Past, present, and future of a freshwater fish metapopulation in a threatened landscape
Bibliographic record
Abstract
It is well documented that hydropower plants can affect the dynamics of fish populations through landscape alterations and the creation of new barriers. Less emphasis has been placed on the examination of the genetic consequences for fish populations of the construction of dams. The relatively few studies that focus on genetics often do not consider colonization history and even fewer tend to use this information for conservation purposes. As a case study, we used a 3-pronged approach to study the influence of historical processes, contemporary landscape features, and potential future anthropogenic changes in landscape on the genetic diversity of a fish metapopulation. Our goal was to identify the metapopulation's main attributes, detect priority areas for conservation, and assess the consequences of the construction of hydropower plants for the persistence of the metapopulation. We used microsatellite markers and coalescent approaches to examine historical colonization processes, traditional population genetics, and simulations of future populations under alternate scenarios of population size reduction and gene flow. Historical gene flow appeared to have declined relatively recently and contemporary populations appeared highly susceptible to changes in landscape. Gene flow is critical for population persistence. We found that hydropower plants could lead to a rapid reduction in number of alleles and to population extirpation 50-80 years after their construction. More generally, our 3-pronged approach for the analyses of empirical genetic data can provide policy makers with information on the potential impacts of landscape changes and thus lead to more robust conservation efforts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".