Using winter diet composition and forage plant availability to determine browse selection and importance for moose (<i>Alces alces</i>) in a landscape modified by industrial forestry
Notice bibliographique
Résumé
Abstract Between 2000 and 2015, moose (Alces alces L.) populations within some areas of north-central British Columbia, Canada declined by 70%. Such declines are occurring in other regions within the range of moose. One cause for mortalities of cow and calf moose in British Columbia was apparent starvation, implying a potential connection to food supply. To investigate possible connections between moose declines and industrial forestry, we examined moose winter diets relative to browse availability in six Biogeoclimatic Ecosystem Classification subzones within north-central British Columbia. In the spring of 2017, we collected moose winter pellets. To assess diet, pellets were analyzed using microhistology, a common technique for quantifying the diets of ungulates. In the summer of 2018, we used a modified point-intercept method to survey browse plant availability at pellet collection sites. We related diet composition to plant availability through indices of selection (use of a forage species relative to availability) and values of importance (the proportion of a species in the diet as a function of its occurrence in the environment) of various browse items to moose. Twenty-eight species of potential browse plants were identified in our browse availability surveys. Only 12 of these plants were found in moose pellets, with four plants [subalpine fir (Abies lasiocarpa Hooker), willow (Salix spp. Linnaeus), paper birch (Betula papyrifera Marshall), and trembling aspen (Populus tremuloides Michaux)] comprising the majority (93.3%) of the diet. We used mixed-model analyses to examine differences between these top four winter diet items, in relation to: (i) diet composition; (ii) plant availability; (iii) selection by moose; and (iv) importance to moose. Subalpine fir (mean: 45.7%) was a significantly larger diet component in pellets than aspen (5.7%) and willow (19.5%), but there was no significant difference in the proportions of subalpine fir and birch (22.4%). Birch and willow were found in significantly higher proportions than aspen, but proportions of birch and willow in pellets did not differ. The availability of the top four diet items was not significantly different between species. Subalpine fir, aspen, birch, and willow were the most selected diet items, but selection was not significantly different between them. The importance values of subalpine fir, birch, and willow were not significantly different from one another, but all three were significantly greater than the importance value for aspen. Diet composition, availability, selection, and importance did not vary between subzones surveyed. The high selection for and importance of subalpine fir, birch, willow, and aspen by moose in winter demonstrate the need to ensure these browse species are maintained on moose ranges, especially where moose populations are declining. Where industrial forestry impacts the abundance and species composition of winter browses for moose, we encourage forest planners and managers to examine browse availability in relation to moose diet, so that the browse plants important to and selected for by moose can be integrated into forest management objectives.
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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 | 0,000 |
| 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 | 0,001 | 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 ».