Plant diversity enhances rehabilitation of degraded lands by spurring plant-soil feedbacks
Bibliographic record
Abstract
Despite a rich history of theoretical and empirical work showing that increasing biodiversity results in higher ecosystem function, this research has not made a commensurate impact on the reclamation of degraded lands, where enhancing ecosystem function is of primary importance. 2. In this study, we manipulated plant diversity on heavily degraded mine lands and showed that increasing plant diversity greatly enhanced the reclamation of these lands. We found that high diversity assemblages were often associated with more biomass, higher stability and less toxic foliage than low diversity treatments, although the monocultures of Miscanthus sinensis (the most productive species) performed equally well as some of the polycultures. 3. Our results showed that species composition and richness explained most of the total variation in biomass yield of the experimental plots, indicating that both the selection and complementarity effects influenced the positive diversity effects observed in this study. 4. M. sinensis and legumes (as a functional group) were found to be the main contributors to the selection effect. The plots with M. sinensis tended to harbor fewer soil fungal pathogens than those without it and a similar pattern was observed for the legumes, indicating a poorly known plant-soil fungal pathogen feedback for these plants. This kind of feedback appeared to play an important role also in shaping the positive plant species richness-ecosystem function relationships recorded in the degraded mine land. More importantly, we provide the first evidence that the observed plant-soil fungal pathogen feedbacks were likely mediated by chitinolytic bacteria that release anti-fungal enzymes. Cellulose-degrading bacteria that aid in plant decomposition and nutrient cycling also attained higher abundances in plots with higher plant diversity, suggesting the contribution of another kind of plant-soil feedback to the positive diversity effects. 5. Synthesis and applications. Our findings reveal that high diverse plant assemblages are better able to spur plant-soil feedbacks and that increasing plant diversity is an important strategy to enhance land reclamation efficiency. Meanwhile, our results also indicate that some plants such as M. sinensis and legumes should be preferentially used to establish diverse plant communities for rapid reclamation of degraded lands.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".