Global Phylogeography and Dispersal Patterns of Commercially Important Shrimp Species
Bibliographic record
Abstract
The dominant shrimp species in commercial breeding are widely introduced and spread worldwide, and their systematic geographical pattern and diffusion paths have attracted much attention. This study combines the progress of molecular phylogenetics and population genetics in recent years, and reviews and analyzes the phylogenetic relationship, natural geographical distribution, artificial introduction history and cross-regional transmission patterns of major economic shrimps. The results show that the Indo-Western Pacific region is the center of origin of most marine shrimps, and there is obvious geographical differentiation of populations in different oceanic regions, and marine barriers restrict gene communication. Human farming activities have accelerated the global spread of shrimp species, but have also caused problems such as germplasm mixing, decline in genetic diversity and alien invasion. Molecular marker analysis revealed the genetic structural characteristics, population differentiation levels and environmental adaptation signals of major farmed shrimp species. In the context of global climate change, the driving role of environmental factors (such as temperature, salinity) on the geographical distribution of shrimp is becoming increasingly prominent. This study systematically sorted out the research progress of the global systematic geographical pattern and transmission model of commercial important shrimps, and pointed out the importance of strengthening genetic diversity protection, standardizing international seedling trade and preventing and controlling disease transmission for the sustainable development of the industry.
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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 | 0.001 |
| 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) | 0.001 | 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".