Non-Lethal Sampling Supports Integrative Movement Research in Freshwater Fish
Bibliographic record
Abstract
Freshwater ecosystems and fishes are enormous resources for human uses and biodiversity worldwide. However, anthropogenic climate change and factors such as dams and environmental contaminants threaten these freshwater systems. One way that researchers can address conservation issues in freshwater fishes is via integrative non-lethal movement research. We review different methods for studying movement, such as with acoustic telemetry. Methods for connecting movement and physiology are then reviewed, by using non-lethal tissue biopsies to assay environmental contaminants, isotope composition, protein metabolism, and gene expression. Methods for connecting movement and genetics are reviewed as well, such as by using population genetics or quantitative genetics and genome-wide association studies. We present further considerations for collecting molecular data, the ethical foundations of non-lethal sampling, integrative approaches to research, and management decisions. Ultimately, we argue that non-lethal sampling is effective for conducting integrative, movement-oriented research in freshwater fishes. This research has the potential for addressing critical issues in freshwater systems in the future.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".