Does connectivity exist for remnant boreal caribou (Rangifer tarandus caribou) along the Lake Superior Coastal Range? Options for landscape restoration
Bibliographic record
Abstract
Genetic analysis can provide important information on the dynamic and spatial structure of groups of animals or populations. Little is known of the genetic population structure of caribou that inhabit the Lake Superior Coastal Range (LSCR) and the level of gene flow between individuals within the range and beyond. From a landscape perspective, this range is spatially isolated and genetic connectivity within the range is presumed limited due to large water crossings on Lake Superior. This study aims to answer if animal movement can be discerned, using genetic population and relatedness analyses, within and beyond the LSCR. Faecal and hair samples collected between 2005 and 2015 in Pukaskwa National Park were analyzed for genetic markers and compared to 131 unique genotypes previously obtained from both within the LSCR and in the two next closest ranges. Animals from one nearshore island (i.e. Otter) were more closely associated with offshore islands than other mainland caribou, likely a result of past movement and translocation rather than ongoing movement. Conversely, on another nearshore island (i.e. Pic), individuals assigned to a different genetic cluster and were related to animals further north outside the range, demonstrating some connectivity through the discontinuous distribution to the coast. Long-term population declines have been observed in the LSCR range despite genetic connectivity within the range and relatively low total habitat disturbance. Restoring connectivity of the LSCR so that it is not isolated from populations to the north is required for the recovery of the mainland portion of the coastal range. These genetic analyses provide some insights on where movements may occur and where landscape restoration efforts may best be directed to enhance connectivity.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".