Hybridization among Divergent Stocks of Largemouth Bass (<i>Micropterus salmoides</i>) Results in Altered Cardiovascular Performance: The Influence of Genetic and Geographic Distance
Bibliographic record
Abstract
Animal populations exhibit wide ranges of divergence associated with both geographic and genetic distances. Here, we examined the role of crossing distance on the cardiovascular response to exhaustive exercise among differentiated stocks of largemouth bass Micropterus salmoides at 10 degrees C and 20 degrees C. Stocks of 2+ fish were produced using adults from three regions in the midwestern United States (southeastern Wisconsin, northwestern Wisconsin, and west central Minnesota) and were crossed with fish from central Illinois. Doppler flow probes were used to quantify cardiac output, heart rate, and stroke volume. Cardiac variables (both resting and maximal) were consistently lowest in pure Illinois fish relative to the F(1) interstock hybrids. Additionally, when exposed to exercise, cardiac variables for F(1) interstock hybrids required approximately 40% longer to return to resting levels compared with the pure Illinois stock. However, the time required to exhaust fish was similar across stocks. Interestingly, all of the stocks (including the interstock hybrids and pure Illinois) maintained cardiac scope. In general, the patterns observed in cardiovascular performance were consistent for both water temperatures. Multiple regression analysis was used to determine which of the divergence metrics contributed to variation in cardiovascular performance in interstock hybrids. Mitochondrial DNA data (genetic distance) were infrequently identified as a significant source of variation in cardiovascular performance. However, genetic distance data for the neutral allozyme markers revealed that these stocks have experienced significant divergence. Latitude (geographic distance) accounted for between 31% and 45% of variation observed in the recovery parameters. This study suggests that the magnitude of stock divergence is an important determinant in the degree to which cardiovascular performance of bass is altered from interstock hybridization and associated breakdown of coadapted gene complexes. Furthermore, these data suggest that translocating bass among even geographically discrete regions or among stocks with reasonable genetic similarity can result in substantial performance alterations at the F(1) generation.
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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 | 0.000 |
| 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".