Predation and Crypsis in the Evolution of Electric Signaling in Weakly Electric Fishes
Bibliographic record
Abstract
Eavesdropping by electroreceptive predators poses a conflict for weakly electric fish, which depend on their Electric Organ Discharge (EOD) signals both for navigation and communication in the dark. The EODs that allow weakly electric fish to electrolocate and communicate in the dark may attract electroreceptive predators such as catfishes and Electric Eels. These predators share with their prey the synapomorphy of passive electric sense supported by ampullary electroreceptors that are highly sensitive to low-frequency electric fields. Any low-frequency spectral components of the EOD make weakly electric fish conspicuous and vulnerable to attack from electroreceptive predators. Accordingly, most weakly electric fish shift spectral energy upwards or cloak low-frequency energy with compensatory masking signals. Subadults and females in particular emit virtually no low-frequency energy in their EODs, whereas courting males include a significant low-frequency component, which likely attracts females, but makes the signals conspicuous to predators. Males of species that coexist with the most predators tend to produce the least low-frequency signal energy, expressing sexual dimorphism in their signals in less risky ways. In these respects, electric signals follow the classic responses to opposing forces of natural and sexual selection, as exemplified in the visual signals of guppies and the acoustic signals of Túngara frogs. Unique to electric fish is that the electric signal modifications that help elude detection by electroreceptive predators are additions to the basal signal rather than losses of attractive components. These enhancements that enable crypsis are energetically costly, but have also provided the evolutionary substrates for subsequent sexual selection and species identity characters.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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 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".