Caribou avoiding wolves face increased predation by bears – <scp>C</scp>aught between <scp>S</scp>cylla and <scp>C</scp>harybdis
Notice bibliographique
Résumé
Summary Prey may trade off resource acquisition with mortality risk by using various habitat selection strategies. Empirical assessments have shown that the functional and numerical responses of predators to human disturbances are variable, yet spatial changes in predation risk by two predators have seldom been studied for prey occurring in human‐modified landscapes. Using the boreal caribou Rangifer tarandus caribou – grey wolf Canis lupus – black bear Ursus americanus system in eastern Canada, we investigated whether responses of prey towards one predator could concomitantly increase risk of predation from another predator exhibiting a different foraging tactic. We investigated trade‐offs made by solitary caribou females and mothers accompanied by their calf during the period of highest calf vulnerability and compared the behaviour of mothers that would eventually lose their calf to predation to that of mothers whose calf survived until the following year. We modelled habitat selection using different metrics of forage based on field measurements and digital maps and developed empirical models of predation risk and prey behaviour using GPS data collected on both predators and prey. Mothers accompanied by their calf seemed to compromise foraging opportunities for safety, as opposed to solitary females who showed no particular avoidance of areas used by predators. Although caribou mothers adopted selection strategies that could have protected their offspring from wolves, females that eventually lost their calf to predation selected for vegetative associations that were favourable to bears. Synthesis and applications . We determined that mothers that most strongly avoided suitable wolf habitat were also those that most strongly selected suitable bear habitat, suggesting that by using antipredator strategies aimed at reducing predation risk from wolves, caribou exposed their offspring to increased predation risk from bears. This result is of paramount conservation value as bears were responsible for 94% of caribou calf kills in this system. In the short term, conservation efforts for boreal caribou may benefit from the management of bear populations by means of liberal hunting regulations or predator control. In the long term, however, these actions should be used in conjunction with the protection of potential calving areas away from cutblocks and roads.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».