Macrofauna-environment interactions and their potential in restoring degraded landscapes in the context of Sub-Saharan Africa: A review of current knowledge
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Notice bibliographique
Résumé
Restoring degraded landscapes, such as those induced by mining activity, is essential for recovering lost ecosystem services. This requires innovative nature-based solutions, especially in sub-Saharan Africa (SSA). This review summarizes current knowledge on soil macrofauna in degraded SSA landscapes, an otherwise overlooked component of ecological restoration. A systematic literature review was conducted, yielding 31 relevant publications that were analyzed to identify patterns in macrofauna assemblages across land-use types in SSA including agricultural, forest, bushland, grassland, savannah, dumpsite and reclaimed mine site landscapes. Bibliometric analysis showed minimal studies before 2014, with research increasing after 2017, mostly in southern and eastern Africa. West Africa remains underrepresented. We found more studies on agricultural systems type (28 of the 32 reviewed studies), reporting seven classes, while less studies were conducted on mining wasteland (3 of 31 reviewed studies) reporting only one class. This highlights the urgent need for more macrofauna research in mine wastelands to pursue restoration. Variations in macrofauna composition (at both class and order level) are also viewed in relation to their physiological and environmental plasticity adaptations. In addition, potential macrofauna functional roles, such as bioturbation, organic matter breakdown, nutrient cycling, as well as other attributes such as tolerance to harsh environments and bioindication of biodiversity recovery, that may support landscape restoration were considered as well. Macrofauna groups with potential in future bioaugmentation strategies (the deliberate introduction of beneficial soil organisms to enhance ecological functions) include earthworms (Oligochaeta), termites (Isoptera) and ants (Hymenoptera: Formicidae). Opportunities and challenges of their integration into restoration planning are also discussed, especially in the context of SSA mining landscapes, which are often characterized by severe ecological degradation such as surface water contamination and heavy metal pollution. Although there is a gradual increase in publications on macrofauna in Southern Africa, their practical inclusion in ecological restoration efforts across SSA remains limited. The lack of a better understanding of macrofauna tolerance mechanisms, particularly to environmental stressors such as temperature fluctuations, chemical pollution, and habitat alterations, and the precise nature of their interactions with both biotic and abiotic environmental factors is identified as an avenue for future investigations.
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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) | 0,000 | 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 découle