Predator‐Mediated Indirect Effects of Snowshoe Hares on Dall's Sheep in Alaska
Bibliographic record
Abstract
ABSTRACT Indirect interactions among species can strongly influence population dynamics and community structure but are often overlooked in management of large mammals. We estimated survival of Dall's sheep ( Ovis dalli ) in the central Alaska Range, USA, during years of differing snowshoe hare ( Lepus americanus ) abundance to test whether indirect interactions with a cyclic hare population affect Dall's sheep either negatively, by subsidizing predators (apparent competition), or positively, by diverting predation (apparent commensalism). Annual survival of adult female sheep was consistently high (0.85 for all yr and age classes combined). In contrast, annual estimates of lamb survival ranged from 0.15 to 0.63. The main predators of lambs were coyotes ( Canis latrans ) and golden eagles ( Aquila chrysaetos ), which rely on hares as their primary food and prey on lambs secondarily. Coyotes and eagles killed 78% of 65 radiocollared lambs for which cause of death was known. Lamb survival was negatively related to hare abundance during the previous year, and lamb survival rates more than doubled when hare abundance declined, supporting the hypothesis of predator‐mediated apparent competition between hares and sheep. However, stage‐specific predation and delays in predator responses to changes in hare numbers led to a positive relationship between abundance of adult Dall's sheep and hares. Lacking reliable estimates of survival, a manager might erroneously conclude that hares benefit sheep. Thus, support for different indirect effects can be obtained from different types of data, which demonstrates the need to determine the mechanisms that create indirect interactions. Long‐term survey data suggest that predation by coyotes is limiting this sheep population below levels typical when coyotes were rare or absent. Understanding the nature of indirect interactions is necessary to effectively manage complex predator–prey communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".