Mitochondrial Genetic Diversity among Farmed Stocks of Oreochromis spp. (Perciformes, Cichlidae) in Madagascar
Bibliographic record
Abstract
The fast development of aquaculture over the past decades has made it the main source of fish protein and led to its integration into the global food system. Mostly originating from inland production systems, aquaculture has emerged as strategy to decrease malnutrition in low-income countries. The Nile tilapia (Oreochromis niloticus) was introduced to Madagascar in the 1950s, and is now produced nationally at various scales. Aquaculture mostly relies on fry harvested from wild populations and grow-out in ponds for decades. It has recently been diversified by the introduction of several fast-growing strains. Little is known how local genetic diversity compares to recently introduced strains, although high and comparable levels of genetic diversity have previously been observed for both wild populations and local stocks. Our study compares DNA barcode genetic diversity among eight farms and several strains belonging to three species sampled. DNA-based lineage delimitation methods were applied and resulted in the detection of six well differentiated and highly divergent lineages. A comparison of DNA barcode records to sequences on the Barcode of Life Data System (BOLD) helped to trace the origin of several of them. Both haplotype and nucleotide diversity indices highlight high levels of mitochondrial genetic diversity, with several local strains displaying higher diversity than recently introduced strains. This allows for multiple options to maintain high levels of genetic diversity in broodstock and provides more options for selective breeding programs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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 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".