Wolf attacks on humans: an update for 2002–2020
Notice bibliographique
Résumé
Linnell, J. D. C., Kovtun, E. & Rouart, I. 2021. Wolf attacks on humans: an update for 2002–2020. NINA Report 1944. Norwegian Institute for Nature Research.\nThe degree to which wolves pose a threat to human safety has been a central part of the public controversy surrounding wolf recovery in Europe for the last three decades. This report seeks to update our knowledge for the period 2002 to 2020. We searched the peer-reviewed literature, technical reports, online news media sources and contacted regional experts to gather as much information as possible. Our coverage for Europe and North America is likely to be high, but for the rest of Eurasia we have at best found a good sample of events, especially for the period after 2015. We identified relatively reliable cases involving 491 human victims. Of these 67 were victims of predatory attacks (9 fatal), 382 were victims of rabid attacks (14 fatal), and 42 were victims of provoked / defensive attacks (3 fatal). Attacks were found in Canada, USA, Croatia, Poland, Italy, Iran, Iraq, Israel, India, Kirgizstan, Turkey, Kazakhstan, Ukraine, Belarus, Moldova, Russia, Mongolia, Armenia, Azerbaijan, Tajikistan and Saudi Arabia. In addition, we found an almost equal number of cases that we could not include because of poor documentation as well as cases that we could clearly reject based on evidence, for example where the attack was actually caused by dogs.\nThe distribution of attacks by rabid wolves closely follows the distribution of rabies cases in humans and other wildlife species. As such this represents a very low risk for Europe due to the near eradication of rabies. The predatory attacks had move diverse etiology. Some clusters, such as those from western Iran, appeared to be linked to landscapes with low wild prey density, high density of humans living in poor socio-economic conditions, and where livestock were the main prey of wolves. A single case appeared to be due to an injured wolf in poor health. A range of other cases though were associated with situations where wolves had been demonstrating fearless behaviour and had been utilising anthropogenic food sources over time before the attacks. Such cases represent a close parallel to the risk factors that are known from other large canids like coyotes in North America and dingoes in Australia. Finally, a single and well-documented fatal attack from Alaska involved a group of healthy wolves in an area with no previous history of fearless wolves or feeding.\nThere is an urgent need to learn more about the behaviour of “bold” or “fearless” wolves and understand at what point a harmless degree of habituation to humans (which is necessary to live in human-dominated landscapes) can lead to potentially dangerous behaviour. There is also a need to develop clear management procedures to both prevent dangerous situations from developing (i.e. feeding) and to react to such situations when they appear. Finally, there is a need for increased communication and awareness raising in this area, both to the public and to medical, veterinary and wildlife management institutions. As our understanding of wolf attacks increases there appears to be a high degree of convergence with the much better understood risks associated with bears, which allows for a more consistent multi-species communication strategy.\nWhile being aware of the potential risks associated with wolves it is also crucial to place this into context. In Europe and North America we only found evidence for 11 attacks, of which 2 (both in North America) were fatal, across a period of 18 years. Considering that there are close to 60.000 wolves in North America and 15.000 in Europe, all sharing space with hundreds of millions of people it is apparent that the risks associated with a wolf attack are above zero, but far too low to calculate.
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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 | 0,001 | 0,001 |
| 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) | 0,009 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».