Selective fragmentation and the management of fish movement across anthropogenic barriers
Why this work is in the frame
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Bibliographic record
Abstract
Disruption of movement patterns due to alterations in habitat connectivity is a pervasive effect of humans on animal populations. In many terrestrial and aquatic systems, there is increasing tension between the need to simultaneously allow passage of some species while blocking the passage of other species. We explore the ecological basis for selective fragmentation of riverine systems where the need to restrict movements of invasive species conflicts with the need to allow passage of species of commercial, recreational, or conservation concern. We develop a trait-based framework for selective fish passage based on understanding the types of movements displayed by fishes and the role of ecological filters in determining the spatial distributions of fishes. We then synthesize information on trait-based mechanisms involved with these filters to create a multidimensional niche space based on attributes such as physical capabilities, body morphology, sensory capabilities, behavior, and movement phenology. Following this, we review how these mechanisms have been applied to achieve selective fish passage across anthropogenic barriers. To date, trap-and-sort or capture-translocation efforts provide the best options for movement filters that are completely species selective, but these methods are hampered by the continual, high cost of manual sorting. Other less effective methods of selective passage risk collateral damage in the form of lower or higher than desired levels of passage. Fruitful areas for future work include using combinations of ecological and behavioral traits to passively segregate species; using taxon-specific chemical or auditory cues to direct unwanted species away from passageways and into physical or ecological traps while attracting desirable species to passageways; and developing automated sorting mechanisms based on fish recognition systems. The trait-based approach proposed for fish could serve as a template for selective fragmentation in other ecological systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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 it