The effect of successive summer drought periods on bacterial diversity along a plant species richness gradient
Bibliographic record
Abstract
Drought is a major stressor to soil microbial communities, and the intensification of climate change is predicted to increase hydric stress worldwide in the coming decades. As a possible mitigating factor for the consequences of prolonged drought periods, above and belowground biodiversity can increase ecosystem resistance and resilience by improving metabolic redundancy and complementarity as biodiversity increases. Here, we investigated the interaction effect between plant richness and successive, simulated summer drought on soil microbial communities during a period of 9 years.To do that, we made use of a well-established biodiversity experiment (The Jena Experiment) to investigate the response of microbial richness and community composition to successive drought periods alongside a plant richness gradient, which covers 1-, 2-, 4-, 8-, 16-, and 60-species plant communities. Plots were covered from natural precipitation by installing rain shelters 6 weeks every summer. Bulk soil samples were collected 1 year after the last summer drought was simulated. Our data indicate that bacterial richness increased after successive exposure to drought, with the increase being stable along the plant richness gradient. We identified a significant effect of plant species richness on the soil microbial community composition and determined the taxa significantly impacted by drought at each plant richness level. Our data successfully demonstrates that summer drought might have a legacy effect on soil bacterial communities.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".