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Record W6903127815 · doi:10.7939/r3-mphh-3b90

Seasonal habitat use, habitat selection, and migratory behaviours of Stone’s sheep (Ovis dalli stonei) in northern British Columbia, Canada

2021· dissertation· en· W6903127815 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatDomestic sheep reproductionHome rangeUngulatePopulationWildlifeRange (aeronautics)Resource (disambiguation)

Abstract

fetched live from OpenAlex

Habitats and migration corridors used by wildlife have become increasingly modified by anthropogenic disturbances, and in many cases have resulted in population declines and local extirpations. To conserve ungulate populations, management strategies often focus on identifying and mitigating disturbances in critical habitats and seasonal ranges. The Cassiar Mountains of northern British Columbia, Canada are home to a spatially structured population of Stone’s sheep (Ovis dalli stonei) composed of small bands (groups) of sheep dispersed throughout the region. The Cassiar Mountains are largely unaltered by human land-use and disturbance, however, more recent increases in recreation and potential resource development expansions might threaten critical habitats and alter seasonal movements of the Cassiar population. My objectives in this study were to identify lambing events, estimate habitat selection during critical lambing and nursery periods, and examine the seasonal space-use and migratory patterns of 18 collared female Stone’s sheep to identify areas of high conservation priority. I assessed individual movement patterns and used vaginal implant transmitters to identify lambing events from 2018 to 2020. Females gave birth from May 3rd to June 14th, which was within the expected lambing season of northern mountain sheep. I estimated habitat selection during each female’s lambing and nursery periods at two spatial scales; first, at the home range scale, by fitting resource selection functions, and second, at a finer scale constrained by individual movement by modelling integrated step selection functions. I found habitat selection was consistent across scales. During lambing and nursery periods, females selected southwest slopes in rugged, steep terrain at mid elevations, demonstrating selection for landscape features that facilitate predator avoidance. Further, during the nursery period, females exhibited selection for intermediate greenness, and unexpectedly, for habitats near roads, likely due to nursing females accessing nutritionally important mineral licks adjacent to roads in the area. To evaluate the seasonal space-use and migration behaviours of Stone’s sheep, I estimated Brownian bridge movement models to delineate winter and summer ranges, migration corridors, and stopover sites. Next, I classified individual migration strategies based on seasonal geographic and altitudinal movements between summer and winter ranges. Variation in migration strategies did not occur across individuals, but rather across bands, suggesting migratory diversity in the Cassiar population is driven by the distribution of resources and topography within the local landscapes of different bands. Due to two bands crossing a major highway during spring and fall migrations, I recommend installing road signage and speed reductions near these areas to reduce road-strike mortality risk and potential impacts to connectivity. Further, I recommend mitigating disturbances in delineated migration corridors, seasonal ranges, and suitable lambing and nursery habitats to better conserve Stone’s sheep in the Cassiar Mountains.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

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)0.0020.000

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 head0.003
GPT teacher head0.150
Teacher spread0.147 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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