MétaCan
Menu
Back to cohort
Record W4400858194 · doi:10.1002/2688-8319.12367

Making sense of wildlife habitat use on active oil sands mines: Quasi‐experiments, occupancy models, trends assessments and upland habitat reclamation

2024· article· en· W4400858194 on OpenAlex
Virgil C. Hawkes, Pascale Gibeau, Wendell Challenger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcological Solutions and Evidence · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsASL Environmental Sciences (Canada)
FundersSuncor Energy IncorporatedImperial Oil LimitedCanadian Natural Resources Limited
KeywordsWildlifeLand reclamationHabitatOccupancyEnvironmental scienceOil sandsWildlife managementEcologyWildlife conservationGeographyAsphaltBiology

Abstract

fetched live from OpenAlex

Abstract Intensive resource extraction activity in the oil sands of Canada alters the quantity, structure and distribution of native ecosystems, which in turn creates substantive challenges for conservation, land management and habitat reclamation. Progressive reclamation occurs on active mine sites in the Athabasca oil sands region (AOSR) of Canada, along with concurrent assessments of reclamation effectiveness. Yet, little is known about the ability of reclaimed habitats to mitigate for the short‐ and long‐term impacts associated with open‐pit mines and provide functional habitat for wildlife. We used a robust quasi‐experiment that combined camera trap data from an observational study with an innovative occupancy model to assess the effectiveness of upland reclamation to provide habitat for wildlife in the AOSR. The dynamic occupancy models were applied to 15 years of camera trap data to assess wildlife usage patterns of nine species of wildlife over seven types of habitats. The habitats sampled ranged from mining‐disturbed habitats reclaimed to upland forest ecosites common in the region, habitats disturbed by natural (fire) and human disturbances (clear‐cut logging), with comparisons to mostly intact mature forests. Our results indicate that the nine species of wildlife assessed used habitats in a manner consistent with expectations: some preferred disturbance‐dominated habitats while others used mature forest to a higher degree. We demonstrate that the application of dynamic occupancy models to camera trap data reliably discerned these trends, providing the means to predict wildlife usage patterns in an ever‐changing landscape, including one containing bitumen extraction as a contributor to landscape‐level modifications. Practical implication : Our work illustrates how continued monitoring of wildlife using camera traps contributes to assessments of reclamation effectiveness with respect to wildlife occurrence, distribution and usage patterns in anthropogenically and naturally disturbed landscapes. Evaluating the effectiveness of reclamation is especially important given the expected increase in habitat reclamation on active oil sands mines over the next several decades, coupled with the need to ensure that disturbed habitats regain ecological function able to sustain wildlife in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.135
GPT teacher head0.345
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it