Data from: Volatile fatty acid and aldehyde abundances evolve with behavior and habitat temperature in Sceloporus lizards
Campos, Stephanie et al. (2020), Data from: Volatile fatty acid and aldehyde abundances evolve with behavior and habitat temperature in Sceloporus lizards, Dryad, Dataset, https://doi.org/10.5061/dryad.83bk3j9nr
Animal signals evolve by striking a balance between the need to convey information through particular habitats and the limitations of what types of signals can most easily be produced and perceived. Here, we present new results from field measures of undisturbed behavior and biochemical analyses of scent marks from 12 species of Sceloporus lizards to explore whether evolutionary changes in chemical composition are better predicted by measures of species behavior , particularly those associated with visual displays, chemoreception, and locomotion, or by measures of habitat climate (precipitation and temperature). We found that more active lizard species used fewer compounds in their volatile scent marks, perhaps conveying less specific information about individual, sex and species identity. Scent marks from more active lizard species also had higher proportions of saturated fatty acids, and the evolution of these compounds has been tracking the phylogeny closely as we would expect for a metabolic by-product. In contrast, the proportions of unsaturated fatty acids were better explained by evolutionary shifts in habitat temperature (not precipitation), with species in warmer climates using almost no volatile unsaturated fatty acids. The proportion of aldehydes was explained by both behavior and environment, decreasing with behavioral activity and increasing with habitat temperature. Our results highlight the evolutionary flexibility of complex chemical signals, with different chemical compounds responding to different elements of the selective landscape over evolutionary time.
Collection of chemical and behavioral data
We collected femoral pore secretions and recorded behavior of adult males in the Sceloporus lizard genus between May 2012 and August 2016 at sites and using methods described in Campos et al., 2020 as part of a larger study of the evolution of multimodal signals in Sceloporus lizards (Hews and Martins, 2013; Martins et al., 2015; Pruett et al., 2016; Romero-Diaz et al., 2019). For each species, we collected behavioral and chemical data from the same population, collecting data at comparable points in species breeding seasons, such that the intensity of male territorial aggression was similar. Since reproductive timing can vary annually with environmental factors (Smith et al., 1995), we also confirmed mating activity through observed courtship and aggressive territorial displays by males. We first filmed a lizard and subsequently caught the lizard to collect its secretions, when possible. This data set includes chemical and behavioral data from Sceloporus virgatus, Sceloporus jarrovii, Sceloporus megalepidurus, Sceloporus grammicus, Sceloporus undulatus, Sceloporus parvus, Sceloporus variabilis, Sceloporus cozumelae, Sceloporus siniferus, Sceloporus merriami, Sceloporus graciosus and Sceloporus occidentalis.
We recorded the undisturbed behavior of 20-30 adult males per species during their respective breeding season, approaching individuals to an average distance of 4-5 m, and filming for up to 10 min during their daily activity period. We scored videos for chemical and visual displays and locomotion, then calculated species’ averages for rates of behavior. Chemical behavior, involved in olfaction and vomerolfaction, included licks (tongue touch to substrate), tongue flicks (tongue in air), lip smacks (rapid opening and closing of the mouth), and chin wipes (jaw rub across substrate). For contrast, we also counted the number of Headbob Displays, stereotyped and species-typical series of up-and-down movements of the head and torso used in social interactions. Many forms of chemical behavior occur as lizards move around their environments, so we also scored general activity levels in two ways. First, we counted the number of short Locomotion Bouts, or episodes in which the subject moved distances <10 cm, which were often associated with chemical sensing or visual display behavior in this study. Second, we calculated the number of all behavioral acts as a measure of total Activity, summing the total number of short distance locomotory movements (< 10 cm), long distance movements (> 10 cm), chemical behavior (tongue flicks plus jaw rubs, counted individually), visual display behavior (headbob displays plus shudder displays, counted as individual bouts), adjustments (small motions of the head or torso that do not move the lizard from one place to another), attacks and tail wags. For each behavioral measure, we estimated the count of behavior per hour and used this frequency in statistical analyses.
Chemical analysis of secretions
We extracted secretions from lizard pores using alcohol-cleaned forceps and wearing nitrile gloves, then stored secretions in 2 mL glass vials with Teflon®-lined screw caps at -20 ºC. At Indiana University’s Institute for Pheromone Research, we used stir bar (Gerstel Twister® PDMS-coated magnetic stir bars) sorptive extraction to chemically analyze secretions (Pruett et al., 2016; Soini et al., 2005). For S. graciosus, S. variabilis, S. occidentalis, and S. grammicus, we analyzed samples from six individuals per species. Samples weighed 1.1–2.2 mg, 1.8–2.4 mg, 1.5–1.8 mg, and 2–2.7 mg for each species, respectively. For other species, we pooled samples from multiple individuals to obtain sufficient quantities for analysis. We combined secretions from 17 S. virgatus, 7 S. jarrovii, and 13 S. megalepidurus males to create six pooled samples per species weighing 1.6–2.4 mg, 1.8–2.5 mg, and 1.8–2.4 mg, respectively. We pooled secretions from 14 S. undulatus individuals into three samples, weighing 0.7–2.9 mg. For S. cozumelae, S. parvus, S. siniferus, and S. merriami we used samples and measures previously described in Pruett et al. (2016), which are two samples per species, each pooling secretions from 7–10 individuals and weighing 2 mg. We also added secretions from 13 S. merriami, pooled into four samples (2–4 males per sample, each weighing 1.5–2.0 mg), for a total of six pooled samples for this species.
We chemically analyzed samples using gas-chromatography/mass-spectrometry. We also processed reagent blanks [2 mL OmniSolv™ water (EMD Millipore Corporation, Billerica, MA) with 50 mg ammonium sulfate (Sigma-Aldrich, St.Louis, MO)] as a control. We added an internal standard (IS) of 8 ng of synthetic 7-tridecanone (Sigma-Aldrich, Saint Louis, MO) dissolved in 5 μL methanol (Baker Analyzed, Mallinckrodt Baker Inc., Phillipsburg, NJ) to every sample. We analyzed volatile-embedded stir bars in a Thermal Desorption Autosampler with a Cooled Injection System (TDSA-CIS 4 from Gerstel GmbH) connected to an Agilent 6890 N gas chromatograph – 5973iMSD mass spectrometer (Agilent Technologies, Inc., Wilmington, DE). Other equipment specifications, including oven program and temperature protocol details, are provided in Pruett et al. (2016).
We identified volatile compounds by comparing mass spectra and retention times against references, reference standard compounds when available, and the National Institute of Standards and Technology (NIST) database. We used post-run selected ion currents (SIC) and measured the peak area of each compound. To estimate the relative abundance of a compound, we divided the compound peak area by the IS peak area and sample mass [compound peak area / IS peak area / sample mass]. We calculated species’ averages for Chemical Richness, or the total number of different volatiles, as a proxy for signal complexity (Hebets and Papaj, 2005).
We used climate data deposited in the Dryad Digital Repository to support Lawing et al. (2016). Lawing et al. (2016) estimated mean climate profiles for each Sceloporus species by averaging bioclimate data (from WorldClim database) for each point at which that species has been reported (in the Global Biodiversity Information Facility). They found that BIO4 (temperature seasonality = standard deviation of temperature*100), BIO6 (lowest minimum temperature of the coldest month), BIO12 (mean annual precipitation), and BIO15 (precipitation seasonality = coefficient of variation) were especially important in describing changes in suitable Sceloporus habitat over evolutionary time. To these measures, we added BIO1 (mean annual temperature) in our analysis as a point of comparison to other studies. As the best available estimate of the climate experienced by the species as a whole, we used mean climate measures averaged across all recorded locations for each species. Although these measures may not accurately reflect the specific climates experienced by the lizards we sampled in the field, they are more appropriate for our phylogenetic comparative analyses of long-term evolutionary history. Furthermore, Parker and Mason (2009) demonstrated in snakes that annual periods of low temperature dormancy (as occurs in many seasonal breeders) significantly boosts the synthesis and concentration of sex pheromones, suggesting that habitat temperatures during periods of behavioral inactivity can still be important in shaping signal composition.
These data are from 12 lizard species in the Sceloporus genus, including Sceloporus virgatus, Sceloporus jarrovii, Sceloporus megalepidurus, Sceloporus grammicus, Sceloporus undulatus, Sceloporus parvus, Sceloporus variabilis, Sceloporus cozumelae, Sceloporus siniferus, Sceloporus merriami, Sceloporus graciosus and Sceloporus occidentalis. The genus name has been ommitted from the "Species" column in our data set.
The relative abundances reported for individual compounds in this data set (c1-c47) were calculated as compound peak area / IS peak area / sample mass. In order to calculate the actual abundance of a compound (in ng) in lizard femoral gland secretions (in mg), the numbers we report must be multiplied by 8 ng (i.e., the abundance of Internal Standard added to each sample) to give compound ng / secretion mg.
We report the mass of each sample to the nearest tenth of a mg. Some samples contained the femoral pore secretions of one to several adult males in order to obtain sufficient quanitites for GC-MS detection.
We summed the abundances of compounds 1-47 for each sample and report this total abundance in the "abundance" column.
The "Richness" column is the total number of compounds detected in a given sample of those compounds measured in this study.
Using bioclimate data reported in Lawing et al. (2016), we calculated and report the average for each variable across the entire geographic distribution of each species used in this study.
Behavioral activity measures are reported as frequencies, or the count of behavior per hour. These measures were calculated from baseline (undisturbed) behavior of adult males, and includes frequencies of headbob behavior (BaseHB), chemical display behavior (BaseChem), locomotor behavior (BaseMv10), and behavioral activity (BaseAct).
National Science Foundation, Award: IOS-1050274
National Science Foundation, Award: IOS-1052247
National Institute of Child Health and Human Development, Award: NIH-NICHD 5T32HD049336-10
Georgia State University and the Center for Behavioral Neuroscience
Georgia State University and the Center for Behavioral Neuroscience