Effects of forest restoration types on soil quality in red soil eroded region, Southern China
Notice bibliographique
Résumé
Land degradation and restoration is one of the greatest challenges in subtropical hilly regions. In Southern China, the area of hilly red soil region accounts for 2.0×10~6 km~2. During recent decades, as a result of increasing demand for firewood, timber and food——human disturbance has destroyed vegetation in the region. Due to the vegetation destruction, the region was given the name, “red desert”. As a result, restoring vegetation and improving soil quality became urgent affairs of the region. It is very important to explore the effects of forest restoration types on soil quality for the restoration and management of such degraded ecosystems. In this study, four typical forest restoration types in the hilly red soil region were selected at the Ecological Benefit Monitoring Station of the Yangtze River Protection Forest——the hilly red soil region of Southern Hunan Province, which is located in the small valley of Changchong Village, Langlong Country, Hengyang County of Hunan Province. The four types are natural secondary forest, tea-oil camellia plantation, Chinese fir plantation, slash pine plantation, and the control which was frequently disturbed. The paper reports on the responses of the soil's physical, chemical and biological properties to the four forest restoration types. From the results of this study, a soil quality index that integrated 13 soil quality indicators was calculated. In addition, the relationships between the soil's physico-chemical and biological indicators were analyzed. Results showed that: different forest restoration types lead to significant differences in the soil's physico-chemical and biological properties. The soil quality of selected plots was ranked as follows: 1) natural secondary forest 2) tea-oil camellia plantation 3) Chinese fir plantation 4) slash pine plantation 5) control. The indices of soil quality for the natural secondary forest, tea-oil camellia plantation, Chinese fir plantation, slash pine plantation, and control were 0.95, 0.68, 0.55, 0.36 and 0.04, respectively. The control possessed the lowest soil quality. The soil quality under the natural secondary forest was the highest among four forest restoration approaches. Natural restoration was an effective approach to improving soil quality at the early stage of restoring. The factors influencing the soil quality of plantations and the control were inappropriate artificial tending, lower litter fall production and quality, lower microbial structure and function, and nutrients loss. The findings indicate that among the 13 soil quality indicators, microbial biomass carbon, substrate richness index and Shannon's diversity index significantly correlated with other 9, 10, 9 indicators respectively. For selecting the soil quality indicator, the microbial biomass carbon combined with microbial function diversity was the better indicator for reflecting soil biological activity and soil quality.
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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 | 0,001 | 0,001 |
| 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) | 0,000 | 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 ».