Selection of Genes and of Habitats: Ecological Genomics in Endangered Caribou
Bibliographic record
Abstract
Habitat selection could be genetically determined. For example, genetic drivers could “force” habitat specialist species to select for specific resources. Caribou (Rangifer tarandus) are habitat specialist and the species is declining mainly due to human-caused habitat alterations. So far, habitat selection for caribou has been studied with ecological data only, and the link with genetics has not been explored, since needed information on individuals carrying genes was not available –i.e. requiring a genomic approach. We examined GPS locations for caribou belonging to two subspecies and three ecotypes from populations distributed throughout western North Canada and investigated selection of winter and summer habitats. We also genotyped 30,000 Single Nucleotide Polymorphisms (SNPs) and determined if SNPs, and the genes that SNPs harbor, were associated to habitat selection factors in caribou individuals. Our results indicated that caribou selected for specific habitats likely representing food sources found in pristine environments. In these same individuals, habitat associated genes were also selected, which were involved in taste perception and thermoregulation of this Northern species. We have therefore detected for the first time a gene-to-environment association involving selection of both genes and habitat, with important implications for conservation. Habitats and climate are dramatically changing worldwide and the genetic aspects of selectivity that we described could indicate limited ability to adapt in caribou. Here, we investigate the link between ecology and genomics in caribou, with applications to other species in which genetic traits may also influence behaviour and limit resilience to changing habitats or climatic conditions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".