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

J Chem Ecol. 2018 Dec;44(12):1084-1100. doi: 10.1007/s10886-018-1017-2. Epub 2018 Sep 21.

Abstract

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.

Keywords: Computational modeling; Fluid dynamics; Insect; Olfaction; Sensilla; Sniffing.

MeSH terms

  • Air
  • Animals
  • Arthropod Antennae / metabolism
  • Biological Evolution
  • Models, Theoretical*
  • Odorants* / analysis
  • Water / chemistry

Substances

  • Water