Population genetic structure across dissolved oxygen regimes in an African cichlid fish
Bibliographic record
Abstract
Ecological isolation is a process whereby gene flow between selective environments is reduced due to selection against maladapted dispersers, migrant alleles, or hybrids. Although ecological isolation has been documented in several systems, gene flow can often be high among selective regimes, and more studies are thus needed to better understand the conditions under which ecological gradients or divergent selective regimes should influence population structure. We test for ecological isolation in a system in which high plasticity occurs with respect to traits that are adaptive in alternate forms under different environmental conditions. Pseudocrenilabrus multicolor victoriae is a widespread haplochromine cichlid fish in East Africa that exploits both normoxic (normal oxygen) rivers/lakes and hypoxic (low oxygen) swamps. Here, we examine population structure, using mitochondrial DNA and microsatellites, to determine if genetic divergence is significantly increased between dissolved oxygen regimes relative to within them, while controlling for geographical structure. Our results indicate that geographical separation influences population structure, while no effects of divergent selection with respect to oxygen regimes were detected. Specifically, we document (i) genetic clustering according to geographical region, but no clustering according to oxygen regime; (ii) higher genetic variation among than within regions, but no effect of oxygen regime on genetic variation; (iii) isolation by distance within one region; and (iv) decreasing genetic variability with increasing geographical distance from Lake Victoria. We speculate that plasticity may be facilitating gene flow between oxygen regimes in this system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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 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".