Journal of Chemical Ecology

, Volume 44, Issue 12, pp 1084–1100 | Cite as

What Can Computational Modeling Tell Us about the Diversity of Odor-Capture Structures in the Pancrustacea?

  • Lindsay D. WaldropEmail author
  • Yanyan He
  • Shilpa Khatri


A major transition in the history of the Pancrustacea was the invasion of several lineages of these animals onto land. We investigated the functional performance of odor-capture organs, antennae with olfactory sensilla arrays, through the use of a computational model of advection and diffusion of odorants to olfactory sensilla while varying three parameters thought to be important to odor capture (Reynolds number, gap-width-to-sensillum-diameter ratio, and angle of the sensilla array with respect to oncoming flow). We also performed a sensitivity analysis on these parameters using uncertainty quantification to analyze their relative contributions to odor-capture performance. The results of this analysis indicate that odor capture in water and in air are fundamentally different. Odor capture in water and leakiness of the array are highly sensitive to Reynolds number and moderately sensitive to angle, whereas odor capture in air is highly sensitive to gap widths between sensilla and moderately sensitive to angle. Leakiness is not a good predictor of odor capture in air, likely due to the relative importance of diffusion to odor transport in air compared to water. We also used the sensitivity analysis to make predictions about morphological and kinematic diversity in extant groups of aquatic and terrestrial crustaceans. Aquatic crustaceans will likely exhibit denser arrays and induce flow within the arrays, whereas terrestrial crustaceans will rely on more sparse arrays with wider gaps and little-to-no animal-induced currents.


Olfaction Sensilla Insect Computational modeling Fluid dynamics Sniffing 



The authors wish to acknowledge the following funding sources: funds from the New Mexico Institute of Mining and Technology to L. Waldrop; computational al- locations to L. Waldrop from the Extreme Scientific and Engineering Discovery Environment (XSEDE) TG-CDA160015 and TG-BIO170090; and funding to S. Khatri from the National Science Foundation Physics of Living Systems #1505061.

The authors wish to thank Swayamjit Ray, Anjel Helms, and Loren Rivera for organizing the “Chemical Ecology in the New Era of Technology” symposium; Laura Miller, Amneet Bhalla, and Boyce Griffith for help with IBAMR; David O’Neal at Pittsburgh Supercomputing Center for aid in computing; Sheila Patek, Philip Anderson, Jonathan Rader, and Dennis Evangelista for influential discussions regarding evolutionary biomechanics and two anonymous reviewers for comments that improved the manuscript.


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Authors and Affiliations

  1. 1.Depatment of BiologyNew Mexico Institute of Mining and Technology SocorroSocorroUSA
  2. 2.Depatment of MathematicsNew Mexico Institute of Mining and Technology SocorroSocorroUSA
  3. 3.Applied Mathematics Unit School of Natural SciencesUniversity of CaliforniaMercedUSA

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