Moose calving in boreal forests of Eeyou Istchee, Northern Quebec
Notice bibliographique
Résumé
In boreal forests of the Cree territory of Eeyou Istchee in Northern Quebec, moose are culturally important to Cree harvesters who are concerned about how moose calving is affected by forestry and fire disturbance. The cryptic nature of moose calving behaviour, including its timing, cow-calf interactions, and habitat-specificity, has limited our understanding of moose calving success and its contribution to moose population dynamics. GPS-collars were deployed on 89 female moose over five years, including 8 collars equipped with animal-borne video and environmental data collection systems (AVED-collars), across regions with varying levels of forestry and fire disturbance. The first data chapter assesses moose calving behaviour, through a focus on cow movement patterns, seasonal timing, and cow-calf interactions. We first assessed the accuracy and precision of six movement-based methods typically used to infer calving dates of moose and other ungulates, by comparing calving dates estimated from GPS-collar movement patterns to AVED video observations of calves and calving. Comparisons of 8 females during 12 calving seasons identified three of the six movement-based methods to be both accurate and precise and we used these three movement-based methods to estimate parturition dates for the larger sample of female moose equipped with GPS collars. Moose parturition dates ranged from May 12 to June 23, with more than 70% of births occurring between May 18 and May 26. Classification of videos from AVEDs revealed that females spent more time walking, standing, feeding, and ruminating the day before calving compared to the day after, when they spent more time laying down and licking their calf. Analysis of movement patterns demonstrated that one day before calving, females were located (net square displacement) 2.5 km from their calving site (median; range <0.1-16.5km), then remained highly localized for 7 days post-calving (median 0.2 km; range <0.1-4.9 km). Parturition dates varied slightly between regions, by on average three days, but did not vary between years or according to latitude, longitude, autumn temperature, forestry disturbance, or hunting disturbance. The second data chapter assesses the habitat-specificity and fidelity of calving locations. We compared space use and multi-annual fidelity during a 7-day period following estimated parturition dates to equivalent measures in late winter and summer and evaluated calving site selection comparing the use and availability of terrain, land cover, road density, and fire and forestry disturbance. For the 7-days following parturition, female space use was confined to 0.04 km2 (median; range <0.01 - 10.3 km2), which was equally as small as winter home ranges (0.04 km2, <0.01 – 1.03 km2), but smaller than the summer home ranges (4.97 km2, 0.047 – 270.41 km2) for moose that have annual home ranges of 116.49 km2 (median, range 24.6 - 961.0 km2). Females expressed moderately low calving site fidelity, calving within 4.00 km (median, range 0.35 - 13.54 km) of previously used calving sites, which is not significantly different than summer (median 2.18 km, mean 2.18 km, 0.24 - 4.65 km) and winter fidelity (median 3.65 km, mean 6.36 km, range 0.70 - 21.05 km). Female moose exhibited extensive individual variability in calving site selection, with an overall preference for elevated areas with mixedwood or broadleaf forests and low road densities. Among the subset of moose with forestry or fire disturbance within their annual home range, some females calved in habitats that were 10-15 years post-fire, while all females avoided calving in habitats that had been disturbed by fire or forestry within the last year. Quantifying the timing, movement, fidelity and habitat selection of moose calving informs habitat and wildlife management including long-term impacts of disturbance and environmental change on moose calving sites
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».