Behavioural Ecology in Conservation Planning: Individual and Sex-Specific Insights from Woodland Caribou (Rangifer tarandus caribou) in Western Canada
Bibliographic record
Abstract
Conservation planning often relies on delineating intraspecific units to capture ecological and evolutionary diversity. To do this, traditional frameworks often emphasize genetic or taxonomic criteria as a first line of evidence for evolutionary significance. While useful, this approach assumes discrete boundaries within species, potentially overlooking the continuous nature of adaptive variation. Individual behavioural diversity, shaped by genetic, environmental, and social processes offers an alternative lens for understanding population structure that reflects functional ecological strategies. This thesis explores how individual-level behavioural variation can inform conservation of woodland caribou (Rangifer tarandus caribou), a threatened species with complex population structure and widespread declines across western Canada. Leveraging a long-term (2000 – 2025) broad-scale GPS telemetry dataset from over 1000 individuals across multiple pre-defined population units and recognized conservation units in British Columbia, I evaluated how variation in movement and habitat selection patterns may reveal ecologically meaningful differences. Analysis of 24 different movement behaviours for female caribou, including migration tendency, home range shape and size, and calving strategies, identified six broad behavioural clusters. Resource selection functions were then evaluated across female caribou, revealing three primary clusters, with additional fine-scale differentiation in habitat selection patterns which only partially aligned with existing conservation units. Finally, a multi-population analysis of both sexes demonstrated consistent sex differences in migration timing, home range size, and habitat selection, with males and females exhibiting distinct spatial strategies that could influence connectivity and habitat requirements. Together, these findings demonstrate that caribou exhibit a wide range of diversity in behavioural strategies that do not always conform to existing taxonomic or genetic boundaries. By incorporating behavioural ecology into conservation planning, we gain a more holistic understanding of intraspecific diversity. Rather than emphasizing rigid units, this thesis argues for conservation approaches that recognize behavioural gradients and variability as central to preserving adaptive potential for species facing rapid environmental change.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".