Identification of Arctic char stocks in the Cambridge Bay area, Nunavut Territory, and evidence of stock mixing during overwintering
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Bibliographic record
Abstract
I examined samples of anadromous Arctic char spawners from twelve locations in the Cambridge Bay area, Nunavut Territory, for evidence of stock structuring.These samples could be distinguished from one another on the basis of differences in morphologicai characters, using discriminant function analysis.Significant differences in the means of morphometric characters (ANOVA, minimum p < 0.05) were evident for most pair-wise comparisons.The morphometric characters that contributed the most to the discrimination were orbital length, maxillary width, and head depth.Discrimination among samples was less effective using meristic counts, but many significant differences were observed in pair-wise comparisons, and results paralleled those from the morphometric analysis.The meristic counts that contributed most to the discrimination were anal fin ray count, pyloric caeaa count, and upper gill raker count.There was evidence of reproductive isolation among these spawning aggregations, based on significant differences (p < 0.05, p < 0.001) in allele frequencies for Malic Enzyme between some samples of spawners.I present clear evidence of homing to natal spawning grounds based on significant differences among samples (ANOVA, minimum p < 0.05) in mean strontium (Sr) concentrations (micro-PIXE) in the eariy growth regions of otoliths of spawners.The consistency of the Sr concentrations among all age groups within each sampie of spawners is evidence of philopatry.I conclude that anadromous Arctic char in the study area home to a high degree and have formed discrete stocks, both within and between river systems.Samples of nonspawning Arctic char captured in autumn upstream migrations as they returned to fresh water showed considerable heterogeneity in morphometric characters (cluster analysis and discriminant function analysis) and otolith Sr concentrations in the early growth regions.This is evidence that these upstream migrations are composed of an admixture of stocks.Nonsatisfaction of Castle-Hardy-V/einberg equilibrium (Malic Enzyme, heterozygote deficiency) in one sample provides additional evidence of mixing of stocks during this overwintering migration.The Arctic char is very important to the economy of the Inuit of the study area and is harvested regularly.Threats to the genetic diversity of this species, contained within the aggregate of these discrete stocks, include habitat destruction and harvest.In order to preserve the genetic diversity of individual stocks, an effective management strategy must be developed and implemented.I present an "Adaptive Management" approach for future consideration.This approach utilizes the traditional ecological knowledge of the resource users, in particular the location of spawning grounds, and couples it with the biological complexities of this species.Harvest plans need to be developed, based on this information, so that individual stocks can be harvested at a level that will not adversely affect the genetic diversity of the species.
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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 it