Prey availability and ambient temperature influence carrion persistence in the boreal forest
Bibliographic record
Abstract
Scavenging by vertebrates can have important impacts on food web stability and persistence, and can alter the distribution of nutrients throughout the landscape. However, scavenging communities have been understudied in most regions around the globe, and we lack understanding of the biotic drivers of vertebrate scavenging dynamics. In this paper, we examined how changes in prey density and carrion biomass caused by population cycles of a primary prey species, the snowshoe hare Lepus americanus, influence scavenging communities in the northern boreal forest. We further examined the impact of habitat and temperature on scavenging dynamics. We monitored the persistence time, time until first scavenger, and number of species scavenging experimentally-placed hare carcasses over four consecutive years in the southwestern Yukon. We simultaneously monitored hare density and carrion biomass to examine their influence relative to temperature, habitat, and seasonal effects. For the primary scavengers, we developed species-specific scavenging models to determine variation on the effects of these factors across species, and determine which species may be driving temporal patterns in the entire community. We found that the efficiency of the scavenging community was affected by hare density, with carcass persistence decreasing when snowshoe hare densities declined, mainly due to increased scavenging rates by Canada lynx Lynx canadensis. However, prey density did not influence the number of species scavenging a given carcass, suggesting prey abundance affects carrion recycling but not necessarily the number of connections in the food web. In addition, scavenging rates increased in warmer temperatures, and there were strong seasonal effects on the richness of the vertebrate scavenging community. Our results demonstrate that vertebrate scavenging communities are sensitive to changes in species' demography and environmental change, and that future assessments of food web dynamics should consider links established through scavenging.
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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 | 0.001 |
| 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".