Winter severity modulates the benefits of using a habitat temporally uncoupled from browsing
Bibliographic record
Abstract
Abstract Resources whose abundance is not affected by the density of the consumer population, namely donor‐controlled resources, are ubiquitous. Donor‐controlled resources can act as food subsidies when they sustain consumer populations at higher densities than what would be predicted without donor‐controlled dynamics. Herbivore populations that have access to food subsidies may reach and maintain high densities, with potential major ecological and economic consequences. A better understanding of the roles of food subsidies on temperate herbivores will likely be achieved by simultaneously taking into account other drivers of demographic variations such as winter severity. Here, we tested the hypothesis that the use of a donor‐controlled food resource that may act as a food subsidy, namely balsam fir ( Abies balsamea ), and winter severity act together to shape the patterns of overwinter mass loss in a large herbivore population (white‐tailed deer, Odocoileus virginianus ). We monitored weather conditions, diet, habitat use, and mass loss of female deer during two highly contrasted winters. During an exceptionally milder winter, characterized by shallower snow depth and warmer windchill temperatures, female deer shifted their diet toward resources usually covered by snow during typical winters. Surprisingly, the rate of body mass loss remained similar during the milder and the harsher winter. The rate of body mass loss rather decreased with the use of balsam fir stands during the harsher winter, but increased with that same variable during the milder winter. Our study revealed that deer can alleviate overwinter mass loss by using a donor‐controlled habitat type temporally uncoupled from browsing, but that this benefit is climate dependent. This study represents an additional step to address the largely unexplored concept of how temporal uncoupling between resources and consumer dynamics may contribute to sustain consumer populations at higher densities than predicted without considering donor‐controlled dynamics.
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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 | 0.000 | 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) | 0.004 | 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".