POPULATION STRUCTURE IN THREE SPECIES OF CO‐DISTRIBUTED SALMONID FISHES IN THE PEACE RIVER AND TRIBUTARIES NEAR A MAJOR PROPOSED HYDROELECTRIC DEVELOPMENT IN NORTHEASTERN BRITISH COLUMBIA, CANADA
Bibliographic record
Abstract
ABSTRACT Dam construction and reservoir formation represent profound anthropogenic alterations to natural riverscapes, especially in terms of connectivity in migratory fishes. The Peace River in northeastern British Columbia (BC), Canada, is the largest river system in BC, home to 39 native fishes and currently has two major hydroelectric projects, and a third one (‘Site C’) is proposed. Three co‐distributed and migratory fishes, the bull trout ( Salvelinus confluentus ), Arctic grayling ( Thymallus arcticus ) and the mountain whitefish ( Prosopium williamsoni ) are key species in the Peace River ecologically and in terms of recreational fisheries. We examined microsatellite DNA variation in these species to assess genetic diversity, levels of population subdivision and connectivity to better understand potential impacts and to provide baseline information for subsequent monitoring. Expected heterozygosity and number of alleles averaged 0.65 and 7.7, 0.73 and 11.9, and 0.72 and 10.8 for bull trout (nine loci), Arctic grayling (10 loci) and mountain whitefish (10 loci), respectively. Estimates of the effective number of breeders ( N b ) ranged from 35 to 255 for bull trout to over 3700 for Arctic grayling. Population subdivision ( F ST , θ ) was 0.040, 0.063 and 0.023 in bull trout, Arctic grayling and mountain whitefish, respectively (all p < 0.001). Temporal differences within localities for all species accounted for <1% of total variation in allele frequencies. An estimated 6.2% (mountain whitefish), 4.6% (bull trout) and 8.8% (Arctic grayling) of fish samples were inferred ( p < 0.05) to be immigrants to one locality from another locality. Our results suggest that connectivity amongst localities is important to successful completion of the life history of each species, the potential disruption of which will be a critical aspect of post‐development monitoring. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.000 | 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".