A Compound Specific Stable Isotope Analysis of Chinook Salmon Stocks Caught in the Northern and Southern Strait of Georgia
Bibliographic record
Abstract
Chinook salmon, compound specific stable isotopes, Strait of Georgia Chinook Salmon are experiencing concurrent declines across their range (Irvine and Fukuwaka 2011).The situation is pronounced in British Columbia where fishery restrictions have been implemented to protect depleted local Chinook stocks.These stocks are critical to multiple stakeholders including resident killer whales, recreational and Indigenous fisheries (Riddell et al. 2013).Though the marine distribution and ecology of these stocks is poorly resolved, it is known that different stocks inhabit different regions of the NE Pacific, and that they may therefore be exposed to food webs of varying structure, prey biomass and nutritional quality (Weitkamp 2010;Miller et al. 2011;Shelton et al. 2018).Differences in regional food-web ecology and its impacts on Chinook salmon stocks are a significant unknown portion of Chinook life history (Riddell et al. 2018).This study aimed to sample Chinook salmon stocks captured from two regions of the BC Coast (Northern Vancouver Island and Southern Vancouver Island) and to use compound specific stable isotope analysis to investigate the food-web ecology of stocks in each region.Adult Chinook were collected from recreational fishing derbies and trawl surveys during July and August of 2018.Locations in Northern Vancouver Island included Malcolm Island and Campbell River.Locations in Southern Vancouver Island included Sidney and the Strait of Juan de Fuca.All Chinook were analyzed for genetic stock ID.Fraser River and Puget Sound Chinook stocks were chosen for analysis and sub-sampled from both regions when possible.From the Northern region, three Harrison, three Chilliwack and two Snohomish Chinook were sampled.From the Southern region, one Harrison and three Snohomish fish were sampled.In addition, three adult herring from both the Northern and the Southern region were also sampled to provide a 'baseline' isotopic signature for a potential prey species.The following two CSIA analyses were conducted: i) Essential/non-essential amino acid δ 15 N values were used to determine the trophic level of the organism.ii) Essential amino acid δ 13 C values were used to investigate the primary producer source materials underpinning the food web.Trophic level was calculated using the formula: TL= ((δ 15 NGlu -δ 15 NPhe -3.4)/7.6)+ 1.For all Chinook and herring samples, δ 13 C values from 8 essential amino acids (His, Ile, Lue, Lys, Met, Phe, Thr, Val) were standardized and analyzed with a principal component analysis to investigate differences in food web sources in the two regions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".