Evaluating evolutionary history and adaptive differentiation to identify conservation units of Canada lynx (Lynx canadensis)
Bibliographic record
Abstract
Protection and management of adaptively diverse populations is critical to meet the goals of conservation policy and to conserve the evolutionary potential of species into the future. The identification of conservation units below the species level can be a helpful tool in this regard. In Canada, such conservation units are referred to as Designatable Units (DUs) which are required to be both discrete and significant. Significance criteria are related to the evolutionary significance of species, or populations below the species level. Evaluating evolutionary significance often concerns adaptive differentiation, which can be difficult to demonstrate empirically, and challenging to establish for wide-ranging species. Such species are often genetically panmictic across their range, and, as a result, lumped into a single or few DUs, even though they may have unique population histories or evolutionary lineages. Here, we use Approximate Bayesian Computation to differentiate between hypotheses of contemporary versus historic phylogenetic histories, and a candidate gene approach using coding trinucleotide repeat markers within functional genes to assess the potential for local adaptation of insular and peripheral populations of Canada lynx (Lynx canadensis). We demonstrate that these populations have evolutionary histories consistent with divergence following the last glacial maximum, and show patterns at cTNR loci that suggest the potential for adaptive divergence as well. We demonstrate how, in concert with previously published evidence of genetic discreteness, our results suggest at least four DUs for Canada lynx: lynx (1) north and (2) south of the St. Lawrence River on mainland Canada, and lynx on the islands of (3) Newfoundland and (4) Cape Breton.
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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 | 0.000 |
| 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".