Should animals navigating over short distances switch to a magnetic compass sense?
Bibliographic record
Abstract
Magnetoreception can play a substantial role in long distance navigation by animals. I hypothesize that locomotion guided by a magnetic compass sense could also play a role in short distance navigation. Animals identify mates, prey, or other short distance navigational goals using different sensory modalities (olfaction, vision, audition, etc.) to detect sensory cues associated with those goals. In conditions where these cues become unreliable for navigation (due to flow changes, obstructions, noise interference, etc.), switching to a magnetic compass sense to guide locomotion toward the navigational goals could be beneficial. Using simulations based on known locomotory and flow parameters, I show this strategy has strong theoretical benefits for the nudibranch mollusk Tritonia diomedea navigating toward odor sources in variable flow. A number of other animals may garner similar benefits, particularly slow-moving species in environments with rapidly changing cues relevant for navigation. Faster animals might also benefit from switching to a magnetic compass sense, provided the initial cues used for navigation (acoustic signals, odors, etc.) are intermittent or change rapidly enough that the entire navigation behavior cannot be guided by a continuously detectable cue. Examination of the relative durations of navigational tasks, the persistence of navigational cues, and the stability of both navigators and navigational targets will identify candidates with the appropriate combination of unreliable initial cues and relatively immobile navigational goals for which this hypothetical behavior could be beneficial. Magnetic manipulations can then test whether a switch to a magnetic compass sense occurs. This hypothesis thus provides an alternative when considering the behavioral significance of a magnetic compass sense in animals.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".