DOI: 10.5061/dryad.w3r22810d
title: Nanoscale ultrastructures increase the visual conspicuousness of signalling traits in obligate cleaner shrimps

description: To be effective, signals must be detectable; thus, signal theory predicts
 that organisms should evolve signals that are conspicuous to intended
 receivers in natural signalling environments. Cleaner shrimps remove
 ectoparasites from reef fish clients and many signal their intent to clean
 by whipping their long, white antennae. Since white is a reliably
 conspicuous colour in aquatic environments, we hypothesized that selection
 has acted to increase broad-spectrum antennal reflectance in these
 species. We compared reflectance and antennae ultrastructure in three
 obligate cleaner species with one facultative cleaner and one non-cleaner
 in two families (Palaemonidae and Lysmatidae). Obligate cleaner antennae
 had a reflectance of 41-52% of human-visible light, compared to 35% in the
 facultative cleaner and 21% in the non-cleaner. Scanning electron
 microscopy (SEM) revealed the antennae in two obligate cleaner species
 contain a layer of densely packed, high refractive index spheres
 (300-400nm diameter), which optical models showed are effective at
 increasing reflectance. In the third obligate cleaner, SEM showed thick
 (~6µm) chitinous layers that may also increase reflectance. The
 facultative and non-cleaning species had no visible antennae
 ultrastructure beyond chitinous exoskeleton. Our results suggest that some
 obligate cleaners have evolved ultrastructural modifications that increase
 the conspicuousness of the antennae as signals.
description: <em>Reflectance Measurements</em>
 We used calibrated photography under a stereomicroscope to
 measure reflectance from the antennae following methods in [22].
 Calibrated photography was used instead of spectoradiometry because
 cleaner shrimp antennae are cylindrical rather than flat, causing light to
 scatter in directions that are not captured by the fibre optic sensor,
 likely underestimating reflectance. In brief, photographs of antennae were
 taken with an iPhone (model 13, Apple Inc., Cupertino, CA) and included a
 reflectance standard comprising five grey paint swatches of measured
 reflectance. We measured the 0-255 value from each swatch of the grey
 standard (using the image analysis software Fiji [23]), using only the
 green channel of the sRGB image. The green channel was used both to
 approximate as closely as we are able brightness vision in particular, and
 because of the three colour channels, it is most closely aligned with the
 ambient illuminant on a coral reef [24]. We then plotted the green values
 of the grey standards against their known reflectance values, and fit
 exponential equations to these values to create a calibration equation for
 each photograph. Then, in Fiji, we measured green-channel values from four
 to ten regions on each antenna; the number of regions sampled did not
 affect our results, as randomly sampling only 4 regions from each specimen
 and re-running our analyses did not change our conclusions in any
 instance. We then converted these antennae values to reflectance using the
 calibration equations generated from the grey standards. We averaged
 reflectance values across individuals to yield a single measure of
 antennal reflectance for each specimen, and averaged across specimens to
 yield average values for each species, for use in analysis.
   <em>Scanning Electron
 Microscopy</em> To identify underlying structural
 features that may enhance antennae reflectance we used SEM.  Two 3mm long
 sections of antenna per animal were excised from two specimens per species
 and fixed for 12 hours in 2.5% glutaraldehyde buffered with artificial
 seawater. After fixation, each sample went through a dehydration series of
 30%, 30%, 50%, 50%, 70%, 70%, 90%, 90%, 100%, 100%, 100% EtOH (15
 minutes/step). Samples were then dried using a LADD CPD3 critical point
 dryer (Ladd Research Industries, Williston, VT, USA) to preserve tissue
 ultrastructure. Once dried, samples were freeze-fractured to expose the
 cross-section, mounted on aluminium SEM stubs with copper tape, and
 sputter-coated with an ~8nm thick layer of gold (Denton Desk V; Denton
 Vacuum LLC, Moorestown, NJ, USA). The samples were imaged using an Apreo S
 scanning electron microscope (ThermoFisher Scientific, Waltham, MA, USA)
 at the Duke University Shared Materials and Instrumentation Facility with
 an acceleration voltage of 1kV and magnifications of 2500x–15000x. We used
 Fiji [25] for morphometric analyses of the sphere layer found using
 SEM.   <em>Optical
 Modelling</em> In two of the three obligate
 cleaner species, SEM images showed a layer of spherical nanoparticles
 inside the cuticle layer. To investigate how the morphology and optical
 properties of these particles impact antennae reflectance, we performed
 finite-difference time-domain simulations (FDTD) using the Lumerical
 solver version 2020b (Ansys, Canonsburg, PA, USA). Random close-packed
 aggregations of spheres mimicking the arrangement observed in the antennae
 were generated using the Uniform Random Particle Distribution (URPD)
 structure in Lumerical. We performed three sets of
 simulations to determine the effects of sphere refractive index, sphere
 layer thickness, and sphere layer diameter on reflectance. First, to
 determine the effect of sphere refractive index on reflectance, we
 simulated a 2µm thick layer of non-absorbing spheres underneath a 5µm
 layer of homogenous chitin, varying sphere refractive index from 1.57
 (approximately that of chitin) to 2.00 (a lower estimate of that of the
 pteridine granules found in white Pierid butterflies [11]) in increments
 of 0.01. Notably, this range encompassed the refractive index of
 isoxanthopterin (1.78), which prior work has identified as the molecular
 basis of the spheres underlying white body colouration in
 <em>Lysmata amboinensis </em>(one of the obligate cleaners
 studied here)<em> </em>[12]. Second, we simulated layers of
 spheres (randomly assigned diameters between 300-400nm, based on what was
 found in <em>A. pedersoni </em>and <em>L.
 amboinensis</em>) between 1µm and 10µm thick in 300nm thickness
 intervals to determine how reflectance changes with layer thickness.
 Third, we simulated the effects of sphere diameter on the reflectance of a
 2µm thick layer of spheres (again based on what we observed in
 <em>A. pedersoni </em>and <em>L. amboinensis</em>)
 ranging between 100nm and 1000nm in diameter, in 30nm intervals; within
 each simulation, all spheres had the same diameter (to within 5nm of one
 another).  For investigating the effects of both layer thickness and
 sphere diameter, we simulated three different sphere refractive indices,
 1.57 (chitin), 1.78 (isoxanthopterin), and 2.00 (pteridine), with a
 background matrix equal to the refractive index of seawater
 (1.34). All simulations were performed in a 4µm x 4µm x
 12µm domain with periodic boundary conditions in the x and y directions,
 broadband (400nm – 700nm) plane wave source propagating in the z
 direction, and perfectly-matched layer boundary conditions in the z
 direction (a computational representation of open boundaries that does not
 reflect any light at the edges of the domain). Although we simulated one
 sphere layer, antennae are effectively one layer wrapped into a cylinder,
 meaning that most incident light upon the antennae passes through two
 layers. Therefore, we report reflectance as: R +
 RT<sup>2</sup>, where R is the reflectance of one layer and T
 is the transmittance, as this equation accounts for reflectance of the
 front layer, plus reflectance of the back layer after having passed
 through the front layer twice.
description: # READ ME GUIDE TO SUPPLEMENTAL DATA AND CODE FILES Caves et al.,
 Nanoscale ultrastructures increase the visual conspicuousness of
 signalling traits in obligate cleaner shrimps. Journal of Experimental
 Biology. R_code.R: -An R script which runs all of the analyses and creates
 all of the figures in the manuscript and extended data. -Three files are
 necessary to run the complete R script: 1\)
 `Reflectance_calibrated_photography.csv`: this file contains reflectance
 data generated using calibrated color photography, for various species of
 shrimps ``` Columns are: -Species: Shrimp species -Specimen: a number
 indicating which individual of a given species reflectance values are
 taken from -Measurement: multiple measurements were taken per individual;
 this column indicates which measurement number a reflectance value is
 associated with -Reflectance: measured reflectance in percent -Type:
 Shrimp type (either “cleaner”, “facultative cleaner”, “or non cleaner”)
 -Category: A categorical variable for the purposes of statistically
 comparing reflectance in cleaners versus others (either “cleaner” or “non
 cleaner”) ``` 2\) `CombinedSphereMeasurements.csv`: this file contains
 measurements (taken from Scanning Electron Microscope images) of the width
 of spheres in Ancylomenes pedersoni and Lysmata amboinensis ``` Columns
 are: -Specimen: A unique identifier for each specimen measured -Width: the
 width of the measured sphere; multiply by 1000 for nanometers -Species:
 either AP (Ancylomenes pedersoni) or LA (Lysmata amboinensis) ``` 3\)
 `SimulationData.csv`: this file contains data output from FDTD simulations
 run in Lumerical, specifically simulated reflectance varying refractive
 index, layer thickness, and sphere diamter (details in main text) ```
 Columns are: -RI_Diam: Sphere diameter in simulations varying diameter
 (see Figure 2D and main text) -RI_1_57_adj: simulated reflectance with
 varying sphere diameter, with refractive index of 1.57 (chitin); see
 Figure 2D and main text -RI_1_78_adj: simulated reflectance with varying
 sphere diameter, with refractive index of 1.78 (isoxanthopterin); see
 Figure 2D and main text -RI_2_00_adj: simulated reflectance with varying
 sphere diameter, with refractive index of 2.00 (pteridines); see Figure 2D
 and main text -Thickness: Layer thickness in simulations varying layer
 thickness (see Figure 2C and main text) -Thickness_1_57_adj: simulated
 reflectance with varying layer thickness, with refractive index of 1.57
 (chitin); see Figure 2C and main text -Thickness_1_78_adj: simulated
 reflectance with varying layer thickness, with refractive index of 1.78
 (Isoxanthopterin); see Figure 2C and main text -Thickness_2_00_adj:
 simulated reflectance with varying layer thickness, with refractive index
 of 2.00 (pteridines); see Figure 2C and main text -Presence_RI: refractive
 index for simulations varying refractive index (see Figure 2B and main
 text) -Presence_Refl_adj: simulated reflectance with varying refractive
 index (see Figure 2B and main text) ```