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Record W7162010932 · doi:10.82308/10513

Moose calving in boreal forests of Eeyou Istchee, Northern Quebec

2025· dissertation· en· W7162010932 on OpenAlexaboutno aff
Mikaela Borgeaud LeBlanc

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsIce calvingPopulationTaigaRuminatingBorealAerial survey

Abstract

fetched live from OpenAlex

In boreal forests of the Cree territory of Eeyou Istchee in Northern Quebec, moose are culturally important to Cree harvesters who are concerned about how moose calving is affected by forestry and fire disturbance. The cryptic nature of moose calving behaviour, including its timing, cow-calf interactions, and habitat-specificity, has limited our understanding of moose calving success and its contribution to moose population dynamics. GPS-collars were deployed on 89 female moose over five years, including 8 collars equipped with animal-borne video and environmental data collection systems (AVED-collars), across regions with varying levels of forestry and fire disturbance. The first data chapter assesses moose calving behaviour, through a focus on cow movement patterns, seasonal timing, and cow-calf interactions. We first assessed the accuracy and precision of six movement-based methods typically used to infer calving dates of moose and other ungulates, by comparing calving dates estimated from GPS-collar movement patterns to AVED video observations of calves and calving. Comparisons of 8 females during 12 calving seasons identified three of the six movement-based methods to be both accurate and precise and we used these three movement-based methods to estimate parturition dates for the larger sample of female moose equipped with GPS collars. Moose parturition dates ranged from May 12 to June 23, with more than 70% of births occurring between May 18 and May 26. Classification of videos from AVEDs revealed that females spent more time walking, standing, feeding, and ruminating the day before calving compared to the day after, when they spent more time laying down and licking their calf. Analysis of movement patterns demonstrated that one day before calving, females were located (net square displacement) 2.5 km from their calving site (median; range <0.1-16.5km), then remained highly localized for 7 days post-calving (median 0.2 km; range <0.1-4.9 km). Parturition dates varied slightly between regions, by on average three days, but did not vary between years or according to latitude, longitude, autumn temperature, forestry disturbance, or hunting disturbance. The second data chapter assesses the habitat-specificity and fidelity of calving locations. We compared space use and multi-annual fidelity during a 7-day period following estimated parturition dates to equivalent measures in late winter and summer and evaluated calving site selection comparing the use and availability of terrain, land cover, road density, and fire and forestry disturbance. For the 7-days following parturition, female space use was confined to 0.04 km2 (median; range <0.01 - 10.3 km2), which was equally as small as winter home ranges (0.04 km2, <0.01 – 1.03 km2), but smaller than the summer home ranges (4.97 km2, 0.047 – 270.41 km2) for moose that have annual home ranges of 116.49 km2 (median, range 24.6 - 961.0 km2). Females expressed moderately low calving site fidelity, calving within 4.00 km (median, range 0.35 - 13.54 km) of previously used calving sites, which is not significantly different than summer (median 2.18 km, mean 2.18 km, 0.24 - 4.65 km) and winter fidelity (median 3.65 km, mean 6.36 km, range 0.70 - 21.05 km). Female moose exhibited extensive individual variability in calving site selection, with an overall preference for elevated areas with mixedwood or broadleaf forests and low road densities. Among the subset of moose with forestry or fire disturbance within their annual home range, some females calved in habitats that were 10-15 years post-fire, while all females avoided calving in habitats that had been disturbed by fire or forestry within the last year. Quantifying the timing, movement, fidelity and habitat selection of moose calving informs habitat and wildlife management including long-term impacts of disturbance and environmental change on moose calving sites

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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