Do measures of plant intake and digestibility from captive feeding trials align with foraging patterns of free-ranging snowshoe hares?
Bibliographic record
Abstract
Context Measures of intake and digestibility from captive feeding experiments are often used to evaluate the nutritional value of plant species to herbivores; however, there is question about how well plant-quality rankings from these trials predict foraging patterns of free-ranging animals. Studies addressing the alignment of results from feeding trials and herbivory in the field using captive and free-roaming conspecifics are needed. Aims Our goal was to compare the feeding patterns of snowshoe hares in captive intake and digestion trials with those of free-living conspecifics in the species’ south-western range. Methods We conducted in vivo intake and digestion trials using captive hares to determine quality and consumption levels of the predominant conifer species in our study system. In the field, we quantified browsing intensity and over-winter depletion patterns of these conifers. We then compared voluntary intake and nutritional quality measured in captivity to consumption in the field. Key results Digestible energy (DE, kJ g–1) of conifers ranged from 11.0 (Pinus contorta) to 13.8 (Pseudotsuga menziesii) among six conifers, and digestible protein (DP, g protein per 100 g feed) from 1.2 (Thuja plicata) to 2.7 (P. contorta). During digestion trials, single-species intake was correlated with the content of digestible protein (DP) and digestible energy (DE). Hares maintained energy balance when fed two single-species diets (Pinus contorta, Pseudotsuga menziesii) and a mixed-species diet. Conifer species on which hares were able to maintain body mass (Pinus contorta, Picea engelmannii, Pseudotsuga menziesii) also tended to be the most heavily exploited by free-living hares. DP content of browse species predicted both browsing intensity and overwinter depletion of conifer species. Conclusions Voluntary intake and nutritional quality of browse, especially DP, successfully predicted foraging patterns of free-ranging conspecifics. Implications Intake and digestion trials can be a useful tool for better understanding patterns of herbivory in the field, and winter habitat quality for populations in this region is likely to be influenced by access to the most energy- and protein-rich conifers.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".