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Spatial memory-based behaviors for locating sources of odor plumes

Overview of attention for article published in Movement Ecology, May 2015
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Title
Spatial memory-based behaviors for locating sources of odor plumes
Published in
Movement Ecology, May 2015
DOI 10.1186/s40462-015-0037-6
Pubmed ID
Authors

Daniel Grünbaum, Mark A Willis

Abstract

Many animals must locate odorant point sources during key behaviors such as reproduction, foraging and habitat selection. Cues from such sources are typically distributed as air- or water-borne chemical plumes, characterized by high intermittency due to environmental turbulence and episodically rapid changes in position and orientation during wind or current shifts. Well-known examples of such behaviors include male moths, which have physiological and behavioral specializations for locating the sources of pheromone plumes emitted by females. Male moths and many other plume-following organisms exhibit "counter-turning" behavior, in which they execute a pre-planned sequence of cross-stream movements spanning all or part of an odorant plume, combined with upstream movements towards the source. Despite its ubiquity and ecological importance, theoretical investigation of counter-turning has so far been limited to a small subset of plausible behavioral algorithms based largely on classical biased random walk gradient-climbing or oscillator models. We derive a model of plume-tracking behavior that assumes a simple spatially-explicit memory of previous encounters with odorant, an explicit statistical model of uncertainty about the plume's position and extent, and the ability to improve estimates of plume characteristics over sequential encounters using Bayesian updating. The model implements spatial memory and effective cognitive strategies with minimal neural processing. We show that laboratory flight tracks of Manduca sexta moths are consistent with predictions of our spatial memory-based model. We assess plume-following performance of the spatial memory-based algorithm in terms of success and efficiency metrics, and in the context of "contests" in which the winner is the first among multiple simulated moths to locate the source. Even rudimentary spatial memory can greatly enhance plume-following. In particular, spatial memory can maintain source-seeking success even when plumes are so intermittent that no pheromone is detected in most cross-wind transits. Performance metrics reflect trade-offs between "risk-averse" strategies (wide cross-wind movements, slow upwind advances) that reliably but slowly locate odor sources, and "risk-tolerant" strategies (narrow cross-wind movements, fast upwind advances) that often fail to locate a source but are fast when successful. Success in contests of risk-averse vs. risk-tolerant behaviors varies strongly with the number of competitors, suggesting empirically testable predictions for diverse plume-following taxa. More generally, spatial memory-based models provide tractable, explicit theoretical linkages between sensory biomechanics, neurophysiology and behavior, and ecological and evolutionary dynamics operating at much larger spatio-temporal scales.

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Mendeley readers

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The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Faroe Islands 1 2%
Unknown 53 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 28%
Researcher 7 13%
Student > Master 6 11%
Student > Doctoral Student 4 7%
Other 3 6%
Other 8 15%
Unknown 11 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 24%
Engineering 11 20%
Neuroscience 5 9%
Psychology 5 9%
Environmental Science 3 6%
Other 4 7%
Unknown 13 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2016.
All research outputs
#18,458,033
of 22,870,727 outputs
Outputs from Movement Ecology
#285
of 315 outputs
Outputs of similar age
#192,569
of 264,408 outputs
Outputs of similar age from Movement Ecology
#5
of 6 outputs
Altmetric has tracked 22,870,727 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 315 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. This one is in the 3rd percentile – i.e., 3% of its peers scored the same or lower than it.
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