Do grizzly bears use or avoid wellsites in west-central Alberta, Canada?
Bibliographic record
Abstract
In west-central Alberta, wellsites are common features in where oil and gas development is prevalent; yet, little is known about how these sites affect grizzly bears.I examined the wellsite selection and use of cover for ten grizzly bears (2-22 years of age) within 500 m of wellsites, between 2005 and 2010.Selection ratios were calculated for five equally large buffer isopleths.Most bears showed positive selection towards the 224-m wide zone containing the wellsite (WSZ).Important bear food growing on these sites is most likely the factor causing this pattern.Nonetheless, bears generally had higher selection ratios in the WSZ during nighttime compared to daytime, suggesting a temporal avoidance of human activity.The largest differences between day and night selection ratios appeared to generally occur in fall (September), especially for females.In addition, during this time, many bears had more GPS-locations inside the WSZ during night than day, even though there were more day GPS-locations in total within the home ranges, suggesting that some bears spend more time close to wellsites during night than day.These patterns coincide with the start of the big game hunting season in the area, and might therefore be a response to a higher human activity around wellsites and access roads during this time.Regarding the degree of cover, the WSZ selection ratio was not significantly correlated to proportion of forest, shrub or barren land in the WSZ.However, crown closure at bear GPS-location clusters for all available bear locations was not only lower close to inactive wellsites compared to active wellsites, it also varied depending on time of day.Differences between GPS-location density inside wellsite buffers and overall location density in the home range varied among bears and years.I conclude that some bears are attracted to wellsites, but avoid human activity by making temporal adjustments in their behaviour, and by using cover to compensate for being in proximity of human activity.Positive selection for anthropogenic features easily accessible by humans increases the risk of bear-human conflicts, which may in turn lead to increased direct mortality for this threatened bear population, but possibly also increased negative attitudes among people in the area.Krontakets slutningsgrad var lägre vid GPS-kluster runt inaktiva wellsites i jämförelse med aktiva wellsites, och med ytterligare tydliga skillnader i slutningsgrad beroende av tiden på dygnet.Skillnader i densitet av GPS-positioner inuti wellsitebuffrar och övergripande GPSpositionsdensitet i hemområden, varierade mellan björnar och år.Jag drar slutsatsen att somliga björnar selekterar för, och dras mot wellsites, men undviker samtidigt mänsklig aktivitet genom att göra temporära anpassningar i sina beteenden, samt genom att använda en högre grad av täckning i form av vegetation, för att kompensera närheten till mänsklig aktivitet.Positiv selektion för antropogena strukturer som är lättåtkomliga för människor ökar risken för konflikter mellan människa och björn.Detta kan leda till en ökad mortalitet hos denna hotade björnpopulation, men även ökade negativa attityder hos människor i området.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".