Additional Navigational Strategies Can Augment Odor-Gated Rheotaxis for Navigation under Conditions of Variable Flow
Bibliographic record
Abstract
The navigation strategies animals use to find sources of odor depend on the olfactory stimuli, the properties of flowing fluids, and the locomotory capabilities of the animal. In high Reynolds number environments, animals typically use odor-gated rheotaxis to find the source of turbulent odor plumes. This strategy succeeds because, although turbulence creates an intermittent chemical cue, the animal follows the (continuous) directional cue created by the flow that is transporting the chemical. However, in nature, animals may lose all contact with an odor plume as variations in the direction of bulk flow cause the plume to be rotated away before the animal reaches the source of the odor. Our goal was to use a mathematical model to test the hypothesis that strategies that augment odor-gated rheotaxis would be beneficial for finding the source of an odor plume in such variable flow. The model links a stochastic variable-direction odor plume with a turbulence-based intermittent chemical signal and four different movement strategies, including: odor-gated rheotaxis alone (as a control), odor-gated rheotaxis augmented by further rheotaxis in the absence of odor, odor-gated rheotaxis augmented by a random walk, and odor-gated rheotaxis augmented by movement actively guided by the heading of the flow when the odor was still present. We found that any of the three augmented strategies could improve on strict odor-gated rheotaxis. Moreover, variations in performance caused the best strategy to depend on the speed of movement of the animal and the magnitude of the variation in flow, and more subtly on the duration over which the augmented strategy was performed. For most combinations of parameters in the model, either augmenting with a random walk or following the last-known heading were the best-performing strategies. Overall, our results suggest that marine animals that rely on odor cues to navigate in turbulent environments may augment odor-gated rheotaxis with additional movements that will increase the probability of finding the sources of odors. Moreover, we believe our approach to modeling odor plumes in variable flows is a valuable step toward mathematically capturing the key conditions experienced by animals navigating on the basis of odors carried by flows.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".