Prey and habitat distribution are not enough to explain predator habitat selection: addressing intraspecific interactions, behavioural state and time
Bibliographic record
Abstract
BACKGROUND: Movements and habitat selection of predators shape ecological communities by determining the spatiotemporal distribution of predation risk. Although intraspecific interactions associated to territoriality and parental care are involved in predator habitat selection, few studies have addressed their effects simultaneously with those of prey and habitat distribution. Moreover, individuals require behavioural and temporal flexibility in their movement decisions to meet various motivations in a heterogeneous environment. To untangle the relative importance of ecological determinants of predator fine-scale habitat selection, we studied simultaneously several spatial, temporal, and behavioural predictors of habitat selection in territorial arctic foxes (Vulpes lagopus) living within a Greater snow goose (Anser caerulescens atlantica) colony during the reproductive season. METHODS: Using GPS locations collected at 4-min intervals and behavioural state classification (active and resting), we quantified how foxes modulate state-specific habitat selection in response to territory edges, den proximity, prey distribution, and habitats. We also assessed whether foxes varied their habitat selection in response to an important phenological transition marked by decreasing prey availability (goose egg hatching) and decreasing den dependency (emancipation of cubs). RESULTS: Multiple factors simultaneously played a key role in driving habitat selection, and their relative strength differed with respect to the behavioural state and study period. Foxes avoided territory edges, and reproductive individuals selected den proximity before the phenological transition. Higher goose nest density was selected when foxes were active but avoided when resting, and was less selected after egg hatching. Selection for tundra habitats also varied through the summer, but effects were not consistent. CONCLUSIONS: We conclude that constraints imposed by intraspecific interactions can play, relative to prey distribution and habitat characteristics, an important role in the habitat selection of a keystone predator. Our results highlight the benefits of considering behavioural state and seasonal phenology when assessing the flexibility of predator habitat selection. Our findings indicate that considering intraspecific interactions is essential to understand predator space use, and suggest that using predator habitat selection to advance community ecology requires an explicit assessment of the social context in which movements occur.
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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 | 0.001 |
| 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 | 0.001 |
| 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".