Assessing the Value of the Umbrella‐Species Concept for Conservation Planning with Meta‐Analysis
Notice bibliographique
Résumé
The umbrella-species concept, which suggests that conservation strategies designed for one species may benefit co-occurring species, has been promoted as a framework for conservation planning. Nevertheless, there has been considerable variation in the outcome of empirical tests of this concept that has led researchers to question its value, so we used data from 15 published studies in a meta-analysis to evaluate whether conservation of putative umbrella species also conserves co-occurring species. We tested the effectiveness of putative umbrella species categorized by taxonomic group, taxonomic similarity to co-occurring species, body size, generality of resource use, and trophic level to evaluate criteria proposed to guide the selection of umbrella species. We compared species richness and number of individuals (by species and higher taxonomic group) between sites with and without putative umbrella species to test whether more co-occurring species were present in greater abundances when the area or resource needs of umbrella species were met. Species richness and abundance of co-occurring species were consistently higher in sites where umbrella species were present than where they were not and for conservation schemes with avian than with mammalian umbrella species. There were no differences in species richness or species abundance with resource generalist or specialist umbrella species or based on taxonomic similarity of umbrella and co-occurring species. Taxonomic group abundance was higher in across-taxonomic umbrella species schemes than when umbrella species were of the same taxon as co-occurring species. Co-occurring species had similar, or higher, species richness with small-bodied umbrella species relative to larger-bodied umbrella species. The only significant difference among umbrella species categorized by trophic level was that species richness was higher with omnivorous than it was with carnivorous avian umbrella species. Our results suggest there is merit to the umbrella-species concept for conservation, but they do not support the use of the criteria we used to identify umbrella species.
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.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».