Predator home range size mediates indirect interactions between prey species in an arctic vertebrate community
Bibliographic record
Abstract
Indirect interactions are widespread among prey species that share a common predator, but the underlying mechanisms driving these interactions are often unclear, and our ability to predict their outcome is limited. Changes in behavioural traits that impact predator space use could be a key proximal mechanism mediating indirect interactions, but there is little empirical evidence of the causes and consequences of such behavioural-numerical response in multispecies systems. Here, we investigate the complex ecological relationships between seven prey species sharing a common predator. We used a path analysis approach on a comprehensive 9-year data set simultaneously tracking predator space use, prey densities and prey mortality rate on key species of a simplified Arctic food web. We show that high availability of a clumped and spatially predictable prey (goose eggs) leads to a twofold reduction in predator (arctic fox) home range size, which increases local predator density and strongly decreases nest survival of an incidental prey (American golden plover). On the contrary, a scattered cyclic prey with potentially lower spatial predictability (lemming) had a weaker effect on fox space use and an overall positive impact on the survival of incidental prey. These contrasting effects underline the importance of studying behavioural responses of predators in multiprey systems and to explicitly integrate behavioural-numerical responses in multispecies predator-prey models.
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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 | 0.001 |
| 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".