biogeographical studies on alien invasive plant species have indicated coevolution with soil biota in their native distribution range, it is unknown whether adaptation to soil biota varies among populations within the native distribution range. The question of local adaptation between plants and their soil biota has important implications for conservation of biodiversity and may justify the use of seed material from local provenances in restoration campaigns. METHODOLOGY/PRINCIPAL FINDINGS: We studied soil biota effects in ten populations of the steppe grass Stipa capillata from two distinct regions, Europe and Asia. We tested for local adaptation at two different scales, both within (ca. 10-80 km) and between (ca. 3300 km) regions, using a reciprocal inoculation experiment in the greenhouse for nine months. Generally, negative soil biota effects were consistent. However, we did not find evidence for local adaptation: both within and between regions, growth of plants in their 'home soil' was not significantly larger relative to that in soil from other, more distant, populations. CONCLUSIONS/SIGNIFICANCE: Our study suggests that negative soil biota effects can prevail in different parts of a plant species' range. Absence of local adaptation points to the possibility of similar rhizosphere biota composition across populations and regions, sufficient gene flow to prevent coevolution, selection in favor of plasticity, or functional redundancy among different soil biota. From the point of view of plant--soil biota interactions, our findings indicate that the current practice of using seeds exclusively from local provenances in ecosystem restoration campaigns may not be justified.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".