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
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".