Assessing factors influencing the space use of a woodland caribou Rangifer tarandus caribou population using an individual‐based model
Bibliographic record
Abstract
Abstract Similar to earlier studies, a population of woodland caribou Rangifer tarandus caribou in west‐central Manitoba, Canada, showed preference for mature coniferous forests and fidelity to seasonal home ranges. However, because preferred forest types were common in the study area, these findings could not determine what would happen if these home ranges were disturbed because the relative importance of preference for these forest types and home‐range fidelity in determining the space use of this population was not known. This question was explored using an individual‐based space‐use model that incorporates a random movement component, a habitat value function that considers these two factors individually or together, and a decision optimisation component. Four possible forms of the model were used to conduct Monte‐Carlo simulations of space‐use patterns, which were compared to true range‐use patterns over an annual cycle. True range use could not be simulated without including a home‐range fidelity factor in the model. This suggests that there is some factor about the selected home ranges that is not quantified by the forest type which is currently present that causes animals in this population to show fidelity to them. The explanation most consistent with the general understanding of the factors limiting this species is that these home ranges are refuges from predation. This suggests that the appropriate conservation action is to protect these ranges from disturbance unless the animals themselves demonstrate the presence of other suitable areas by dispersing to them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".