Plant diversity enhances the reclamation of degraded lands by stimulating plant–soil feedbacks
Notice bibliographique
Résumé
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. 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. 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. Miscanthus 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 harbour 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. Synthesis and applications . Our findings reveal that highly 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 after contamination. Meanwhile, our results also indicate that some plants such as Miscanthus sinensis and legumes should be preferentially used to establish diverse plant communities for rapid reclamation of degraded lands.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».