Evaluating <sup>87</sup> Sr/ <sup>86</sup> Sr isotope ratios and Sr mass fractions in otoliths of different European freshwater fish species as fishery management tool in an Alpine foreland with limited geological variability
Bibliographic record
Abstract
Abstract The focus of this study was to assess the potential of otolith microchemistry as a fishery management tool for different European freshwater fish species in an Alpine foreland with a diverse range of different water bodies but low geological variation. 87 Sr/ 86 Sr isotope and Sr/Ca ratios in water samples from 26 habitat sites in a pre-alpine catchment region around lake Chiemsee, Germany, an important region for recreational and economic fisheries, were analysed. 87 Sr/ 86 Sr isotope ratios and the Sr mass fractions in otoliths of 246 fish out of 16 species were determined using (laser ablation) inductively coupled plasma mass spectrometry ((LA)-ICP-MS). Habitats could be discriminated into three distinct strontium isotope regions (SIGs) and seven clusters with characteristic 87 Sr/ 86 Sr isotope and Sr/Ca ratios. The direct comparison of 87 Sr/ 86 Sr isotope ratios in water and otolith samples allowed to identify fish that might have been a) migrating b) transferred from other water bodies or c) stocked from fish farms. Sr/Ca ratios in water and the Sr mass fraction in otoliths were highly correlated, although significant differences between species from the same environment could be documented. Sr mass fractions in sagittae of Perca fluviatilis were about 60 % of those in sagittae of Coregonus spp and of lapilli of roach Rutilus rutilus from the same habitats. Different partition factors for water to otolith Sr/Ca mass fractions were determined for different species. Discrimination of fish otoliths by 87 Sr/ 86 Sr isotope ratios and Sr mass fractions according to habitat clusters was possible with success rates ranging from 92 % to 100 % for cyprinids, European perch Perca fluviatilis , whitefish Coregonus spp . and European grayling Thymallus thymallus, and was 74 % for salmonids. Otolith microchemistry proved to have great potential to serve as a fishery management tool at smaller spatial scales such as in the studied Alpine foreland when considering the limited variation of 87 Sr/ 86 Sr isotope and Sr/Ca ratios, the type and spatial distribution of habitats, and the species and question under investigation. Highlights Otolith microchemistry applied in in area with limited geological variability Fish transferred, stocked or migrated were identified Regressions between Sr/Ca ratios in water predict Sr mass fractions in otoliths Species specific Sr discrimination from water into otoliths European freshwater fish species assigned to habitat clusters of origin
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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 | 0.000 |
| 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) | 0.001 | 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".