Fitness consequences of divergent oxygen environments in a widespread African cyprinid
Bibliographic record
Abstract
East African papyrus swamps and their connected streams are characterized by a very steep gradient of dissolved oxygen (DO) ranging from extremely hypoxic swamp waters to well-oxygenated stream habitats. These connected ecotypes host morphologically and physiologically distinct phenotypes of the cyprinid fish Barbus neumayeri. Notably, low-DO populations are characterized by much larger gills and higher hematocrit that are likely to facilitate oxygen uptake in hypoxic waters. Metrics of genetic structure in this species indicate higher gene flow within than between DO regimes, suggesting that migrants crossing the oxygen gradient have reduced fitness. Despite this evidence for local adaptation in divergent DO environments, the fitness consequences of phenotypic divergence are unknown and led to the current goal of documenting fitness-related traits in a high- and low-DO population of B. neumayeri that are connected geographically. In this study, I used an intensive mark and recapture study to document natural growth rate, body condition, length, viability, and movement of B. neumayeri within and across DO regimes, and collections of mature females to estimate reproductive traits (gonad size, egg size, and fecundity). I tested for (1) phenotypic divergence in fitness-related traits between high- and low-DO phenotypes, and (2) evidence for movement between low- and high-DO habitats. Results indicated lower condition, survival, and reproductive investment in swamp-dwelling (low DO) fish, which is consistent with predictions based on physiological costs of hypoxic habitats. However, I found equivalent growth rates of populations in their natural habitats, suggesting that some of these costs are compensated for by other ecological advantages of the swamp. Finding very few non-local fish (migrants), I draw inferences regarding the potential for local adaptation in the system.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".