Orb weaving spiders employ a “silken toolkit” to accomplish a range of tasks, including retaining prey that strike their webs. This is accomplished by a viscous capture thread spiral thread that features tiny glue droplets, supported by a pair of elastic flagelliform fibers. Each droplet contains a glycoprotein core responsible for adhesion. However, prey retention relies on the integrated performance of multiple glue droplets and their supporting fibers, with previous studies demonstrating that a suspension bridge forms, whose biomechanics sum the adhesive forces of multiple droplets while dissipating the energy of the struggling insect. While the interdependence of the droplet’s glycoprotein and flagelliform fibers for functional adhesion is acknowledged, there has been no direct test of this hypothesized linkage between the material properties of each component. Spider mass, which differs greatly across orb weaving species, also has the potential to affect flagelliform fiber and glycoprotein material properties. Previous studies have linked spider mass to capture thread performance but have not examined the relationship between spider mass and thread material properties. We extend earlier studies to examine these relationships in 16 orb weaving species using phylogenetic generalized least squares. This analysis revealed that glycoprotein stiffness (elastic modulus) was correlated with flagelliform fiber stiffness, and that spider mass was related to the glycoprotein volume, flagelliform fiber cross-sectional area and droplets per unit thread length. By shaping the elastic moduli of glycoprotein adhesive and flagelliform fibers, natural selection has maintained the biomechanical integration of this adhesive system.

Thread measurements: 

Web samples were collected from fresh orb webs in nature. A metal frame with double sided tape (3M #9086K29550360) on its rim was pressed from behind a web, ensuring that a web’s native tensions were preserved. Once adhered to the taped rim, the remaining web was separated by hand along the outer edge of the frame, isolating the sample. Samples were brought back to lab as soon as possible for testing. To prepare individual droplets for testing, we collected a thread on carbon tape covered forceps to ensure natural thread tension was maintained. After contacting a thread strand with the forceps, we cut the connecting threads with a pair of iris scissors. This sample then spanned the 4.8mm space between the supports of a microscope slide sampler (Opell et al., 2011). We ensured that these threads were perpendicular to the supports, guaranteeing consistency in the length of the tested thread and the angle of droplet extension. To ensure that only a single droplet contacted our probe, we isolated the central droplet of the suspended strand. Droplets on either side were slid away from the central droplet using a wooden applicator stick that was whittled to a fine tip, exposing a few xylem fibers.

Droplets were tested in a sealed chamber to maintain humidity at 55% relative humidity. With the desired humidity achieved, droplets were extended using a probe. Before each test, the 413µm tip of this polished steel probe was cleaned with 100% ethanol on a Kimwipe® or Whatman® filter paper. After inserting the probe into a port in the side of the chamber, the probe was locked into a support resting beside the microscope to prevent its movement (Opell et al., 2018). The isolated droplet was then brought into contact with the probe tip using the microscope’s mechanical stage. The adhered droplet was extended until it pulled off from the thread. Extending these droplets provided the angle of extension and stress strain curves, thus providing the elastic modulus and toughness. Seperate droplets were flattened with a device the dropped a coverslip onto the threads, allowing us to measure droplet volume and glycoprotein from surface area measurements. 

Flagelliform fiber properties of A. pegnia, A. argentata, M. sagitatta, and N. oaxacensis, and T. elongata capture threads were newly measured. Additional threads from each individual’s web were secured to cardboard samplers and sent to the American Museum of Natural History for characterization of their elastic modulus and toughness using a Nano Bionix instrument. Similar methodology and instrumentation was used by Sensenig et al., 2010 to determine these properties for eleven of the study species present in the literature. The flagelliform fiber features of C. conica were used for the similarly sized species C. turbinata included in this study (Sensenig et al., 2010).

PGLS:

We used phylogenetic generalized-least squares (PGLS) to examine relationships among the capture thread material properties under Brownian Motion, with Pagel’s lambda to detect phylogenetic signal (Pagel, 1999). The phylogeny used in this analysis is based on a time calibrated tree produced from BEAST (Dimitrov et al., 2017). Details on how this tree was edited can be found in glycoPGLS.R. Having a complete 16 species tree, we used PGLS to examine relationships among traits and plot phylomorphospace plots, carried out using the ape, caper, geiger, and phytools packages in R (Revell, 2012; Pennell et al., 2014; Orme et al., 2018; Paradis & Schliep, 2019; R Core Team, 2019).

Sensitivity analyses:

Our tree editing introduced considerable uncertainty in our results, as the placement of additional taxa stems from taxonomic knowledge instead of phylogenetic. Four species: A. pegnia, N. crucifera, N. oaxacensis, and M. sagitatta were added in this manner. The placement of A. aurantia and V. arenata were based on other phylogenies, but these were derived from different datasets that feature different sampling of spider diversity (Garrison et al., 2016; Scharff et al., 2019). What may compound this uncertainty is the varying nodal support across the branches of our input tree, with broad confidence intervals around the divergence times among these relationships as well. Therefore, it’s necessary to examine alternate topologies and branch lengths to assess the influence of constructing our 16 species phylogeny in its present form. To assess the impact of adding species to our phylogeny, we created seven alternate phylogenies. Six of these alternate phylogenies featured a random placement of a single “new” species (A. pegnia, A. aurantia, N. crucifera, N. oaxacensis, M. sagitatta or V. arenata). The randomized trees were the basis of our sensitivity analysis (prepped in glycoPGLS.R). The actual sensitivty analyses (using SensiPhy package in R) were carried out in Sensitivity.R.