Designing Sortable Guilds for Multispecies Selective Fish Passage
Bibliographic record
Abstract
ABSTRACT The importance of connectivity for freshwater organisms is widely recognised, yet in‐stream barriers associated with population declines and increased risk of extinction remain globally ubiquitous. Despite their negative consequences, these barriers can protect aquatic communities by limiting the spread of invasive species, leading to conflicting management goals in some regions. Selective fish passage is a solution for the conflicting goals of passing native, desirable species while restricting the spread of invasives. Approaches that can target groups of species sharing similar attributes (i.e. guilds) are likely to be more efficient than those that target species individually, particularly in taxonomically diverse systems. We explored the guild structure of 220 Great Lakes freshwater fishes based on morphological, phenological, physiological and behavioural attributes associated with passage and movement. We identified five distinct guilds as well as the attributes most important for defining these groupings: maximum total length, trophic level, relative eye size, spawning temperature, spawning season, presence/absence of ampullary electroreceptors and the presence/absence of hearing specialisations. The approaches outlined in this work can be generalised to enhance selective fish passage in aquatic ecosystems worldwide.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".