Summer habitat use and movements of invasive wild pigs (<i>Sus scrofa</i>) in Canadian agro-ecosystems
Bibliographic record
Abstract
Resource selection informs understanding of a species’ ecology and is especially pertinent for invasive species. Since introduced to Canada, wild pigs ( Sus scrofa Linnaeus, 1978) remain understudied despite recognized negative impacts on native and agricultural systems globally. Elsewhere in North America, pigs typically use forests and forage in agricultural crops. We hypothesized Canadian wild pigs would behave similarly, and using GPS locations from 15 individuals, we examined diel and seasonal resource selection and movement in the Canadian prairie region. Forests were predominately selected during the day, while corn ( Zea mays L.), oilseeds, and wheat ( Triticum aestivum L.) were predominately selected at night. Forests and corn were consistently selected throughout the growing season. Wetlands and forests showed greater use rates than other habitats, with evident trade-offs as crop use increased with the timing of maturation. Activity was consistent with foraging in growing crops. Results indicate diel patterns were likely a function of short-term needs to avoid daytime anthropogenic risk, while seasonal patterns demonstrate how habitats that fill multiple functional roles — food, cover, and thermoregulation — can be optimized. Understanding selection by invasive species is an important step in understanding their potential environmental impacts in novel environments and informs their management.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".