Identifying designatable units for intraspecific conservation prioritization: a hierarchical approach applied to the lake whitefish species complex (Coregonus spp.)
Bibliographic record
Abstract
The concept of the designatable unit (DU) affords a practical approach to identifying diversity below the species level for conservation prioritization. However, its suitability for defining conservation units in ecologically diverse, geographically widespread and taxonomically challenging species complexes has not been broadly evaluated. The lake whitefish species complex (Coregonus spp.) is geographically widespread in the Northern Hemisphere, and it contains a great deal of variability in ecology and evolutionary legacy within and among populations, as well as a great deal of taxonomic ambiguity. Here, we employ a set of hierarchical criteria to identify DUs within the Canadian distribution of the lake whitefish species complex. We identified 36 DUs based on (i) reproductive isolation, (ii) phylogeographic groupings, (iii) local adaptation and (iv) biogeographic regions. The identification of DUs is required for clear discussion regarding the conservation prioritization of lake whitefish populations. We suggest conservation priorities among lake whitefish DUs based on biological consequences of extinction, risk of extinction and distinctiveness. Our results exemplify the need for extensive genetic and biogeographic analyses for any species with broad geographic distributions and the need for detailed evaluation of evolutionary history and adaptive ecological divergence when defining intraspecific conservation units.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".