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. 2021 Sep 21;11(20):14146–14161. doi: 10.1002/ece3.8132

Phylogenetic and morphological influence on habitat choice in moisture‐harvesting horned lizards (Phrynosoma spp.)

Anna‐Christin Joel 1,✉, Jenice R N Linde 1, Philipp Comanns 1, Caroline Emonts 1, Margret Weissbach 1, Morris Flecks 2, Dennis Rödder 2,✉
PMCID: PMC8525137  PMID: 34707847

Abstract

In previous studies, the superhydrophilic skin of moisture‐harvesting lizards has been linked to the morphological traits of the lizards’ integument, that is, the occurrence of honeycomb‐shaped microstructures. Interestingly, these structures can also cover the skin of lizards inhabiting wet habitats. We therefore tested the influence of the microstructures’ main features on the habitat choice and wettability in the genus Phrynosoma. The genus Phrynosoma comprises moisture‐harvesting species as well as nonspecialists. Lizards of this genus inhabit large areas of North America with diverse climatic conditions. Remarkably, the differences in the manifestation of microstructures are just as versatile as their surroundings. The phylogeny of the lizards as well as the depth of their ventral microstructures, though independent of each other, correlated with the precipitation in their respective habitat. All other morphological traits, as well as the skin's wettability itself, could not predict the habitat of Phrynosoma species. Hence, it is unlikely that the microstructure influences the wettability, at least directly. Hence, we presume an indirect influence for the following reasons: (a) As the ventral side cannot get wet by rain, but the belly could easily interact with a wet surface, the microstructure might facilitate water absorption from wet soil following precipitation. (b) We found the number of dorsal microstructures to be linked to the occurrence of silt in the habitat. In our study, we observed scales being heavily contaminated, most likely with a mixture of dead skin (after shedding) and silt. As many lizards burrow themselves or even shovel sand onto their backs, deploying the substrate might be a mechanism to increase the skin's wettability.

Keywords: adaptation, desert, drinking, rain harvesting, skin, wettability

Lizards inhabiting arid regions have to harvest water from various sources, as water is scarce. These moisture‐harvesting lizards are suspected to have a specialized microstructure on their skin, rendering the skin superhydrophilic. However, our data do not support this hypothesis. We found soil particles accumulating in the structures, implying that microstructures could function as some sort of "container", accumulating soil and dirt and thus changing the surface chemistry.

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1. INTRODUCTION

High temperatures as well as rare and irregular precipitation characterize arid regions across the world. To survive in such a harsh environment, animals require specialized adaptations, for example, avoiding of overheating and gathering enough water. Efficient water collection from rain, moist air, or soil has been described as “moisture harvesting” and evolved independently in several species (Cardwell, 2006; Lillywhite & Stein, 1987; Norgaard & Dacke, 2010; Repp & Schuett, 2008; Sherbrooke et al., 2007; Yenmiş et al., 2015). Moisture‐harvesting lizards, as one example for these species, show a stereotypical behavior: In several species of the genera Phrynocephalus, Trapelus, and Phrynosoma, this behavior includes (a) lowering of head and tail, (b) raising of abdomen in an arch, (c) splaying of legs, and (d) flattening of the body (Schwenk & Greene, 1987; Sherbrooke, 1990, 2004; Vesely & Modry, 2002). On the other hand, the integument (skin and appendages like scales) of such lizards shows specific adaptations as well. Whereas in wet habitats, like rainforests, the lizards’ scales exhibit superhydrophobic and self‐cleaning properties to prevent infections (Joel & Weissbach, 2019; Watson et al., 2015), in arid regions they have to prevent water evaporation from their body and simultaneously absorb, retain, and/or facilitate drinking of water (Comanns, 2018; Joel et al., 2018).

The reptilian epidermis in general consists of an inner α‐ and an outer β‐layer, mainly composed of α‐ and β‐keratins, respectively. These two layers are divided by the mesos layer (Alibardi & Maderson, 2003; Maderson et al., 1998). Because of its composition of lipids, it is responsible for the water impermeability of the lizard's integument and hence protects the lizard from desiccation. The outer β‐layer is covered by the corneous protective Oberhäutchen (Nick, 2014). For harvesting water, the lizards’ scales overlap, forming an interconnected channel network (Comanns et al., 2015; Gans et al., 1982; Sherbrooke et al., 2007). Because of capillary forces within these channels, water transportation takes place passively and sometimes even with a pre‐determined flow direction toward the mouth (Comanns et al., 2011, 2015, 2016; Yenmiş et al., 2015). In addition to this channel network, the lizards must have a hydrophilic integument. The hydrophilicity was so far linked to a honeycomb‐shaped microstructure (or microornamentation) on the Oberhäutchen, keeping a film of water after pre‐wetting (Berthé et al., 2009; Comanns et al., 2011; Hofling & Renous, 2009; Riedel et al., 2015; Sherbrooke et al., 2007; Vesely & Modry, 2002; Yenmiş et al., 2015). This microstructure, however, is also found on nonmoisture‐harvesting reptiles, such as the modest forest dragon Hypsilurus modestus (own observation) or the smooth helmeted iguana Corytophanes cristatus (Lang, 1989).

Our study focuses on the genus Phrynosoma (horned lizards), which comprises at least three moisture‐harvesting species (P. cornutum, P. modestum, and P. platyrhinos) as well as at least one nonspecialist (P. hernandesi) (Dodge, 1938; Peterson, 1998; Sherbrooke, 1990, 2002). Additionally, members are endemic to southwestern regions of North America and inhabit mainly, but not only, arid habitats (Baur & Montanucci, 1998; Bryson et al., 2012; Lara‐Resendiz et al., 2014, 2015; Newbold & MacMahon, 2014; Sherbrooke, 2002; Zamudio & Parra‐Olea, 2000). In case the microstructure does indeed entail increased wettability, we assume that Phrynosoma species inhabiting drier areas exhibit more and/or deeper honeycomb‐shaped structures on their Oberhäutchen. Additionally, we assume that closely related species would inhabit similar habitats, as their morphological features would be beneficial for colonization. Hence, in this study we analyze the linkage between microstructure, phylogeny, habitat choice as well as wettability of Phrynosoma spp.

2. MATERIAL AND METHODS

2.1. Study animals

Six captive‐bred Phrynosoma platyrhinos were kept in an arid terrarium (146 cm × 55 cm × 80 cm). A soil mixture consisting of sand and clay was used as substrate. Below the heat lamp, temperature was 45–50°C, whereas the cooler regions of the terrarium were 28°C. The lizards were fed with ants, cowpea weevils, and microcrickets. Please refer to Baur and Montanucci (1998) for further information about keeping Phrynosoma.

Additional to samples of our individuals, shed skin of captive‐bred P. asio, P. cerroense, P. coronatum, P. goodei, P. hernandesi, P. orbiculare, P. modestum, and P. taurus was kindly provided by private breeders. Please note that we were not able to match these samples to individuals within one species, and thus, there might be pseudo‐replicates included in the shed skin data.

Museum specimens of wild‐caught P. asio, P. cerroense, P. cornutum, P. hernandesi, P. orbiculare, P. platyrhinos, P. solare, P. taurus, and Moloch horridus were obtained from the collection of the Zoological Research Museum Alexander Koenig, Bonn, Germany. The used biological material is also listed in the supplement (Table S1).

2.2. Wetting experiments

We refrained from using museum specimens for wettability tests, as we observed ruptures of the Oberhäutchen in several specimens, leading to an absorption of the applied fluid by the subjacent skin layers. Hence, we chose to use only shed skin for wetting experiments. Shed skin samples exhibiting a rupture within the region of interest were discarded.

Three pieces of shed skin, ventrally and dorsally, were taken for examination. Scale structure differs between ventral and dorsal sides in Phrynosomatidae, making discrimination easy. The pieces of shed skin were placed onto a glass slide, and 2 µl of distilled water with 0.6% blue food dye (Queen Fine Foods PTY Ltd., Alderley, Australia) for coloration was applied. Spreading of the liquid was observed via a high‐speed recording microscope (250 fps, VW‐9000C; Keyence Cooperation, Osaka, Japan). The differences (%) of the area covered by the droplet (0 to 60 s) were evaluated with the help of a customized Python (3.5) script. For calculation of mean and statistics, we replaced data for perfect wetting (i.e., droplet wets complete skin within 60 s and thus a rim is unidentifiable) with the largest value we were still able to measure in our data set (raw data: Table S7).

We validated our data with the wettability of living animals (P. asio, P. modestum, P. platyrhinos, P. solare, P. taurus). For this, a droplet of tap water was applied to the dorsal side of the animal to visually check whether spreading occurs (“yes” vs. “no”). For all but P. platyrhinos, these data were provided by private breeders.

2.3. Cleaning of samples

All skin samples were contaminated to varying degrees. This was not only true for museum specimens but also for shed skin samples. Hence, the contamination is not (only) due to storage and/or age of the museum samples. Different cleaning methods were exploited to remove the contamination on the shed skin of P. platyrhinos, without any success:

We first used an ultrasonic bath with different cleaning agents (distilled water, 70% ethanol, and chloroform) for 30 s and 60 s. In a second approach, shed skin samples were incubated and swirled for 90 min in chloroform and subsequently treated for 30 s in chloroform in the ultrasonic bath. The same treatment was carried out with soapy water and the final cleaning with distilled water. Alternatively, the shed skin pieces were either fixed with double‐sided sticky tape and cleaned with a fine brush and/or compressed air of 10 bar, or a second stripe of adhesive tape was slightly pressed onto the distal side of the shed skin and then slowly pulled off. In a last trial, the shed skin was fixed upside down to a centrifugation tube, either empty or filled with distilled water. The samples were then centrifuged with 2,000 g for 2 min.

2.4. Morphological examination of microstructures

Skin samples (approx. 5 × 10 mm, ventrally and dorsally) were taken with a scalpel from preserved museum specimens of P. asio, P. cerroense, P. cornutum, P. hernandesi, P. orbiculare, P. platyrhinos, P. solare, and P. taurus. Samples were dehydrated by an ascending ethanol series. Remaining alcohol was washed out with hexamethyldisilazane and dried overnight. Afterward, one side of the sample was clean cut with a razor blade. Slices were either placed flat or with the cutting edge facing up on SEM plates. Afterward, samples were sputtered with gold and observed with a scanning electron microscope (Philips AG, Amsterdam, the Netherlands). Shed skin samples of P. asio, P. cerroense, P. coronatum, P. goodei, P. hernandesi, P. modestum, P. orbiculare, P. platyrhinos, and P. taurus were prepared as described above without the dehydration step.

Data are presented as mean ± SD, where SD is the standard deviation (raw data: Table S7, including biological material source). SEM samples were analyzed using Keyence VW‐9000 Software (version 1.4.0.0). The clean cut samples were used to measure the depth of the microstructure (with n as high as possible for each sample), whereas the flat samples were used to calculate the microstructures per mm2 (with three spots per sample).

2.5. Histology

Histological examinations were performed with skin samples of museum specimens of P. solare, P. cornutum, and M. horridus. As museum specimens, they were wild‐caught animals and not bred for several generations on a non‐natural substrate. Thus, the contamination should appropriately reflect any contamination occurring in the wild. Samples were prepared and dehydrated as described before and then cut with razor blades into slices of ca. 1 mm width. These slices were embedded in epoxy resin. Semi‐thin sections of ~0.7 µm thickness were cut with an OM U3 microtome (Reichert, Vienna, Austria). For the subsequent staining, the epoxy resin was removed as described by Mayor et al. (1961). Prepared sections of each lizard and body side were stained with either methylene blue staining, alizarin red staining, periodic acid‐Schiff staining, or gram staining (Mulisch & Welsch, 2015). Cover‐slips with sections, stained with methylene blue, alizarin red, or periodic acid‐Schiff stain, were glued to an object slide using Merckoglas. For gram‐stained sections, Canada balsam was used for final fixation. All sections were examined with a BA310 digital microscope (Motic Deutschland GmbH, Wetzlar, Germany).

2.6. Phylogenetic tree

Depending on the taxonomic concept, the genus Phrynosoma currently comprises 17–21 species (Montanucci, 2015; Uetz et al., 2020; Zamudio et al., 1997). However, by testing several species delimitation methods, Blair and Bryson (2017) found no support for the classification proposed by Montanucci (2015), who resurrected the names P. brevirostris and P. ornatissimum and used morphological information to describe two new taxa (P. bauri and P. diminutum). Therefore, we follow the taxonomy proposed by Blair and Bryson (2017) within the present study.

Phylogenetic relationships within Phrynosoma were inferred with BEAST version 1.8.3 (Drummond et al., 2012), which estimates phylogeny using Bayesian MCMC. We used previously published data (Hodges & Zamudio, 2004; Leaché & McGuire, 2006; Nieto‐Montes de Oca et al., 2014) of six nuclear loci (BDNF, EXPH5, NKTR, R35, RAG1, and SOCS5, Tables S2 and S3). Substitution models were calculated using ModelTest (Posada & Crandall, 1998) as implemented in the package phangorn for Cran R. Model parameters were estimated separately for each locus, but loci were not partitioned by codon positions in order to avoid overparameterization that impeded the MCMC mixing. The Yule speciation process was set as tree prior to using a random starting tree. Results of the BEAST analyses were summarized from four independent runs with 2 × 107 generations each, sampling every 2 × 103 trees and omitting the initial 10% as burn‐in after checking for convergence and sufficient effective sample sizes with Tracer v1.7 (Rambaut et al., 2018).

Divergence dates were estimated via a relaxed molecular clock approach with an estimated rate and uncorrelated lognormal distribution (Drummond et al., 2006). Three fossil taxa were used for calibration: Paraphrynosoma greeni (33.3 mya, stem of Phrynosoma; Holman, 1987; Smith, 2006; Wiens et al., 2013), Phrynosoma sp. (13.6 mya, oldest known fossil from the P. douglasii group; Estes & Tihen, 1964; Bryson et al., 2012), and Phrynosoma anzaense (1.8 mya, sister of P. mcallii; Norell, 1989) (Table S4). Fossils represent minimum ages of clades; thus, they were implemented as single‐sided hard bounds by using a diffuse gamma shaped prior distribution with the fossil's age as offset.

2.7. Hydrological and pedological niche assessment

With a spatial resolution of 30 arc seconds, climatic information characterizing humidity and precipitation conditions within the range of the studied Phrynosoma species was obtained from the CHELSA database representing an average between 1979 and 2013 (Karger et al., 2017). As we were predominantly interested in the hydric niche of the species, we downloaded monthly mean, minimum, and maximum temperature as well as precipitation and computed bioclimatic variables as listed in Table 1 using the ENVIREM package for R (Title & Bemmeis, 2017). These variables describe annual averages, extremes, and different aspects of the conditions the species experience within their habitats. Therefore, these parameters are likely to represent the selective landscape influencing the morphological adaptations associated with moisture harvesting. Soil data for the average conditions within a depth range of 0–5 cm and with a spatial resolution of 250 m were obtained from the SoilGrids database (https://www.isric.org/explore/soilgrids).

TABLE 1.

Definitions and abbreviations of bioclimatic variables. A: Zomer et al. (2008); B: Hargreaves et al. (1985); C: Thornthwaite (1948); D: Busby (1991) E: Willmott and Feddema (1992); J: Vörösmarty et al. (2005); K: Metzger et al. (2013); L: www.soilgrids.org vers. 2.0., average conditions at a depth range of 0–5 cm. PET = potential evapotranspiration

Abbreviation Description Units Source
annualPET Annual potential evapotranspiration: a measure of the ability of the atmosphere to remove water through evapotranspiration processes, given unlimited moisture mm/yr A, B
aridityIndexThornthwaite Thornthwaite aridity index: index of the degree of water deficit below water need – C
bio_12 Annual Precipitation mm/year D
bio_13 Precipitation of Wettest Month mm/month D
bio_14 Precipitation of Driest Month mm/month D
bio_15 Precipitation Seasonality Coefficient of variation D
bio_16 Precipitation of Wettest Quarter mm/quarter D
bio_17 Precipitation of Driest Quarter mm/quarter D
bio_18 Precipitation of Warmest Quarter mm/quarter D
bio_19 Precipitation of Coldest Quarter mm/quarter D
climaticMoistureIndex A metric of relative wetness and aridity – E, J
PETColdestQuarter Mean monthly PET of coldest quarter mm/month K
PETDriestQuarter Mean monthly PET of driest quarter mm/month K
PETseasonality Monthly variability in potential evapotranspiration mm/month K
PETWarmestQuarter Mean monthly PET of warmest quarter mm/month K
PETWettestQuarter Mean monthly PET of wettest quarter mm/month K
cfvo Volumetric fraction of coarse fragments (>2 mm) cm3/dm3 (vol‰) L
clay Proportion of clay particles (<0.002 mm) in the fine earth fraction g/kg L
sand Proportion of sand particles (>0.05 mm) in the fine earth fraction g/kg L
silt Proportion of silt particles (≥0.002 mm and ≤0.05 mm) in the fine earth fraction g/kg L
soc Soil organic carbon content in the fine earth fraction dg/kg L
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As geographic range surrogates, georeferenced records for each species were obtained from the global biodiversity information facility (www.gbif.org) and the VertNet database (www.vertnet.org), wherein the final data set comprised in total 8,844 unique records (115 of P. asio, 1,143 of P. blainvillii, 44 of P. braconnieri, 191 of P. cerroense, 2,589 of P. cornutum, 2,183 of P. coronatum, 9 of P. ditmarsi, 40 of P. douglasii, 105 of P. goodei, 699 of P. hernandesi, 314 of P. mcallii, 873 of P. modestum, 554 of P. orbiculare, 1,574 of P. platyrhinos, 6 of P. sherbrookei, 407 of P. solare, and 74 of P. taurus).

Phylogenetic signals in hydric and pedological niche dimensions and morphological traits were assessed using two approaches: Pagel's lambda (Pagel, 1999) and Blomberg´s K (Blomberg et al., 2003) using the phylosignal package for R (Keck et al., 2016).

Based on each set of records, the median position of the species in climate space was computed and median traits of all three morphological variables were tested in a phylogenetic general least‐squares (PGLS) framework in R using a Brownian motion model as phylogenetic constrain (Orme et al., 2018). We acknowledge the possibility of alpha error accumulation using false discovery rate (fdr) adjustment (p.adjust function in R). We performed a principal component analysis using 10,000 random samples throughout the study area considering those variables, where we detected a significant relationship between morphological features and environmental parameters irrespective of potential alpha errors (see results). Based on the median positions of each species in the resulting principal components, we reconstructed ancestral conditions using the “fastBM” function and trait diagrams using the “phenogram” function of the phytools package for R (Revell, 2012). These trait diagrams illustrate a projection of the phylogenetic tree in a space defined by the climatic niche and time (Evans et al., 2009). The niche breadth of each species was illustrated using density profiles (function “ggdensity,” “ggpubr,” and “ggplot2” packages for R; Wickham (2016) and Kassambra (2020)). The multidimensional niche position and volume were quantified by computing hypervolumes based on support vector machines (hypervolume package for R; Blonder, 2015; Blonder et al., 2014).

3. RESULTS

3.1. Phylogenetic tree and divergence times

Our dated phylogeny of Phrynosoma obtained from the BEAST analyses is generally well supported, with most nodes having posterior probabilities >.95 (Figure 1). The inferred relationships largely reflect the subgeneric divisions of Phrynosoma and the topology is in concordance to previously published phylogenies of the genus (Leaché & Linkem, 2015; Leaché & McGuire, 2006; Wiens et al., 2013). Estimated divergence times (Table S4) between clades or species range between 45.93 mya (95% highest posterior density intervals 33.30–64.00 mya) and 3.33 mya (0.87–6.28 mya).

FIGURE 1.

FIGURE 1

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Dated phylogeny of the genus Phrynosoma (left), traits measured (middle) as well as distribution records used in this study (right). The tree was obtained from a Bayesian relaxed‐clock analysis of six nuclear loci. The outgroup (Sceloporus bicanthalis) is not shown for clarity. Gray bars show 95% highest posterior density (HPD) of divergence times, numbers on nodes refer to Table S4, where the detailed values are given. Solid nodes have posterior probabilities >.95 and the topology presented here is identical to the fully supported phylogeny based on phylogenomic data of Leaché and Linkem (2015). Next to the phylogenetic tree are the mean values for wettability (wet) as well as microstructure number (MSn) and depth (MSd), dorsally and ventrally of each species tested (compare to Tables S5 and S6). These traits are also presented below linked to habitat and annual precipitation (bio12). The traits are placed as centroid within the convex hull of the distribution records for each species. Inset: Phrynosoma taurus

3.2. Phylogenetic signal in hydric niche dimensions

Based on phylogeny, we analyzed the dispersion of Phrynosoma across America. We indeed found strong evidence that the habitat choice of Phrynosoma is in dependence on its phylogenetic origin. There were significant phylogenetic signals analyzing hydric as well as the pedological niche dimensions (Table 2; i.e., Thornthwaite aridity index, annual mean precipitation (bio_12), minimum (bio_14) and maximum (bio_13) precipitation of the driest/wettest month, precipitation of the wettest quarter (bio_16), the climatic moisture index, and the proportion of soil organic carbon compounds (soc) and clay). As suggested by both Pagel's lambda and Blomberg's K, a Brownian motion model of evolution may explain best the relationships in hydric niche dimensions. Phylogenetic signals in pedological niche dimensions were less pronounced.

TABLE 2.

Significant phylogenetic signals in terms of Pagel's lambda and Blombergs K and K* in hydric and pedological niche dimensions (p < .05). For abbreviations, see Table 1. Appendix 1 comprises data of all analyses

Variable Phylogenetic signal Significance (p‐value)
K K* Lambda K K* Lambda
aridityIndexThornthwaite 1.16 1.15 1.05 0.02 0.02 0.05
bio_12 1.30 1.22 1.06 0.01 0.02 0.03
bio_13 1.23 1.14 1.08 0.02 0.03 0.00
bio_14 1.23 1.27 1.05 0.02 0.01 0.03
bio_16 1.23 1.14 1.08 0.01 0.02 0.00
climaticMoistureIndex 1.18 1.17 1.05 0.02 0.02 0.05
clay 0.86 0.88 0.89 0.01 0.01 0.04
soc 0.68 0.72 0.73 0.05 0.05 0.05
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3.3. Characterization of the morphological traits in correlation to phylogeny

According to the phylogenetic signal when analyzing the niche dimensions, we assumed that likewise morphological traits correlate to habitat choice, as morphological traits are likely to be similar in closely related species. We therefore tested the linkage between phylogeny and microstructure characteristics. Phrynosoma's Oberhäutchen are covered with pentagonal or hexagonal microstructures (Figure 2). The surface of the scales was not uniformly structured, though, but microstructures were pronounced in the periphery projecting into the channels between the scales. A microstructure was often missing in the middle of the scales, especially on scales of P. cornutum and on ventral scales of almost all species (to a different degree) except for P. taurus. On the scales, ~ 1,300 to ~ 2,800 structures per mm2 were counted, whereas the mean depth varied from 0 to 7.5 µm (Figure 1, Table S5). On P. asio and P. taurus, deeper microstructures were characterized (ventral 7/7.5 µm, dorsal 6 µm). Flat structures were detected on the ventral side of P. modestum (0 µm) and P. platyrhinos (0.5 µm). The most microstructures were counted on P. taurus (ventral ~2,800 mm−2), followed by P. modestum (ventral ~2,700 mm−2) and P. hernandesi (ventral and dorsal ~2,600 mm−2). Fewest structures were counted for the dorsal side of P. cornutum (~1,300 mm−2), followed by P. cerroense (ventral ~1,400 mm−2). Comparing depth as well as density of structures (ventrally and dorsally), we found no significant phylogenetic signal (Figure 1, Appendix S1). Hence, morphological traits of the Oberhäutchen are not linked to phylogeny of Phrynosoma.

FIGURE 2.

FIGURE 2

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Different manifestation of microstructures on ventral and dorsal scales of two exemplary Phrynosoma species. SEM images

3.4. Correlation of morphology and habitat

Though morphological traits are independent of phylogeny, habitat choice was linked to morphological traits additionally to being linked to phylogenetic relations. By testing if morphological features can be explained by climatic factors, the phylogenetic generalized least squares regressions suggested a significant correlation in 9 of 175 tests when treating tests separately (Table 3, Appendix S1, but see potential caveats below). Annual mean precipitation (bio_12), precipitation of the wettest month as well as quarter (bio_13, bio_16), precipitation seasonality (bio_15), potential evapotranspiration (PET) of the coldest quarter, and PET seasonality were significant predictors of ventral microstructure depth (six cases, Figure 3) and the interaction of ventral and dorsal microstructure depth (two cases). Only one pedological parameter was significantly correlated with morphology (silt ~number of dorsal microstructures).

TABLE 3.

Summary statistics of significant phylogenetic generalized least‐square regressions. P‐values were adjusted using the FDR method of p.adjust in R. Significance is marked in red. For abbreviations, see Table 1. MS: microstructure

Correlation Estimate SE t Value Pr(>|t|) R 2 Adj. R 2 F‐statistic df df p Adj. p
PETColdestQuarter ~ ventral MSs depth + dorsal MSs depth
(Intercept) 185.30 381.30 0.49 0.64 .63 .53 6.73 2 8 .019 .269
Ventral MSs depth 125.16 52.19 2.40 0.04
Dorsal MSs depth 102.34 98.92 1.03 0.33
bio_15 ~ ventral MSs depth + dorsal MSs depth
(Intercept) 35.43 19.25 1.84 0.10 .57 .46 5.27 2 8 .035 .269
Ventral MSs depth 4.88 2.65 1.84 0.10
Dorsal MSs depth 5.65 4.34 1.30 0.23
PETColdestQuarter ~ ventral MSSs depth
(Intercept) 534.78 177.53 3.01 0.01 .58 .53 12.30 1 9 .007 .147
Ventral MSs depth 154.42 44.04 3.51 0.01
PETseasonality ~ ventral MSs depth
(Intercept) 131,912.26 16,557.94 7.97 0.00 .43 .37 6.90 1 9 .028 .147
Ventral MSs depth −10788.23 4,107.52 −2.63 0.03
bio_12 ~ ventral MSs depth
(Intercept) 219.31 141.77 1.55 0.16 .37 .30 5.36 1 9 .046 .172
Ventral MSs depth 61.39 26.52 2.32 0.05
bio_13 ~ ventral MSs depth
(Intercept) 35.89 29.15 1.23 0.25 .48 .42 8.31 1 9 .018 .147
Ventral MSs depth 15.64 5.43 2.88 0.02
bio_15 ~ ventral MSs depth
(Intercept) 60.16 11.61 5.18 0.00 .37 .30 5.20 1 9 .049 .172
Ventral MSs depth 5.33 2.34 2.28 0.05
bio_16 ~ ventral MSs depth
(Intercept) 110.35 85.33 1.29 0.23 .44 .38 7.10 1 9 .026 .147
Ventral MSs depth 41.90 15.73 2.66 0.03
Silt ~ number of dorsal MSs
(Intercept) 413.52 61.73 6.70 0.00 .49 .44 8.81 1 9 .016 .336
Number of dorsal MSs −0.08 0.03 −2.97 0.02
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FIGURE 3.

FIGURE 3

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Significant correlations between hydric niche dimensions and ventral microstructure depth as revealed by pgls analyses. None of these correlations remained significant when correcting for alpha error accumulation using false discovery rates. Abbreviations: bio_12 annual mean temperature; bio_13 precipitation of the wettest month; bio_15 precipitation seasonality; bio_16 precipitation of the wettest quarter; PET potential evapotranspiration. Species are abbreviated with the first three letters of their specific epithet

As our data analyses were explorative, we need to acknowledge the potential of alpha error accumulation, and indeed, accounting for false discovery rates (fdr), none of our correlations remained significant. Testing 175 correlations at an alpha of 0.05 results in an adjusted significance level of 0.00028, which is very unlikely to be met by any correlation considering our sample size and natural variation in both morphological and ecological space. Therefore, our results need to be interpreted with caution.

3.5. Comparisons of hydric niches among taxa

A principal components (PC) analysis based on those habitat variables significantly correlated with morphological features suggested two PCs, which in total represent 84.7% of the total variation. PC1 (63.1%, eigenvalue = 3.8) is strongly negatively correlated with PET seasonality and positively correlated with annual mean precipitation (bio_12), precipitation of the wettest month (bio_13), and quarter (bio_16). PC2 (21.7%, eigenvalue = 1.3) is mainly driven by precipitation seasonality (bio_15) and PET of the coldest quarter (cf. correlation circle in Figure 4).

FIGURE 4.

FIGURE 4

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Principal components (PC) and factor loadings based on significant correlations as revealed by pgls regressions. Abbreviations: bio_12 annual mean temperature; bio_13 precipitation of the wettest month; bio_15 precipitation seasonality; bio_16 precipitation of the wettest quarter; PET potential evapotranspiration

Comparing the distribution of species in the environmental space revealed strongly varying degrees of niche position and breadth (Figure 5). The niche space as suggested by the hypervolume analyses revealed that P. orbiculare occupies the largest niche space (14.7), followed by P. cornutum (10.7), P. hernandesi (10.6), P. solare (10.1), P. modestum (6.1), P. blainvillii (6.1), P. platyrhinos (5.7), P. asio (5.2), P. taurus (2.4), P. douglasii (1.8), P. cerroense (1.7), P. coronatum (1.6), P. sherbrookei (1.3), P. braconnieri (1.2), P. ditmarsi (0.4), P. goodei (0.4), and P. mcallii (0.4). According to our niche volume analysis and ancestral character reconstruction (Figure 5), the realized niche breadth is comparatively smaller and more segregated in PC1 than in PC2.

FIGURE 5.

FIGURE 5

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(a) Two‐dimensional hypervolumes of the niches of Phrynosoma. Niche space is defined as principal components as shown in Figure 4, wherein subclades are shown separately in the same PCA space to facilitate readability. (b) Phenograms showing the median distribution of Phrynosoma taxa in hydric niche space. While the tips of the phylogenies indicate the median position of the species in PC space, the positions of the internal nodes are derived from ancestral character reconstructions using Brownian motion. Density distributions indicating niche occupancy across PC space are derived from all species records and medians are indicated as dashed horizontal lines

3.6. Wettability of Phrynosoma

Foreshadowing a link between morphology of the skin and habitat choice, we finally tested whether surface structures indeed increase wettability. We detected large differences in wettability of Phrynosoma species: Neither all species nor both body sides of one species (dorsal or ventral) were equally well wettable (Figures 1 and 6, Table S6). Only the shed skin of four of the nine tested species (P. asio, P. cerroense, P. hernandesi, and P. modestum) showed a prompt spreading of water on their skin (i.e., perfect wetting), and only for P. modestum, this was true for both body sides (Figure 6, Table S6). This pattern of wettability could be replicated in live animals (only dorsal side): P. asio, P. modestum, and P. solare (no shed skin samples available for the latter species) proved to be perfectly wettable, whereas water did not spread well on the skin of P. platyrhinos and P. taurus. The differences in wettability were neither following an obvious phylogenetic nor morphological pattern. We additionally observed that the stereotypic moisture‐harvesting behavior does not have to indicate a good wettability of the skin: Even though P. platyrhinos performed the stereotypical behavior (Figure 6a), the wettability of its skin was rather low compared to other Phrynosoma species.

FIGURE 6.

FIGURE 6

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(a) Stereotypic moisture‐harvesting posture exhibited by Phrynosoma platyrhinos in captivity. (b–d) Three different wettabilities observed on dorsal shed skin of different Phrynosoma species. Phrynosoma coronatum (b) was not wettable and the droplet did not change its shape after 60 s. Phrynosoma asio (d) was perfectly wettable and direct spreading hampered measurements of droplet size after 60 s. Phrynosoma cerroense (c) represents an intermediate wettable Phrynosoma species and the droplet spread, but was still visible as droplet after 60 s

3.7. Contamination as an influencing factor?

The “non‐predictability” of wettability by neither morphological trait nor phylogeny would stay in contrast to the described correlation between some climatic factors and morphological traits. However, applying fdr corrections advise us to interpret some of our data with caution. During SEM analysis, we encountered problems with contaminants on the scales of almost all Phrynosoma species, varying in shape and size as well as quantity even within one individual (Figures 2 and 7). None of our cleaning approaches resulted in successful removal of these contaminants. We hypothesized contamination might be a concomitant feature of the microstructure and could be the link between morphology, phylogeny, and hydric and pedological niches.

FIGURE 7.

FIGURE 7

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The skin sample of Phrynosoma solare with rod‐like and spherical dirt particles. Such particles were only found on P. solare. SEM image

For a first insight into such an interplay, we analyzed the origin of the contaminations on museum skin samples of P. cornutum, for which moisture harvesting has been described in literature, as well as P. solare, which has been observed to be perfectly wettable (tests in live animals). Additionally, we included the moisture‐harvesting lizard Moloch horridus in our study. M. horridus is often used as a comparison species for Phrynosoma, as it inhabits a similar habitat in Australia, but developed moisture‐harvesting independently of Phrynosoma (Meyers & Herrel, 2005; Pianka & Parker, 1975; Pianka & Pianka, 1970; Sherbrooke, 1990, 1993; Sherbrooke et al., 2007). All three species exhibited a high amount of contamination on their skin.

Semi‐thin sections of resin‐embedded skin of P. cornutum, P. solare, and M. horridus were stained with methylene blue. We observed the contamination to be stained more strongly than the skin and purple instead of blue (Figure 8). Alizarin red dyes inorganic particles, while, for example, skin layers stay unstained. We observed stained particles within the contamination, often measuring only a micrometer or less in diameter. To check for organic particles, we performed a gram staining and it colored both, skin and contamination. Depending on the presence of α‐ or β‐keratins, skin layers turned red (α‐layer) or purple (β‐layer). The contamination was mainly stained red. A test for collagens and cell walls of fungi via periodic acid‐Schiff staining revealed no coloration in samples of P. cornutum nor M. horridus, but rod‐shaped and spherical structures on P. solare, as also observed in SEM images (Figure 7), were heavily stained pink.

FIGURE 8.

FIGURE 8

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Histological examination of contamination. Semi‐thin sections of scales were stained with either methylene blue, alizarin red, gram staining, or periodic acid‐Schiff staining (PAS). In methylene blue staining, visible skin layers (α‐ and β‐layer) were tagged for the ventral side of Moloch horridus with the respective Greek letter for clearer depiction of used sections

4. DISCUSSION

Previous studies linked the superhydrophilic skin of moisture‐harvesting lizards to the occurrence of honeycomb‐shaped microstructures. Our results show a correlation of precipitation in the habitat with the ventral microstructure depth as well as a correlation of hydric as well as the pedological niche dimensions with phylogeny, though morphological traits and phylogeny were independent of each other. However, all other morphological traits as well as the skin's wettability itself could not predict the habitat choice of Phrynosoma species. Furthermore, applying fdr corrections to control for potential alpha errors revealed that none of these correlations remained significant. We conclude that it is unlikely that the microstructures influence the wettability, at least directly. We speculate that Phrynosoma and other moisture‐harvesting lizards could deploy the soil of their habitat to influence the skin's wettability. Future studies have to validate this hypothesis.

4.1. Evolution of environmental niches

Wiens et al. (2013) suggested that Phrynosoma originated in comparatively arid environments and mesic habitats were occupied only later. Adaptation to arid environments may therefore be the ancestral condition. According to our dated phylogeny, diversification within the genus mainly happened 15–46 Ma ago (Figure 1) and within this period, climatic conditions in Northern and Central America have been subject to numerous fluctuations and changes (Chapin, 2008). Interestingly, we found a phylogenetic signal for the choice of habitat, regarding precipitation‐related variables and two of three pedological factors. This is partly in concert with previous findings: Analyzing both temperature and precipitation‐related variables, Luxbacher and Knouft (2009) found strong phylogenetic signals only in a single climatic niche axis described by a principal component analysis (PCA) but not in morphological features. This niche axis was related to annual precipitation, precipitation of wettest month, precipitation of wettest quarter, temperature seasonality, maximum temperature of warmest month, and temperature annual range. However, the authors suggested that when accounting for phylogenetic autocorrelation, climatic niche axes were correlated with morphological features (residuals of length measurements, excluding body size) indicating morphological adaptations to environmental conditions. These findings are very similar to what we have found for the microstructures, which may have evolved after speciation as a response to habitat features (i.e., convergent evolution) rather than enabling habitat use in the first place. A comparison between P. goodei and P. cerroense illustrates this very nicely: They are distantly related and P. cerroense inhabits the Baja California Peninsula whereas P. goodei lives on the mainland in a similar habitat. This is reflected in very similar ecological niches, for example, regarding precipitation (Figure 3), but also very similar traits of microstructures (aside number of ventral structures). Interestingly enough, both species exhibit different wettability properties, with P. cerroense being well wettable and P. goodei is not.

In contrast, P. goodei and P. platyrhinos are closely related species with limited habitat overlap. In accordance with the prediction that phylogeny influences niche choice, their habitats showed, for example, similar annual precipitation (Figure 3). Nevertheless, aside from the dorsal depth of microstructures, both are morphologically distinct and equally poorly wettable. On the contrary, the next related species, P. modestum, has no habitat overlap with both and is superhydrophilic. It has equally flat ventral microstructures compared to P. platyrhinos and similar quantity of dorsal microstructures compared to P. goodei. We found correlations for both these features with hydric (ventral depth), respectively, pedological (dorsal quantity) niche dimensions.

Though we found correlations between morphological traits and niche, applying fdr corrections to control for potential alpha errors erased all correlations. Hence, our data have to be interpreted with caution and we assume it is rather unlikely that the microstructures (directly) influence wettability. Skin structures have been shown to influence tribological properties (Baum et al., 2014), which could be reflected in worn down microstructures at exposed parts of the scales in Phrynosoma.

4.2. Moisture harvesting in Phrynosoma spp

Phrynosoma is a typical exemplary genus for moisture (or rain) harvesting lizards, and for three species, the stereotypical behavior has already been described. For P. modestum, our study could confirm that moisture harvesting implies a superhydrophilic skin. However, for P. platyrhinos, we found the contrary: the stereotypical moisture‐harvesting behavior was accompanied by a badly wettable skin with only few and flat microstructures. Interestingly, P. hernandesi was formerly observed to conventionally drink when thirsty (Dodge, 1938), but we characterized their skin as superhydrophilic. Future studies hence should also focus on the important feature of the wettability of the skin when describing moisture harvesting in reptiles.

Four of the five species with the largest niche space characterization show a superhydrophilic skin (P. cornutum is described as moisture harvesting having a predominant flow direction of spreading water (Comanns et al., 2015)). Hence, this ability might enable a dispersal to new ecological niches and/or an evolutionary advantage in comparison with other Phrynosoma. For example, the habitat of the very distantly related P. asio and P. taurus largely overlaps, but the realized niche space of the superhydrophilic P. asio is larger. However, P. orbiculare occupies the largest realized niche space of all Phrynosoma and showed no special wettability characteristics. Harvesting water well is not the only selection pressure: P. cornutum, with the second largest niche space, is now listed as vulnerable (or worse) species in almost all its habitats in US states (https://explorer.natureserve.org/). The number has declined due to loss of habitat, human eradication of prey ants, invading fire ants, and collection as pet animals (Pianka & Hodges, 2021).

4.3. Origin of sample contamination

It was surprising to find an indicated link between deeper ventral microstructures and higher precipitation, as the ventral side of Phrynosoma is not exposed to rain. On the other hand, higher precipitation also leads to wetter soil, which has regular contact to the ventral integument. Analyzing the relation between Phrynosoma's morphological traits and soil parameters revealed that the occurrence of silt (particle size: ≥0.002 and ≤0.05 mm) in the habitat correlates with the number of dorsally located microstructures. Particles of the contamination on our samples were stained by alizarin red and thus contain calcium (Mulisch & Welsch, 2015). Since most Phrynosoma, and also our comparison species Moloch horridus, live in desert regions containing limestone and/or sand and sandy loams, stained particles are most likely sand dust, including silt (American Association for the Advancement of Science, 1896; Pianka, 1991; Pianka & Pianka, 1970). There was no phylogenetic signal for silt, but other soil parameters in the habitat (clay and organic particles; Table 2). Hence, we speculate a link between silt and microstructures could have developed independently.

Additionally, there was a strong signal for shed skin, especially remnants of the lower α‐layer. An accumulation of fragments of old skin seems plausible due to the lizards’ innate shedding behavior and these skin remnants would be stained by gram staining due to the amount of cystine in α‐keratin (Alibardi, 1998; Fischer, 1953). The organic contamination on the P. solare scales (both sides) also consisted of fungi, seen in the SEM as well as in our histological examinations. Fungi are found on several healthy reptiles as biofilm (Paré et al., 2003). We found fungi only on P. solare, and hence, assume this contamination was due to a captured unhealthy animal or incorrect storage of samples and has no functionality.

4.4. Influence of the honeycomb‐shaped microstructure on wettability

If the microstructure of moisture‐harvesting lizards’ scales would be the key factor for the efficient spreading of water on their skin, being clean would be essential. However, Phrynosoma were never directly observed nor described in literature to perform grooming or similar behavior. On the contrary, Phrynosoma as well as M. horridus evolved habits that increase their level of contamination: Depending on the species, behaviors like rubbing their venters on the ground, shoveling sand on their dorsal surface, or burrowing themselves in a sandy and dusty substrate were described (Comanns et al., 2016; Pianka et al., 1998; Sherbrooke, 1993; Weese, 1919). All of these can contribute to silt accumulating in the honeycomb‐shaped microstructures of the lizards’ scales. Additionally, the lizards’ skin often sheds in pieces, especially the α‐layer in direct contact with the new forming Oberhäutchen (Maderson et al., 1998). These residual skin pieces complement the contamination. Therefore, we hypothesize that the scales’ microstructure does not contribute to the lizards’ wettability directly, but can serve as container for contamination. Smaller particles, like shed skin and especially silt, would influence the wettability positively due to (a) smaller capillaries forming between the grains and particles and (b) in case of silt: reduced contact angle compared to the skin's keratin due to different material chemistry. Further investigations should evaluate this by, for example, comparing the wettability of freshly shed animals (no silt accumulation) to animals exposed to silt in a controlled manner.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

AUTHOR CONTRIBUTION

Anna‐Christin Joel: Conceptualization (lead); Data curation (equal); Investigation (equal); Supervision (equal); Visualization (equal); Writing‐original draft (lead). Jenice R. N. Linde: Data curation (equal); Investigation (equal); Writing‐original draft (supporting). Philipp Comanns: Conceptualization (equal); Funding acquisition (lead); Project administration (equal); Supervision (equal); Writing‐review & editing (supporting). Caroline Emonts: Data curation (equal); Investigation (equal); Writing‐review & editing (supporting). Margret Weissbach: Data curation (equal); Investigation (equal); Writing‐review & editing (supporting). Morris Flecks: Data curation (equal); Formal analysis (equal); Visualization (equal); Writing‐review & editing (equal). Dennis Rödder: Conceptualization (equal); Data curation (equal); Formal analysis (equal); Investigation (equal); Validation (equal); Visualization (equal); Writing‐original draft (equal).

Supporting information

Table S1‐S7

Click here for additional data file. (121.3KB, pdf)

Supplementary Material

Click here for additional data file. (80.2KB, xlsx)

Supplementary Material

Click here for additional data file. (50.6KB, nex)

Supplementary Material

Click here for additional data file. (824B, nwk)

ACKNOWLEDGMENTS

We want to thank private breeders for the provision of the shed skin and wettability data of their live animals. Martin Singheiser provided valuable and helpful information about breeding and husbandry of P. platyrhinos. Many thanks to the veterinary office, LANUV, as well as to Kira Scherer and the team of the Institut für Versuchstierkunde from UKA for enabling us to keep and study P. platyrhinos (permission of animal keeping and handling: 39.3‐60.06.04‐mü‐an/bra and 84‐02.01.04.2015). Thanks to Nadine Böttcher and Caroline C. F. Grannemann for assistance in the morphological examination. This work was supported by the European Commission within the project “LiNaBioFluid” [665337]. Open access funding enabled and organized by Projekt DEAL.

Joel, A.‐C. , Linde, J. R. N. , Comanns, P. , Emonts, C. , Weissbach, M. , Flecks, M. , & Rödder, D. (2021). Phylogenetic and morphological influence on habitat choice in moisture‐harvesting horned lizards (Phrynosoma spp.). Ecology and Evolution, 11, 14146–14161. 10.1002/ece3.8132

Anna‐Christin Joel and Jenice R. N. Linde are contributed equally.

Contributor Information

Anna‐Christin Joel, Email: joel@bio2.rwth-aachen.de.

Dennis Rödder, Email: d.roedder@leibniz-zfmk.de.

DATA AVAILABILITY STATEMENT

The supplement includes the following tables: S1 Samples used for investigation. S2 Taxon sampling and GenBank accession numbers. S3 Used loci and dataset properties. S4 Estimated divergence times. S5 Mean morphological traits. S6 Mean wettability of shed skin of Phrynosoma. S7 Raw data. Additionally, Appendix S1 includes the detailed statistical tables. Our phylogenetic data are also provided as nexus and newick file.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1‐S7

Click here for additional data file. (121.3KB, pdf)

Supplementary Material

Click here for additional data file. (80.2KB, xlsx)

Supplementary Material

Click here for additional data file. (50.6KB, nex)

Supplementary Material

Click here for additional data file. (824B, nwk)

Data Availability Statement

The supplement includes the following tables: S1 Samples used for investigation. S2 Taxon sampling and GenBank accession numbers. S3 Used loci and dataset properties. S4 Estimated divergence times. S5 Mean morphological traits. S6 Mean wettability of shed skin of Phrynosoma. S7 Raw data. Additionally, Appendix S1 includes the detailed statistical tables. Our phylogenetic data are also provided as nexus and newick file.

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