Patterns in consumption of woody plants by snowshoe hares in the northwestern United States
Bibliographic record
Abstract
Herbivores manifesting spatially variable population densities may elicit geographical differences in the characteristics of the plants upon which they feed. Northern snowshoe hare (Lepus americanus) populations undergo dramatic numerical cycles; during periods of hare abundance, browsing by these populations can result in both absolute food shortage and the production of chemical defenses among browsed plants. Southern hare populations never achieve the densities characteristic of their northern counterparts and, therefore, should be less likely to elicit either food biomass limitation or the production of plant chemical defenses. Thus, hares in these populations should have access to a superabundant food supply and select browse species according to their nutrient content rather than their defensive chemical composition. We measured the extent of browse use by hares in the southwestern portion of the species’ range by calculating per capita winter browse availability (total biomass of potential food divided by winter hare population estimate) on six study sites during the winter of 1999. In addition, we used feeding trials on captive hares to determine patterns of browse consumption. Per capita browse biomass estimates were adequate to support the hares residing on each study site; on average, a 10-fold numerical increase would have been required to produce absolute food shortage. Patterns in consumption of browse by hares were not related to concentrations of plant chemical defenses (total phenols and monoterpenes), but rather to crude protein content. Levels of protein and copper (and possibly selenium) in the major browse species in our area were low, implying that, despite having access to a superabundance of poorly defended food, hares in southwestern populations may be subject to a poor-quality diet. In support of this possibility, we found that free-ranging hares had reproductive rates (potential natality = 5.64 young female-1 year-1) that were qualitatively lower than any reported in the literature (n = 18 studies) and males had relatively poor overwinter condition as well as delayed testes recrudescence. Poor diet quality and, consequently, low reproductive rates may contribute to the allegedly non-cyclic and generally lower densities of southwestern hare populations.Keywords: snowshoe hare, Lepus americanus, browse availability, plant chemical defenses, browse consumption patterns, reproductive rates, protein, copper.
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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 | 0.000 | 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 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".