An Investigation of Five Decades of Canid Management Research in the United States and Canada
Notice bibliographique
Résumé
Predator removal has been the dominant method of mitigating predator damage to livestock for centuries in the United States and Canada. The 1970s saw legislative and cultural shifts from predator eradication to selective and non-lethal mitigation strategies. Research concurrently increased and focused on which strategies were effective at reducing livestock depredations. I collected research findings published between 1970 and 2018 on mitigating livestock depredation by coyotes and wolves. I investigated potential issues in this literature with implications for current canid management, such as whether traditional management strategies have been properly evaluated or whether the research endorsed a particular strategy. I also investigated the characteristics of the research over time and whether the research showed evidence of publication bias. Lastly, I evaluated whether the confounding effect of context has been accounted for in the research. I found there were nearly three times as many non-lethal than lethal research findings and twice as many types of non-lethal strategies than lethal strategies. My results also justify the use of producer assessments in future research on mitigating livestock depredations. I found differences in research characteristics, such as the canid species evaluated and how research findings are disseminated, across the five decades between 1970 and 2018. I also report that research quality improved across the five decades as there were fewer lower quality research findings after the 1980s. There was no evidence of traditional success oriented publication bias. I did find evidence that non-success related research characteristics were associated with publication in journals and I termed these relationships ‘non-traditional publication bias’. Research findings that evaluated wolves, had academic Principal Investigators, or used statistical analyses were more likely to be published in journals. My final analysis focused on five contextual factors: historical/concurrent lethal control, wild prey, landscape, season, and anthropogenic characteristics. Research findings did not consistently report contextual information. Similarly, there were only a few instances of authors reporting an effect of contextual factors on their results. Based on the CONSORT checklist used in medical research, I developed guidelines for the reporting of future research to ensure replicability and usability in meta-analyses.
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 | 0,000 | 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 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 ».