Body size and prey abundance influence activity patterns in a diverse mesocarnivore community
Bibliographic record
Abstract
Wildlife species that share resources may experience niche overlap and competition across spatial, temporal, or dietary dimensions. Mesocarnivores often overlap in habitat and food requirements. Temporal niche partitioning may facilitate co-occurrence, but the environmental and behavioural processes behind this are not well understood. We used five years of remote camera data to investigate temporal niche partitioning among six sympatric mesocarnivores—short-tailed weasel ( Mustela erminea ), American mink ( Neogale vison ), American marten ( Martes americana ), fisher ( Pekania pennanti ), wolverine ( Gulo gulo ), and Canada lynx ( Lynx canadensis )—in British Columbia, Canada. Our study spanned a period of fluctuating snowshoe hare ( Lepus americanus ) abundance, coinciding with decreases in lynx and increases in fisher abundances. These shifts allowed us to test whether smaller species altered activity patterns in the presence of larger ones (size-dominance hypothesis) and whether activity varied with prey availability (prey-abundance hypothesis). Supporting the size-dominance hypothesis, marten activity differed in the presence of lynx and fisher, while lynx and wolverine maintained consistent patterns regardless of smaller species. Supporting the prey-abundance hypothesis, the activity patterns of marten and lynx differed during a hare population low. These results suggest that mesocarnivores display plasticity in temporal activity that may reduce interspecific competition and facilitate co-occurrence.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".