Estimating the scale of fish feeding movements in rivers using δ<sup>13</sup><i>C</i>signature gradients
Bibliographic record
Abstract
1. Isotopic signatures of consumers provide a time integration of their feeding history, and as a result of movements, are often out of line with signatures of their local resources. Such disequilibrium can be useful for inferring the spatial scale of consumer movement. 2. delta(13)C signatures of dissolved inorganic carbon as well as periphyton and invertebrates, exhibit pronounced gradients along rivers. We outline an analytical framework to estimate the spatial scale of movement of riverine fish by comparing the slopes of their delta(13)C signature gradients to that of the stream invertebrates they consume. For free-ranging juvenile Atlantic salmon (Salmo salar L.), unconstrained by barriers, delta(13)C signatures departed considerably from invertebrate signatures, and along-stream slopes were as little as half those recorded for stream invertebrates. Movement estimates for these fish, based on their signature slopes, are approximately 20 km. 3. By contrast, stream resident salmonids (whose movements are constrained by physical barriers) and sedentary taxa such as sculpins and sticklebacks, have carbon signatures much closer to invertebrate signatures where they were collected. For these groups, our method yields negligible estimates of movement, similar to those of invertebrates. 4. Although this method cannot provide precise estimates of how much individual organisms move, or reveal details of movement history, it may provide an effective complement to telemetric and other methods of studying movement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".