Female Moose Prioritize Forage Over Mortality Risk in Harvested Landscapes
Bibliographic record
Abstract
ABSTRACT Since 2010, several moose ( Alces alces ) populations have declined across North America. These declines are believed to be broadly related to climate and landscape change. At the western reaches of moose continental range, in the interior of British Columbia, Canada, wildlife managers have reported widespread declines of moose populations. Disturbances to forests from a mountain pine beetle ( Dendroctonum ponderosae ) outbreak and associated salvage logging infrastructure in British Columbia are suspected as a mechanism manifested in moose behavior and habitat selection. We examined seasonal differences in moose habitat selection in response to landscape change from mountain pine beetle salvage logging infrastructure: dense road networks and large intensive forest harvest cutblocks. We used 157,447 global positioning system locations from 83 adult female moose from 2012 to 2016 on the Bonaparte Plateau at the southern edge of the Interior Plateau of central British Columbia to test whether increased forage availability, landscape features associated with increased mortality risk, or the cumulative effects of salvage logging best explain female moose distribution using resource selection functions in an information‐theoretic framework. We tested these hypotheses across biological seasons, defined using a cluster analysis framework. The cumulative effects of forage availability and risk best predicted resource selection of female moose in all seasons; however, the covariates included in the cumulative models varied between seasons. The top forage availability model better explained moose habitat use than the top risk model in all seasons, except for the calving and fall seasons where the top risk model (distance to road) better predicted moose space use. Selection of habitat that provides forage in winter, spring, and summer suggests that moose seasonally trade predation risk for the benefits of foraging in early seral vegetation communities in highly disturbed landscapes. Our results identified the need for intensive landscape‐scale management to stem moose population declines. Additional research is needed on predator densities, space use, and calf survival in relation to salvage logging infrastructure. © 2020 The Wildlife Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".