Data from: Microhabitat selection by boreal woodland caribou improves access to food
Notice bibliographique
Résumé
Abstract Bio-logging sensors attached to radiotelemetry receivers have great potential to transform our understanding of the ecological, physiological, and energetic constraints that shape patterns of wildlife movement under field conditions. We used video camera collars to assess microhabitat selectivity by woodland caribou (Rangifer tarandus) in boreal forests of Ontario, Canada. Our study areas provided a range of fine-grain microhabitats within forest stands (>10 ha), drawn from an unlogged forest landscape and a partially commercially-logged landscape. We classified ground-truthed samples within each stand into their sub-stand vegetation types at a scale of <10 m radius. We used a resource selection function to evaluate microhabitat selection by caribou, contrasting their selection of vegetation type by season, study area, calf presence, and behaviour, as identified from 17,384 videos from 19 caribou. Most caribou observations were in upland sites in all seasons and caribou showed seasonal selection among the vegetation types. All used sites were dominated either by black spruce (Picea mariana) or jack pine (Pinus banksiana) and all other vegetation types were seldomly used. The only favoured lowland vegetation type was poor lowland (low stocking, wet deep organic soils) and wetland types selected in summer. Caribou with calves did not select vegetation types differently from females without calves, nor did they avoid other caribou. Caribou selected for vegetation types with the greatest amount of lichen and other commonly used food types. While habitat selection at landscape scales is important to avoid predation, the videos enabled an understanding of within stand selection among closely-related forest types, indicating habitat selection occurred at a finer spatial scale for different reasons. This new knowledge is useful for identifying silvicultural practices needed to restore plant communities most strongly selected by caribou across a managed landscape, which would be expected to improve their energetic balance. The data file 'caribou_finegrain_data_RSF.csv' contains the data required to repeat the analysis on microhabitat selection by woodland caribou (Rangifer taranadus) in northern Ontario described in Thompson et al. (2026) by the same authors listed as creators. The 'animalID' column shows the unique animal identifier for each adult female caribou. The 'used' column indicates whether the point was used (1), or available (0). Used points were the vegetation categories identified from video collar recordings and available points were inferred from a combination of remotely sensed and ground collected data using random points within 90% minimum convex polygon seasonal home ranges. Vegetation type was determined by trained observers viewing the video files from video collars and were combinations of categories from a forest ecosystems classification system (Sims et al. 1989). Behaviour represents the primary behaviour displayed within videos for used points, and was randomly assigned to available points. Seasons were defined as winter and non-winter, primarily depending on snow cover, with a more specific definition provided in Thompson et al. (2026). Study areas are show as 'NK' for Nakina, Ontario, and 'PL' for Pickle Lake, Ontario, depending on where each animal was originally captured and fitted with a GPS video collar. References: Sims, R., W. D. Towill, K. A. Baldwin, and G. M Wickware. 1989. Field guide to the forest ecosystem classification for Northwestern Ontario. Forestry Canada and Ontario Ministry of Natural Resources, Forest Resource Development Agreement. Thunder Bay, Ontario. Thompson, I.D., P. A. Wiebe, A. R. Rodgers, D. Reid, J. A. Baker, B. R. Patterson, E. P. McNeill, R. Dejeante, and J. M. Fryxell. (in press). Microhabitat selection by boreal woodland caribou improves access to food. Wildlife Biology
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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 | 0,000 | 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) | 0,003 | 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 ».