Gene flow and genetic structure of two of Arkansas’s rarest darter species (Teleostei: Percidae), the Arkansas Darter, Etheostoma cragini, and the Least Darter, E. microperca
Bibliographic record
Abstract
Distinguishing the effects of naturally caused historical fragmentation from those of contemporary landscape modification is critically important to understanding the consequences of human influences on patterns of gene flow and population dynamics. Nonetheless, relatively few recent studies focusing on this issue have dealt with species that showed evidence of historical fragmentation. In the current study, we disentangled the effects of fragmentation operating over separate timescales on two darter species, Etheostoma cragini and E. microperca, from the Ozark Highlands. Formerly more wide-spread within this region in Arkansas, these species now occur only in highly isolated habitats (i.e., spring-runs). We separated fragmentation effects at distinct spatial and temporal scales by using several molecular loci (i.e., mtDNA/nuclear DNA/nuclear microsatellite DNA), as well as a variety of analytical approaches. Sequence divergence among Ozark and northern populations of E. microperca indicate long-standing isolation resulting from vicariant events. Both species were further isolated in unique ‘island’ habitats, sometimes at fine spatial scales, as shown by sequence divergence among Ozark Highland populations of E. cragini. Microsatellite data also revealed additional subdivision among Arkansas populations with E. cragini divided into three distinct populations and E. microperca into two. Overall, migration rates were similar among contemporary and historical time periods although patterns of asymmetric migration were inverted for E. cragini. Estimates of contemporary effective population size (Ne) were substantially lower for both species than past population sizes. Overall, historical processes involving natural fragmentation have had long-lasting effects on these species, potentially making them more susceptible to current anthropogenic impacts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.020 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 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".