A living inventory of planted trees in South Africa derived from iNaturalist
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Notice bibliographique
Résumé
• South Africa has a long history of introduction of trees from other parts of the world, starting with introductions in the mid-17th century. • Planted trees (both native and non-native) now dominate treescapes in many part of the country, especially in urban ecosystems. • Although planted trees are a key component of South Africa's green infrastructure and provide diverse ecosystem services, no up-date list of planted tree species exists. • This study used the citizen science platform iNaturalist to compile a spatially-explicit “living inventory” of planted tree species for South Africa. • The planted tree flora of South Africa comprises over 35,000 records of 805 taxa, 79 % of which are non-native. Over a third these taxa belong to three families: Fabaceae, Myrtaceae and Arecaceae. • Examples are provided of uses of the inventory for managing diverse aspects of South Africa's treescapes, including for monitoring the emergence of new invasions. Trees have a multifaceted influence on ecosystems globally. Treescapes have been manipulated by humans over millennia for ecological, economic, and cultural reasons that have changed over time and continue to change. In South Africa tree planting over three centuries has radically affected the composition of treescapes, contributing important ecosystem services, but also disservices. Rapid global change calls for diverse interventions to create more resilient ecosystems. Many nature-based solutions involve manipulating tree cover in rural and urban landscapes. There is a need for a spatially-explicit database of planted trees in South Africa to serve as the foundation for policy and management decisions. We used the community science platform iNaturalist to create a comprehensive database of planted trees in South Africa. Records were carefully checked to verify the accuracy of taxon identifications, locality data, and categorization as planted rather than wild-growing trees. The cleaned database contained 35,303 records of 805 planted tree taxa; over 90 % of records were identified to species level. Almost a third of taxa (32.2 %) belong to three families: Fabaceae (97 taxa), Myrtaceae (80 taxa) and Arecaceae (78 taxa). Rarefaction and extrapolation curves suggest fairly comprehensive sampling, but several regions are under-sampled. Non-native taxa dominate, with Melaleuca viminalis having the most records. The Western Cape has the highest number of records and taxa, particularly in urban areas. Both native and non-native trees provide key ecosystem services, but non-natives dominate. The database provides the first spatially-explicit open-access resource for guiding decisions on tree planting and the management of planted trees in South Africa. It offers a snapshot of tree planting trends, predominantly from recent years, leading to some underrepresentation of historically planted species. The database has numerous potential uses, including guiding management of trees pests and diseases, urban greening initiatives, monitoring for new invasions, and planning nature-based solutions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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