Origins of invasive piscivores determined from the strontium isotope ratio (<sup>87</sup>Sr/<sup>86</sup>Sr) of otoliths
Bibliographic record
Abstract
We examined strontium isotope ratios (87Sr/86Sr) in fish otoliths to determine the origins of invasive piscivores in the Upper Colorado River Basin (UCRB, western USA). We examined87Sr/86Sr from fishes in different reservoirs, as well as the temporal stability and interspecies variability of87Sr/86Sr of fishes within reservoirs, determined if87Sr/86Sr would be useful for “fingerprinting” reservoirs where invasive piscivores may have been escaping into riverine habitat of endangered fishes in the UCRB, and looked for evidence that such movement was occurring. Our results showed that in most cases87Sr/86Sr was unique among reservoirs, overlapped among species in a given reservoir, and was temporally stable across years. We identified the likely reservoir of origin of river-caught fish in some cases, and we were also able to determine the year of possible escapement. The approach allowed us to precisely describe the87Sr/86Sr fingerprint of reservoir fishes, trace likely origins of immigrant river fish, and exclude potential sources, enabling managers to focus control efforts more efficiently. Our results demonstrate the potential utility of87Sr/86Sr as a site-specific and temporally stable marker for reservoir fish and its promise for tracking fish movements of invasive fishes in river–reservoir systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".