Ecological drivers of ultraviolet colour evolution in snakes

Domain: earth_science
Published: 2024-06-18
Editorial outcome: accept

Abstract
Ultraviolet (UV) colour patterns invisible to humans are widespread in nature. However, research bias favouring species with conspicuous colours under sexual selection can limit our assessment of other ecological drivers of UV colour, like interactions between predators and prey. Here we demonstrate widespread UV colouration across Western Hemisphere snakes and find stronger support for a predator defence function than for reproduction. We find that UV colouration has evolved repeatedly in species with ecologies most sensitive to bird predation, with no sexual dichromatism at any life stage. By modelling visual systems of potential predators, we find that snake conspicuousness correlates with UV colouration and predator cone number, providing a plausible mechanism for selection. Our results suggest that UV reflectance should not be assumed absent in “cryptically coloured” animals, as signalling beyond human visual capacities may be a key outcome of species interactions in many taxa for which UV colour is likely underreported.

Introduction
Humans are a poor proxy for the visual capabilities of animals across the tree of life1. Colouration and its perception are major factors influencing an organism’s survival and reproductive success, yet the limitations of human vision have largely restricted the study to species that are brightly coloured in “visible” wavelengths of light (400–700 nm2,3). However, the ability to perceive ultraviolet (UV) wavelengths (300–400 nm) is found in many other animals, and UV colour is used frequently in visual communication within and across species3,4. This mismatch between human and animal visual systems can result in cryptic diversity in colouration and create a profound barrier to understanding the ecology of many species5.

For most systems in which UV colouration is well understood, its primary reported function is reproduction rather than survival benefits. From the role of nectar guides in increasing flower pollination6 to ultraviolet facial markings for social signalling in fish7 and birds8, UV colouration provides iconic examples of how reproduction shapes receiver-dependent signal evolution across taxa9. However, any bias toward studies on reproduction-related mechanisms might not accurately reflect the true distribution of function in nature. Instead, a bias could arise because colour patterns used primarily for crypsis or concealment have been understudied for UV colouration. In theory, multiple types of selection can affect colour evolution, and these processes are hypothesised to produce different signatures on the standing variation of UV colouration within and among species10.

Here we use a broad-scale survey of snake colouration and visual receiver modelling to test the relative roles of survival and reproduction in UV colour evolution across Western Hemisphere snakes (N=110 species). Snakes have been previously studied for human-visible colour variation in both crypsis and mimicry11,12, and they are known to have the visual capacity to perceive UV wavelengths13. Even though snakes are nested within the larger “lizard” clade that is known to use UV colouration widely for sexual signalling14,15, the function and prevalence of UV reflectance remain unreported across snakes. If UV colouration is also under strong sexual selection in snakes, differences should be greatest within species between males and females and most pronounced in reproductive (adult) life stages. Alternatively, natural selection from UV-sighted predators should instead produce differences in UV reflectance among species, predictable by habitat specialisation and activity patterns. Predator-driven evolution could also produce differences between adults and juveniles, but in the opposite direction than predicted by sexual selection, as protective colouration often confers a benefit at vulnerable early life stages (as seen in juvenile lizards16). Lastly, if UV colouration is selectively neutral, we would expect a strong phylogenetic signal across taxa and no independent influence of sex, life stage, activity pattern, or habitat. Repeated convergent evolution of UV colouration in response to independent transitions to the same habitat would strongly reject a neutral mechanism.

Results
Previous research on UV colouration is skewed towards reproduction
UV coloration has been studied over many years, but this research attention may not be uniformly distributed across functional contexts and clades. To quantify the potential presence and magnitude of bias in reports of UV colour, we systematically reviewed the published literature (N=2401 identified studies; Supplementary Fig. 1, Supplementary Data 1) for function and perception of UV colour. We found that when the function was directly tested or inferred (N=281 studies), reproductive functions like mate choice and pollination were indeed reported much more frequently than survival benefits (Fig. 1a, b, red vs. grey wedges). Across studies of all taxa (Fig. 1a), we found that flowering plants, butterflies, and vertebrates were the primary targets of research to the exclusion of most organismal diversity. Within vertebrates (Fig. 1b), the majority of studies were conducted on birds, with nearly 1/3 of those on only three species from just two families (Great Tits, Parus major; Eurasian Blue Tits, Cyanistes caeruleus; and King Penguins, Aptenodytes patagonicus). We found an additional 230 studies that did not test function but which overwhelmingly (97%) report the widespread ability to perceive UV colour in species across many clades (Supplementary Data 1). Together, these results suggest there is indeed high potential for overlooked UV colouration that would directly affect our understanding of both its function and evolution across systems.

UV colouration is widespread across snake species
By conducting broad surveys of snake colouration in natural populations using cameras specifically designed to capture both human-visible and UV reflectance under natural lighting, we found that UV colouration is unexpectedly prevalent across snakes (Fig. 2; Supplementary Data 2). Although there was substantial variation in the intensity and physical location of UV reflectance across species (Fig. 2a, Supplementary Figs. 2–4), the overwhelming majority (90%) of species reflected UV wavelengths on some part of their bodies, especially the ventral surface and in the colour white (Fig. 2b; Supplementary Fig. 4). UV reflectance on both dorsal and ventral surfaces showed little phylogenetic signal, even when accounting for phylogenetic uncertainty (all Pagel’s lambda < 0.2 and all p > 0.1, and thus not significantly different from zero). We also found that UV reflectance on one body surface did not reliably predict reflectance on the other surface (all R2=0–0.11). Dorsal UV reflectance was both lower overall and more concentrated into patches along the body than ventral reflectance, especially on heads and chins (χ2 = 40.206; p < 0.001). Additionally, both the spectrometer and photographic analyses suggest that human-visible and UV elements are decoupled, as the presence of UV reflectance could not be reliably predicted from a snake’s visible colouration alone (Figs. 2c and 3a; Supplementary Figs. 2–4; see Supplementary Note 1 for discussion of scale properties).

Sex does not predict UV colouration, but age class does
To test for age and sex differences in UV reflectance, we analysed a subset of 101 species for which we had robust within-clade sampling (N=410 individuals). Many species showed significant intraspecific variation in UV reflectance, including between individuals that looked similar in the human-visible spectrum (Fig. 3a, discrete UV polymorphism in Amazonian tree boas, Corallus hortulanus). Using mixed-effects models controlling for clade as a random effect, we found no differences in overall, dorsal, or ventral UV reflectance between males and females (all F < 0.05; p > 0.8; Supplementary Fig. 5). However, we found highly significant differences between age classes, such that juvenile snakes had higher reflectance than adults in all comparisons (all F > 10.77; p < 0.002; Fig. 3b, c, Supplementary Fig. S6). Together, these findings suggest that sexual selection is unlikely to explain the evolution of UV colouration in snakes, in contrast to many other reptiles14,15 and other vertebrates (Fig. 1b).

Habitat ecology predicts UV colour evolution across species
Given that exposure to predators varies depending on the habitat a prey species uses and its relative risk when asleep or awake17, we also tested whether primary habitat type and diel activity patterns were significant predictors of UV reflectance (Supplementary Data 3). Using phylogenetic generalised linear models, we found that habitat is a significant predictor of dorsal UV reflectiveness (t=1.75; p=0.035), with arboreal snakes having significantly higher UV reflectance relative to snakes from all other habitat types (Fig. 3c; Supplementary Fig. 7). Nocturnal snakes also had significantly higher UV reflectance than diurnal snakes (t=2.05; p=0.046), and these differences were more extreme for dorsal colour alone (Supplementary Fig. 7). This repeated evolutionary convergence across the same habitat specialisations is inconsistent with a conclusion that neutral processes are driving the evolution of UV reflectance across these snake species, suggesting instead that UV colour is under natural selection.

Snake conspicuousness to other species depends on UV colouration and chromacy
The three main classes of predators on snakes are birds, mammals, and other snakes17, which all vary in their ability to perceive different wavelengths, including UV18,19 (Fig. 4a). We tested the impact of UV reflectance on the conspicuousness of snakes to six different vertebrate receivers as modelled by their measured visual sensitivities to colour20,21. We found that snake colour conspicuousness varies greatly among these receivers, with human perceptions of mean dorsal colour contrast (ΔS) being more similar to the dichromatic visual system of other mammals, like dogs, than to the UV-sensitive birds, lizards, and snakes (Fig. 4b; human mean represented by dashed line). By a considerable margin, birds were the receivers for which conspicuousness was the highest. These results are clear even for dorsal surfaces (Fig. 4b), which are maximally visible to predators but which also show reduced UV reflectivity relative to venters (Fig. 3b). Remarkably, up to 30% of the differences in snake conspicuousness among receivers could be explained by the snake’s dorsal UV reflectance alone, even though these receivers differ in many aspects of their colour sensitivity (Fig. 4c, d; Supplementary Figs. 8, 9). To test whether the higher colour contrast for UV-sensitive visual systems was only the result of bird visual systems’ higher chromacy, we fit a multiple regression model predicting colour contrast as a function of chromacy (2, 3, or 4 cones) and UV sensitivity (λmax for the shortest peak sensitivity of any cone). Both UV sensitivity and chromacy were significant predictors of colour contrast (overall model: F(3,1634) = 409.1, p < 0.001), indicating that the importance of UV reflectance in our results is not solely a consequence of our choice of visual systems. While the relationship between ΔS and conspicuousness may not be strictly linear22, our overall results suggest that predation—especially by birds—is a plausible mechanism for the evolution and maintenance of widespread UV coloration in snakes.

Methods
Literature review
To assess trends and biases in the UV literature, we used the Scopus online citation database (accessed 2 November 2023) to identify studies that tested the function of UV colouration across the tree of life (Supplementary Fig. 1). To sample the literature inclusively, we searched within article title, abstract, and keywords using the following set of terms, Boolean operators, and wildcards: ultraviolet OR uv OR “nectar guide” AND (reflect* OR absorb* OR colour* OR colour* OR pattern* OR signal*) AND (“natural selection” OR “sexual selection” OR adapt*). We then restricted this search to only include articles and reviews in the subject areas of (1) biochemistry, genetics, and molecular biology, (2) agricultural and biological sciences, and (3) environmental science. The resulting database included 2401 published manuscripts requiring additional filtering for relevance before scoring for tests of UV function. First, we reviewed titles to remove any articles that were not relevant to UV reflection in an ecological context, such as papers that used UV light in laboratory methodologies, UV radiation in the context of atmospheric science, and human medical treatment (N=1516 removed). We then reviewed the abstract and keywords of each remaining paper to identify the study organisms and the specific biological mechanism for which UV reflection was discussed, with “mechanism” referring to the presence of UV colour on the study organism or the ability to perceive UV wavelengths. If the specific function of UV colour could not be determined from the abstract, we then reviewed the full text of the article. In 362 cases, this additional review of the abstract and text found that the paper was not relevant to UV colouration in an ecological context and thus noted as “NA” for mechanism.

We then classified scored mechanisms within categories of “survival” (N=38), “reproduction” (N=224), “both” (N=20), “unknown” (N=40, generally reporting only the existence of UV colour), or “other” (N=201), with the last category overwhelmingly pertaining to UV perception (97%). Papers grouped into the “survival” category included mechanisms such as camouflage, warning or startle colouration, assistance with prey acquisition, and protection from UV radiation via reflectance. Papers assigned to the “reproduction” category included intraspecific signalling, sexual selection, and pollination. Most tests of intraspecific communication focused on signals relevant to reproduction (mate choice, honesty of signals, access to breeding sites, etc.) and did not explicitly test for dual functions related to survival, but we scored some of these studies as “both” if survival was directly addressed. Papers focused on perception or visual tuning were placed into the “other” category because they did not discuss a specific function of UV reflectance. Papers that discussed only UV fluorescence or absorption (rather than reflection) were scored as “NA” for mechanism, as neither of these phenomena represents true UV reflective colouration. Three authors (HLC, JDC, and ADR) contributed to the first pass on these scores, and then one author (ADR) performed quality control and standardisation to ensure uniformity among scorers, with disagreements discussed until consensus. After all filtering and scoring steps, 523 articles that tested for the function or perception of UV colouration were included in our assessment of relevant previous research (511 of which mapped to taxonomic categories in Fig. 1; see Supplementary Fig. 1 and Supplementary Data 1).

Field collection
We captured 438 snakes from field expeditions to Peru (2016–2018), Nicaragua (2018), Belize (2019), and the United States (Texas, Colorado; 2021). We collected snakes through a combination of opportunistic foot surveys, drift-fence lines with pitfall and funnel traps, and driving surveys44. All field methods were approved by Institutional Animal Care and Use Committees (the University of Michigan #PRO00006234 and #PRO00008306, Dickinson College #895) and respective governmental authorities (Peru: Servicio Nacional Forestaly de Fauna Silvestre 029-2016-SERFOR-DGGSPFFS, 405-2016-SERFOR-DGGSPFFS, 116-2017-SERFOR-DGGSPFFS; Nicaragua: Ministerio del Ambiente y los Recursos Naturales DGB-IC-058-2017, DGPNB-IC-019-2018, DGPNB- IC-020-2018, DGPNB-IC-002-2019; Belize: Forest Department of the Ministry of Agriculture, Fisheries, Forestry, the Environment and Sustainable Development FD/WL/1/19(10); Texas Parks and Wildlife, #SPR-1020-175; Colorado Department of Natural Resources, #1950298916). Although we captured and released several live specimens, the majority were vouchered for natural history museums, with specimen numbers and collections of deposition given in Supplementary Data 1.

Photography
To quantify reflectance at both visible and UV wavelengths, we used a Nikon D7000 DSLR camera (Nikon Inc., Melville, NY, USA) with full-spectrum conversion (LifePixel; Mukilteo, USA) and equipped with a Coastal Optics UV–VIS–IR 60mm F/4 macro lens (Jenoptik Optical Systems, Jupiter, FL, USA). We photographed the dorsal and ventral surfaces of each specimen with both a Baader (Mammendorf, Germany) UV/IR cut filter and a UV-Pass filter in a standardised setting at each field site. We adjusted F-stops, shutter speeds, and ISO to local field conditions. We illuminated each specimen using both ordinary incandescent and UVB light bulbs (Reptizoo; Miami, USA) with standardised angles, placement, and diffusion to minimise specular reflectance, or using natural ambient light when electrical power was unavailable in remote locations (~10% of our data). We photographed specimens against a blue, black, or white matte background (Hengming; Guangzhou, China) with a 40% grey reflectance standard (Labsphere; North Sutton, USA) to standardise photos across variation lighting conditions and a 50mm scale bar. We performed spectrometry measurements on a subset of snakes from a series of patches representing each unique colour on a given snake (Supplementary Fig. 2) using an Ocean Insight Flame Miniature Spectrometer (Model: FLAME-S-UV-VIS ES) with a PX-2 Pulsed Xenon Light Source and QR400-7-SR Light Source cable (Ocean Insight; Orlando, USA) calibrated using a Labsphere 99% white reflectance standard (Labsphere; USA).

Ecological characterisation
We used primary literature to characterise habitat and diel activity patterns for snakes. We assigned species as arboreal following Harrington et al.45, fossorial following Cyriac and Kodandaramaiah46, or aquatic following Murphy47, and remaining species as terrestrial with quality control via our field surveys above. We assigned diel activity states as diurnal or nocturnal via Harrington et al.45 and field guides (Supplementary Data 3). Eight species were not assigned a primary diel activity pattern due to a lack of available information. We assigned sex using a combination of probes and observations of everted hemipenes in males or by palpating developing offspring in females. We determined snake age classes (juvenile, adult) by ranking measured snout-vent lengths (SVL) within species to calculate sex-specific size at maturity thresholds for each species or from published literature48.

Manual scoring of UV reflectance from photographs
We quantified UV reflectance for each snake by comparing UV-pass photos using two independent observers (HLC & JDC). First, we scored the dorsal side of each snake for the presence or absence of UV reflectance by comparing pixels on the snake’s body to the 40% reflectance standard because pixels without reflectance looked uniformly dark in comparison (e.g., Fig. 2a, Supplementary Fig. 2), and then we qualitatively estimated the overall proportion of the body with this reflectance (coverage). Because most photographs were illuminated in the same way, we could identify small patches of specular reflectance (mirror-like reflection of light from a shiny scale surface) by their high brightness and repeatable location on the parts of the body in a direct angle toward the light sources (e.g., Supplementary Fig. 1, 6), and we treated those patches as having “no scoreable data”. We then recorded the location of the remaining UV reflectance as being on either the head, body, tail or any combination of the three. The corresponding colour in the visible colour range was determined by comparing the UV-pass photo to the visible colour photo. We also qualitatively scored the brightness of the UV-reflective colour as being either less, more or of similar brightness to the 40% colour standard. We then repeated these steps for the ventral surface of each animal.

After both scorers had completed the above process, we identified and resolved the few discordances about UV presence or absence via discussion or by an independent third author (ADR). Then, scores were combined into a snake’s UV reflectance index by first averaging scores across the two observers, and then multiplying the mean brightness score by the mean proportion of the body with UV reflectance (coverage). We performed these calculations separately for dorsal and ventral surface indices and summed them for an overall reflectance index per snake, and all three of these indices were retained for downstream statistical analysis.

Quantitative colour pattern analysis and receiver cone catch models
To generate multispectral images (Supplementary Fig. 10), we combined pairs of visible and UV camera RAW images (Nikon NEF files) for the subset of images with the best photographic quality to minimise analytical error. We then normalised across images using the 40% Spectralon reflectance standard included in each photo to create a 5-channel (R, G, B, uvB, and uvR) multispectral image. We excluded background pixels using the corresponding binary mask produced by Batch-Mask49 and set the scale in ImageJ50 from a 50mm scale bar included in each image. UV reflectance was calculated as the sum of uvR and uvB channels across each snake. We note that there was no straightforward way to exclude specular reflectance from quantitative analysis of multispectral images, so much of it was interpreted as UV reflectance in this analysis (see Supplementary Note 1 and Supplementary Fig. 6 for detailed comparison of the manual vs. ImageJ metrics, which were largely congruent). For patch measurements (Fig. 2c), we took the mean of three independent measurements for each channel for each colour on individuals using the polygon and measure tools in ImageJ. To process images for receiver analyses, we used the micaToolbox ImageJ plugin and quantitative colour pattern analysis (QCPA) pipeline20,51 to produce cone-catch images and run edge intensity analyses. We generated cone-catch models for our camera using the chart-based procedure in micaToolbox with a photographed set of UV-reflective pastels arranged in a grid and measured their precise spectral reflectance curves using a Flame-S-XR1 spectrometer from Ocean Insight. We sourced receptor sensitivities from those available in micaToolbox20 (blue tit [i.e., UVS bird], peafowl [VS bird], human, gecko [lizard], and dog) and from the literature (snake21). Of these, the UVS bird, lizard, and snake have cones with peaks in the UV range (372 and 362 nm), while the dog and peafowl have short-wavelength sensitive cones with peak sensitivities above the UV (430 and 433 nm, respectively) with declining (but non-zero) sensitivity in the UV range. We classified these visual systems as UV-weak in Fig. 4 to distinguish them from the ultraviolet-sensitive (UVS) blue tit, gecko, and snake visual systems, but our visual modelling approach accounts for this non-zero UV sensitivity. All receptor sensitivities (λmax) are given in Supplementary Table 1. In cases where Weber fractions were not known (gecko and snake), we tested multiple values based on the range of Weber fractions of other visual systems in our dataset and in the literature (e.g., all Weber fractions equal, SWS > LWS). We found that changes in Weber fraction did not qualitatively affect our results (data not shown), so here we report values using Weber fractions of 0.05 for all channels for both gecko and snake.

We then converted the multispectral images to cone-catch images and ran each through the QCPA framework. Briefly, this involved (1) masking out the image background using a region-of-interest (ROI) generated by Batch-Mask49; (2) Gaussian acuity correction for a viewing distance of one meter; (3) receptor noise-limited (RNL) filtering and clustering to group colours which would not be distinguishable by that viewer at that distance; and (4) local edge intensity analysis (LEIA) and calculation of other metrics of visual contrast (see Supplementary Fig. 10 and van den Berg et al.51 for details). To directly assess the perceived chromatic contrast of entire snake colour patterns, we used the mean chromatic colour distance (ΔS, the Euclidean distance between points in receiver colour space) as calculated by the LEIA analysis on the RNL-clustered image. Chromatic ΔS summarises the degree of colour contrast as a distance metric between two patches (e.g., ΔS between two pixels of the same colour will be 0) rather than directly comparing average chromaticity, and mean chromatic ΔS (ΔS) represents an average of these values across the whole organism. For example, the blue, red, and yellow plumage of a scarlet macaw would have a higher chromatic ΔS than a uniformly green bird, even if they might have the same average chromaticity. As the goal of this analysis was to compare snake appearances across viewers with differing receptor sensitivities, we kept as many values as possible constant between QCPA runs for different cone-catch models and used framework defaults where appropriate (e.g., viewing distance of one meter, see Supplementary Note 2 and Supplementary Table 1 for all modelling parameters). For cone-catch models that did not include a luminance channel for edge intensity analysis (dog, human, and snake), we created one using the ‘Create luminance channel’ function by averaging together photoreceptor channels following the literature (Supplementary Table 1).

Statistical and phylogenetic analysis
To account for phylogenetic uncertainty, we performed all species-level analyses across two different time-calibrated phylogenies with the best coverage across snake species in our dataset52,53. We pruned each tree to include only species with molecular data that were also present in our dataset, using intrageneric tip substitution to place congeners where possible (yielding a total of 104 species for analyses with one tree52 and 95 species for the second tree53 that had reduced sampling of non-colubrids). To test the effect of ecology (habitat) and diel activity on UV reflectance while controlling for phylogenetic non-independence, we ran phylogenetic linear models54 and phylogenetic ANOVAs (in ‘phytools’55) on both manually-scored and computer-scored metrics. We note that the computer-scored metric required the highest quality photos in RAW format, in which the visible and UV photos of the specimen could be perfectly aligned, which was not always possible (e.g., if the specimen was moved slightly in between photos). Usable image pairs represent a subset of ~30% of all snakes measured and a concomitant reduction in statistical power (N=65 species). For intraspecific analyses, we used a series of mixed-effect models to test if sex or age predicts UV reflectance while controlling for clade as a random effect. To avoid singularity issues with our models, we used a reduced dataset containing the four clades for which we had enough samples across all age and sex classes (Colubrinae, Dipsadinae, Elapidae, and Viperidae; N=410 individuals). We ran each analysis as linear and multiple regression models to account for distribution non-normality, but all models yielded broadly congruent results. To calculated degrees of freedom and P-values, we used the “Satterthwaite approximation” implemented in the ‘lmerTest’ package56. To assess interactions between body regions (e.g., dorsal and ventral, heads vs. bodies), we used Chi square analyses for both individual data and species means. To test the relative effects of UV sensitivity and chromacy, we fit a multiple regression model predicting mean colour contrast as a function of a number of cones and UV sensitivity (λmax; see also Supplementary Table 1). We implemented all analyses in R 4.2.1 and assessed significance at p=0.05 with two-tailed tests.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study investigates the presence of UV coloration in 110 snake species using ultraviolet photography and spectrophotometry, and assesses potential drivers (predation, sexual selection) for the evolution of UV signalling in these taxa. In the field of visual ecology, it is certainly interesting to know which species reflect UV colouration. This has been documented in multiple other species, including insects, birds and fish. However, it is challenging to provide convincing evidence that selective pressures act on UV coloration without more detailed visual modelling, understanding how these visual signals are displayed against background habitats, and ideally behavioural evidence of how potential signal receivers responding to UV signals. UV reflectance can also be a by-product of the physical properties of pigments or structural colours. While the number of species sampled is impressive, the broad conclusions that the authors make from the title, ‘Predators drive the evolution of ultraviolet colouration in snakes’ and conclusory sentences, ‘Our results show that predator-driven evolution of UV reflectance across snakes not only exists, but also provides a plausible process by which such patterns are maintained over evolutionary time) are not supported by the data.\nMajor points\nSpectral sensitivity curves and visual modelling: More information needs to be provided on the spectral sensitivity curves shown in Figure 3a, as there are some issues that may impact the visual modelling. It states that curves were from micaToolbox (bluetit [i.e., diurnal bird], human, and dog) and from the literature (owl43 and snake44).’ However, two species: Nocturnal bird vision and Dog vision state they are UV-, but clearly show the sensitivity curves extending into the UV. Filtering properties of corneas and lenses (e.g. filtering wavelength below 400nm) and oil droplets in burds may be altering the spectral sensitivity curves and need to be considered, otherwise the results from the modelling may be inaccurate. These details should be specified in the methods section and spectral sensitivity curves should be adjusted to show this.\nChromacy: Also, the choice of taxa viewing the snake’s colour patterns also need careful consideration as you have a combination of UV+ and UV- sensitive species but also di-, tri- and tetra-chromatic visual systems. Contrast measures are generally going to be higher for those with higher levels of chromacy.\nNocturnal vision: The result stating that, ‘Nocturnal snakes also had significantly higher UV reflectance than diurnal snakes (t = 2.05; P = 0.046)’ does not support the hypothesis that predators are driving the amounts of UV reflectance in colour patterns. In nocturnal environments, most of the UV light from ambient conditions has disappeared. Also, in dim light conditions vertebrates switch over from cone-based vision to rod-based vision, which is not UV sensitive.\nVentral vs dorsal: If UV-contrast was driven by predators, then why is UV colouration also displayed at higher levels on ventral surfaces, as predators are unlikely to view the ventral surface during the predation sequence, ‘Dorsal UV reflectance was both lower overall and more concentrated into patches along the body than ventral reflectance (χ2 = 40.206; P < 0.001).’\nMinor issues\nL154-155: ‘One fundamental insight from this work is that none of this UV reflectance is predictable from the snake’s visible colour pattern alone.’ I do not think that most in the field of visual ecology would hypothesis that UV reflectance could be predicted by visible reflectance, so I find this a strange conclusion from the study. Colours are often described by whether they contain a UV component or they don't, for example: blue versus UV-blue, but there has never been any predictions that I have seen that states that by understanding the reflectance in the visible you would be able to know anything about the amount or presence of UV reflectance of the same colour patch.\nThe authors state L89 that ‘This repeated, non-random evolutionary convergence across habitat specialisations strongly supports the conclusion that predators play a critical role in the evolution of UV reflectance across snake species’; however, the study does not investigate the visual characteristics of the background the snakes are viewed against, so it is hard to make inferences from this.\nL251: ‘Create luminance channel function by averaging together the long- and medium wavelength-sensitive channels, which is the standard in visual ecology’. This needs a citation and it depends on the taxa. For example, fish are thought to process luminance using their double cones, but also use double cones for processing chromatic information. Whereas birds have single cones for colour vision but are thought to only process luminance information through double cones. So is a little more complicated than stated.\nL254: there are multiple ways of measuring contrast, so this needs to be explained in more detail here, rather than rely on referencing the QCPA paper or the supplementary information. This doesn’t tell you how these measures are calculated, which is important for the results. For example, in Figure 2, it needs to be made clear what the units refer to.", "reviewer_2": "Dear Authors,\nI have very much enjoyed reviewing one of the first papers to study UV colouration in a broad sample of non-avian, non-lepidopteran species. The authors conclude that UV reflectance in some species of snake has an antipredator function. To do so, the paper tests expected relationships between colour form, sex, age, activity time and habitat in order to infer function. This is a useful and valid approach. Results show that UV reflectance is associated with being a juvenile, arboreality and nocturnality, but not with sex, interpreted as consistent with an antipredator function as opposed to a sexual function of being a neutral trait. As with almost all comparative evidence, this evidence is correlational, but that is the way it is – I commend the general approach taken, the quantity and quality of underlying data, as well as many aspects of the methodology and reporting.\nFor me, one of the most remarkable findings was that UV reflectance was associated with all visible colours (Fig 3) but imperfectly so (i.e. some reds were UV reflective while others weren’t). This gives some confidence that UV reflectance is not just a side-effect of selection on non-UV colour. However, this remains my greatest concern for the interpretation that UV colour may have evolved under selection in snakes for an antipredator function, and that this may sometimes be independent of visible colouration. The large majority of white colours are classified as UV reflective and it could be that the chromophores involved in producing white colour are also involved in the production of other colours, for example to make them brighter. It is hard to tell without statistical analysis, but this appears to be suggested by Fig 1C – while UV reflectance does not seem to be correlated with any of the visible colours except white, within a colour category, visible and UV reflectance appear correlated (it would be good to present these analyses). If this is so, it could be that the UV reflectance is a consequence of selection on visible colour. I think discussion of colour production in snakes generally, and specifically of key study species (for example of Dipsas and Micrurus pictured in Fig 1.) could give more confidence here. What chromophores are responsible for white colour? Do these also contribute to colour in the examples of other UV reflective visible colours?\nMy second query, which may affect the conclusions drawn, is how UV reflectance relates to structural wear to the epidermis and moulting. We know these are issues affecting UV reflectance in birds (e.g. doi.org/10.1111/j.1095-8312.2002.tb02085.x). The epidermis of juveniles (and arboreal/nocturnal?) snakes could wear faster and/or moult more frequently, and this could contribute to results. Fig. 2a seems to suggest that individuals can vary in their overall UV reflectance (i.e. intra-individual UV reflectance of different colour patches is correlated – another analysis worth doing), which would be consistent with this idea. Additional measurement of individuals at different stages in the moult cycle would be very instructive and give ore confidence in conclusions in my view.\nMy final substantial concern, which is mentioned in SI Fig 6 but I think needs to be brought to the main methods, is how gloss was considered and handled in analyses. This is related to the previous point – as well as species differences in gloss, glossiness also varies with moult and condition. Glossiness is interesting in that it is a component of the stimulus that a viewer will see looking at the snake, with recent work showing gloss can have antipredator and sexual functions, but it is different to other aspects of colouration in that it will vary with the relative positions of the illuminate and viewer, skin condition, and lighting directionality. As glossiness depends on dermal microstructure it could also plausibly be involved in locomotion, hydrophobicity etc. Clearly some of the UV reflectance in images is due to specular reflections – it sounds like these were avoided in measurement? What is the reasoning for this? Unfortunately I was unable to access the original image files to get a feel for how glossiness varies within and between species in your sample.\nSmaller points:\nL31-32 “essential for their communication” – ambiguous – rephrase.\nL39 There are other functions of colouration – for example anti-parasite colouration, colour used to lure or flush food, colour used for social signalling. Some of these functions make the same prediction as the anti-predator and sexual hypotheses. Could unique predictions for these functions be tested? If not I think this issue needs to be acknowledged.\nL64 What does P>0.1 mean here? “all Pagel’s lambda < 0.2; P > 0.1)” -> “all Pagel’s lambda < 0.2 and P(≠0) > 0.1)”?\nL130 Most natural surfaces (leaves, soil, rocks, bark, water) have low UV reflectivity, at least in the wavelengths most UV sensitive animals are sensitive to. Exceptions include surfaces like snow, light sand, then objects like fruits and flowers. I can’t access the cited study but is seems to focus on much shorter wavelengths than most UV sensitive animals are sensitive to. So I am quite sceptical of the UV camouflage idea.\nL132 Could there be a bit more precision in what is meant? A startle display generally involves some behavioural component, which does not seem to align with the animal being asleep: “predator encounters that wake sleeping snakes”?\nL195 “Natural ambient light” – was there any further requirement? In very overcast conditions there would be very little UV environmental light available for photography.\nL198 As ColorCheckers are not calibrated beyond visible and they do not seem to be used except to provide a scale bar, maybe just streamline and avoid confusion for future readers by saying the images had a scale bar in them?\nL216 What were the criteria for presence/absence and % cover? As you have calibrated image data and perform a quantitative analysis on a subset of data, it would be informative to explain why you subjectively quantified presence/absence and %cover for the main analysis (relates to main points 2 and 3).\nL220-221 Was this done using pixel values or by eyeballing? It is not clear.\nL263 – I’m confused by this – for interspecific analyses the sampling unit is the species – why is there a loss of statistical power? Or did the species sample change?\nFig 2 B&C – wouldn’t it be clearer if the same colour categories were presented in both (i.e. add ‘blue’, ‘orange’)?\nFig 3 b – colour contrast to what?\nSI Fig. 7 I think it should be clearer in the main text that results in several instances depended on the phylogeny used, and that quite a few results are borderline significant. In terms of the hypothesis testing the manual and computer scored metrics rarely produce the same result (1/7 significant results are common).\nYours sincerely,\nWill Allen", "reviewer_3": "I commend the authors for their commendable efforts in collecting what is evidently a challenging dataset, and the results presented in the manuscript are indeed intriguing. However, I have significant reservations regarding both the theoretical foundation and the methodology employed in this paper.\nIn the introduction, the authors argue that UV-coloration (or UV-reflectance) is often overlooked because it is cryptic to human perception, and its significance is primarily understood in the context of \"reproductive biology\" (pollination biology and sexual selection). I respectfully disagree with this assertion. The phenomenon of animals perceiving different wavelengths, including those invisible to humans, has been well-established for decades. A simple search on Web of Science yields over a hundred papers that address UV-reflection in various contexts, including predator-prey interactions, its significance in egg-rejection behavior among parasitic birds, parental favoritism, and social interactions. Consequently, it would be more appropriate to acknowledge that while UV-reflection is not ignored, its ecological and evolutionary importance remains an active area of investigation.\nThe authors make a bold claim that \"UV-coloration in snakes is driven by predators,\" and they support this assertion with several key observations from their data: 1) the reduced UV reflectance on the dorsal side of snakes, 2) the heightened UV reflectance in juveniles, and 3) the increased UV reflectance in arboreal snakes.\nIn my assessment, deducing such far-reaching conclusions from these observations is not justified. Firstly, there is a lack of evidence establishing a direct link between UV reflectance and predation risk in snakes. In other species, particularly butterflies and moths, the evidence regarding the impact of UV reflectance on predation risk is inconclusive, with some studies suggesting an increase in risk, while others find a decrease or neutrality. The authors seem to assume that UV reflection serves as a warning signal to predators, but the exact mechanism remains unclear (no note about venomousness of snakes for example). Moreover, this assumption raises questions about why juveniles, presumably more vulnerable, exhibit higher reflectance, and why the dorsal side of adult snakes, exposed to predators, displays lower UV reflectance. To address these issues, I strongly recommend that the authors conduct experiments or provide alternative evidence to establish the connection between UV reflection and predation risk in snakes.\nConsidering that the majority of snakes are nocturnal (with nocturnal species displaying stronger UV-reflection), their visibility to natural predators depends on both natural illumination (irradiance) and the predators' ability to perceive objects in low-light conditions. To better understand the relevance of UV reflection, it is crucial for the authors to calculate absolute quantum cone catch values for the sample patches of interest (preferably also including natural backgrounds) for predators' photoreceptor types. Such calculations require data on natural light levels, combining information on the light source's photonic emissions, the number of reflected photons, and the absorption by photopigments. In essence, this analysis will determine whether the objects of interest, especially UV-reflectance, are visible against their natural backgrounds in low-light conditions to relevant predators.\nRegarding snake anatomy, it is worth exploring the possibility that the heightened UV reflection in juveniles and arboreal snakes is non-adaptive or a byproduct of other factors. For instance, juveniles may have thinner skin and less developed scales compared to adults, while arboreal snakes may possess softer skin and less rough scales. If for example the oily liquid between the alpha-layer and beta-layer of snake skin, would be UV-reflective (many oils are), may simply reflect through the thin skin of juveniles? This hypothesis warrants investigation.\nIn conclusion, while the authors have undertaken commendable work and presented intriguing results, there is a need for a more robust theoretical foundation and a refined methodology to support their claims. Further experiments and analyses are essential to establish a direct link between UV reflection and predation risk in snakes."}, "author_response": "Response to Reviewers\nThank you very much for considering our revised submission. The referee comments were very helpful in strengthening the manuscript, especially in clarifying the methods and contextualising the results more carefully. We believe this revised version is much improved over the original. We thank the referees and editorial team for their time and care in giving thoughtful feedback.\nOur principal revisions to this manuscript include:\n• Revisions to the title, abstract, and throughout the manuscript to better align with uncertainty in causality in the absence of direct experimental evidence on predator perception and response\n• New analyses: we have incorporated new receiver visual systems to better test the contributions of chromacy and UV sensitivity to snake colour conspicuousness\n• Addition of a new literature review of papers testing the function of UV colouration and a new Figure 1 to support conceptual framing and significance\nReferee comments are in regular text and our responses are bolded. Please note that for logical flow, we have responded to the reviewers in the reverse order of Referee #3, #2, and then #1.\nReferee #3\nI commend the authors for their commendable efforts in collecting what is evidently a challenging dataset, and the results presented in the manuscript are indeed intriguing.\nThank you for your thoughtful engagement with the work - yes, snakes in the tropics are very challenging (but exciting) to collect in this breadth and depth!\nHowever, I have significant reservations regarding both the theoretical foundation and the methodology employed in this paper. In the introduction, the authors argue that UV-coloration (or UV-reflectance) is often overlooked because it is cryptic to human perception, and its significance is primarily understood in the context of “reproductive biology” (pollination biology and sexual selection). I respectfully disagree with this assertion. The phenomenon of animals perceiving different wavelengths, including those invisible to humans, has been well-established for decades. A simple search on Web of Science yields over a hundred papers that address UV-reflection in various contexts, including predator-prey interactions, its significance in egg-rejection behavior among parasitic birds, parental favoritism, and social interactions. Consequently, it would be more appropriate to acknowledge that while UV-reflection is not ignored, its ecological and evolutionary importance remains an active area of investigation.\nWe took this comment very seriously, and we of course agree that UV coloration has been studied in a number of contexts and clades over many years. However, it was unclear to us how uniformly distributed this research attention was overall. If a bias towards reports of UV traits related to a particular function did exist, we needed to quantify its magnitude - or its absence. So, we performed a large, standardised literature search as suggested, compiling and evaluating a database of 2,400 published articles matching to inclusive search terms about all UV colour across taxa. While many of these studies proved not to be relevant in an ecological context (e.g., UV light in laboratory methodologies), we identified 511 articles across major taxonomic groups that tested for either the a) function or b) perception of UV colouration in nature. We then classified these articles via abstracts and text by the ecological mechanism underlying UV reflection, ultimately binning by major functional classes of reproduction, survival, both, unknown, or other. We have added a new Supplementary Data File with all of these manuscripts and our scores (Supplementary Data 3), included a new figure showing counts in these different categories (now Fig. 1), and revised sections of the Introduction, Conclusions, and extensively in the Methods to reflect these changes.\nBriefly, we concluded that for the nearly 300 studies in this database that successfully inferred an ecological function of UV colour (not just its perception), the number reporting functions related to reproduction vastly outnumbered those related to survival. These results are shown in the new main text Fig. 1, in which we displayed raw counts for a) all taxa, and then b) only vertebrates, plotted in each panel by both subclade and function. However, to facilitate interpretation of these results by our author team, we also generated a null distribution for counts under the assumption that functions related to reproduction and survival were reported equivalently, within and among clades (see Key). We ultimately decided this comparison to a null distribution was too bulky for the manuscript, but we are including the full taxa version below for reviewers to evaluate (see below comparing expected [null distribution] counts to observed counts, numbers also noted in outer arcs, in the same style as Fig. 1). This exercise clearly demonstrates the magnitude of observed skew towards both reproduction and vertebrates/plants relative to what would be expected under a uniform model. Thus, we chose to retain the general conceptual framing and significance that pertained to this reviewer concern. However, we also agree (and note in our revised ms, lines 41-44) that the literature on this topic could easily be a biased subset of the true distribution of functions in nature for a range of reasons, including interests of the research community and relative ease with which certain functions can be studied.\nKey\nExpected distribution Observed distribution\nClade n Number of studies of studies of studies\n# supporting UV\ncolouration for\nsurvival Other insects Other insects\n76 4\nSpiders Butterflies + Moths Spiders Butterflies + Moths\nOther arthropods 4 15 Other arthropods 5 7\n10 0\nOther invertebrates 13 25 Flowering plants Other invertebrates 1 5 Flowering plants\nNumber of studies\nsupporting UV Vertebrates 6 Vertebrates 35\nClad # e n c re ol p o r u o ra d ti u on c t fo io r n 6 Vertebrates V 1 e 6 r 1 tebrates:\nFlowering plants 25 13 Other invertebrates Flowering plants 49 0 Other invertebrates\nC\n10 1\n15 4 Other arthropods 23 4 Other arthropods\nD B Butterflies + Moths Spiders Butterflies + Moths Spiders\nE\nF Arc lengths are A 76 6\nG proportional to clade’s Other insects Other insects\nglobal species richness\nThe authors make a bold claim that \"UV-coloration in snakes is driven by predators,\" and they support this assertion with several key observations from their data: 1) the reduced UV reflectance on the dorsal side of snakes, 2) the heightened UV reflectance in juveniles, and 3) the increased UV reflectance in arboreal snakes. In my assessment, deducing such far-reaching conclusions from these observations is not justified. Firstly, there is a lack of evidence establishing a direct link between UV reflectance and predation risk in snakes. In other species, particularly butterflies and moths, the evidence regarding the impact of UV reflectance on predation risk is inconclusive, with some studies suggesting an increase in risk, while others find a decrease or neutrality. The authors seem to assume that UV reflection serves as a warning signal to predators, but the exact mechanism remains unclear (no note about venomousness of snakes for example). Moreover, this assumption raises questions about why juveniles, presumably more vulnerable, exhibit higher reflectance, and why the dorsal side of adult snakes, exposed to predators, displays lower UV reflectance. To address these issues, I strongly recommend that the authors conduct experiments or provide alternative evidence to establish the connection between UV reflection and predation risk in snakes.\nRevised as suggested; we have removed “predators” from the title, as well as extensively revised language in the abstract, introduction, results, and conclusions to better align with uncertainty in causality. We have also provided better logical framing in the Discussion about how our results fit together within the possible mechanisms that could generate survival benefits to UV colouration. We agree that behavioural experiments on both predator and snake responses are the next round of experiments and data collection necessary to fully test these hypotheses - now informed by this new knowledge of which parts of a snake’s body are relevant to this test, and hopefully inspiring working groups beyond our own as well.\nAdditionally, we agree fully with the reviewer that any assumption that UV primarily serves as warning coloration would be premature and, in our view, less plausible than several alternative hypotheses (Lines 157-163). In our revised manuscript, we better define these potential mechanisms as either 1) crypsis, or 2) a “startle” or “signal boosting” effect that visible colour markings serve in defensive displays performed across the vast majority of snakes that are not dangerously venomous to predators (e.g., of which one example is the amazing display of Dasypeltis, which has no teeth at all: https://www.youtube.com/shorts/ eXJ2tBxaOUE; see also Gans & Richmond 1957, Copeia). We also note that like in this\nExtensively revised discussion, Lines 153-206.\nConsidering that the majority of snakes are nocturnal (with nocturnal species displaying stronger UV-reflection), their visibility to natural predators depends on both natural illumination (irradiance) and the predators' ability to perceive objects in low-light conditions. To better understand the relevance of UV reflection, it is crucial for the authors to calculate absolute quantum cone catch values for the sample patches of interest (preferably also including natural backgrounds) for predators' photoreceptor types. Such calculations require data on natural light levels, combining information on the light source's photonic emissions, the number of reflected photons, and the absorption by photopigments. In essence, this analysis will determine whether the objects of interest, especially UV-reflectance, are visible against their natural backgrounds in low-light conditions to relevant predators.\nWhile about half of the species in our dataset are nocturnal, the arboreal species in particular are still visible during the day while they sleep in trees. In that sense, the ability of a nocturnal snake to remain inconspicuous during daytime hours may be at least as important as its ability to do so at night. Furthermore, many nocturnal snakes begin moving early enough in the late afternoon that they may draw the attention of diurnal visually-oriented predators (revised manuscript, Lines 164-173). However, we broadly agree with this comment that an analysis of quantum cone catch values under nocturnal viewing conditions has the potential to be extremely informative and to provide qualitatively different information than the analysis we do present. These, and extensive natural background data, would be very exciting data to collect in the future.\nHowever, we elected not to compute absolute quantum cone catch values for patches of interest on the snakes in our images because we believe that these values would be difficult to interpret without first gathering extensive data on background (= ambient environmental) UV reflectance. We chose to focus on measures of internal contrast because they have ecological relevance but do not require comparisons with the background and would allow us to photograph and analyse each snake in a standardised way. In essence, the purpose of our visual modelling analysis was to ask whether the observed patterns of UV reflectance have the potential to affect how receivers view them. We chose a daylight illuminant primarily because UV light is more abundant during the day than at night, meaning selection pressure may be greatest for UV reflectance under daylight conditions.\nRegarding snake anatomy, it is worth exploring the possibility that the heightened UV reflection in juveniles and arboreal snakes is non-adaptive or a byproduct of other factors. For instance, juveniles may have thinner skin and less developed scales compared to adults, while arboreal snakes may possess softer skin and less rough scales. If for example the oily liquid between the alpha-layer and beta-layer of snake skin, would be UV-reflective (many oils are), may simply reflect through the thin skin of juveniles? This hypothesis warrants investigation.\nRevised as suggested: We have now added an extensive supplementary discussion section (Supplementary Text) on 1) skin, 2) scales, 3) shed/moult cycles, and 4) shine to address these concerns (and those of Reviewer #2).\nImportantly, we found that ventral scales – the biggest, thickest scales on all snake ecotypes and age classes – tended to have the highest UV reflectance, thus suggesting that softer or thinner scales are unlikely to explain either higher reflectance in juveniles or in arboreal taxa. This point is discussed more extensively in our revised Supplementary Text, as well as how scale property considerations may impact the study of every colour in reptile scales, rather than being something specific to UV wavelengths. We also acknowledge there that a better understanding of the cellular mechanisms underlying UV colour, including oils, will be important for resolving when and how scale properties themselves may be contributing to variation in UV reflectance. We agree fully that this warrants further investigation.\nIn conclusion, while the authors have undertaken commendable work and presented intriguing results, there is a need for a more robust theoretical foundation and a refined methodology to support their claims. Further experiments and analyses are essential to establish a direct link between UV reflection and predation risk in snakes.\nThank you again for your helpful comments!\nReferee #2\nI have very much enjoyed reviewing one of the first papers to study UV colouration in a broad sample of non-avian, non-lepidopteran species. The authors conclude that UV reflectance in some species of snake has an antipredator function. To do so, the paper tests expected relationships between colour form, sex, age, activity time and habitat in order to infer function. This is a useful and valid approach. Results show that UV reflectance is associated with being a juvenile, arboreality and nocturnality, but not with sex, interpreted as consistent with an antipredator function as opposed to a sexual function of being a neutral trait. As with almost all comparative evidence, this evidence is correlational, but that is the way it is – I commend the general approach taken, the quantity and quality of underlying data, as well as many aspects of the methodology and reporting.\nThank you!\nFor me, one of the most remarkable findings was that UV reflectance was associated with all visible colours (Fig 3 [author note: original Fig. 1c?]) but imperfectly so (i.e. some reds were UV reflective while others weren’t). This gives some confidence that UV reflectance is not just a side-effect of selection on non-UV colour. However, this remains my greatest concern for the interpretation that UV colour may have evolved under selection in snakes for an antipredator function, and that this may sometimes be independent of visible colouration. The large majority of white colours are classified as UV reflective and it could be that the chromophores involved in producing white colour are also involved in the production of other colours, for example to make them brighter. It is hard to tell without statistical analysis, but this appears to be suggested by Fig 1C – while UV reflectance does not seem to be correlated with any of the visible colours except white, within a colour category, visible and UV reflectance appear correlated (it would be good to present these analyses). If this is so, it could be that the UV reflectance is a consequence of selection on visible colour. I think discussion of colour production in snakes generally, and specifically of key study species (for example of Dipsas and Micrurus pictured in Fig 1.) could give more confidence here. What chromophores are responsible for white colour? Do these also contribute to colour in the examples of other UV reflective visible colours?\nRevised as suggested regarding what is known about chromatophores, pigments, and structural colours, as we have now added a supplementary discussion point about “white” (Supplementary Text, paragraph four): “The third concern is about whether the cellular mechanisms that could be producing UV reflectance may be correlated with a visible colour that itself is under selection, which would suggest our results could be a by-product of selection in the visible spectrum. We did measure white colours as UV reflective more often than any other visible colour (Fig. 2c, Fig. S4b; note that what humans perceive as “white” generally represents high reflectance across all visible wavelengths, see Fig. S2), but we do not yet have enough cellular data in snakes to assign structural or pigment-based mechanisms to most colours other than those produced by melanins (blacks) or pteridines (reds; with minimal to no carotenoids1), including UV or white. In lizards, it appears at least some UV reflectance is caused by structural colours rather than by pigments7, and this mechanism of a structural UV colour overlaying pigments of any variety would be consistent with our finding that many visible colours can have UV reflectance, including black (Fig. S1c; Fig. S4b; Fig 2c). While we cannot currently perform a formal test of this hypothesis, we consider the cellular mechanisms underlying UV colour to be the next big frontier in this field necessary to resolve some of these outstanding questions.”\nThis second suggestion - a formal analysis of whether UV reflectance correlates among and/ or within colours - was a very intriguing one that we thought a lot about how to implement appropriately in the context of biological rather than just statistical significance. We chose a Chi-squared approach to test if observed occurrences of colours that are also UV reflective deviated from expected values under a random distribution (now a new Fig. S4b). Not surprisingly, UV reflective white patches occurred at a significantly higher frequency than what would be expected under the null model. However, it is worth noting that every visible colour is reported to have at least one occurrence of UV reflectance and many colours (i.e., yellow, black, green, and brown) actually reflected significantly lower amounts of UV than expected, suggesting that selection for bright colouration alone does not drive UV reflectance. In relation to actual histology of the snake scales, it is possible that melanins and other non-white colour producing pigments may suppress the occurrence of UV reflectance, especially on the dorsal surfaces of snakes (the surface most exposed to predators). But overall, this analysis revealed that many colours, not just white, are correlated with UV production, likely favouring a structural colour mechanism overlaying pigments of any variety.\nMy second query, which may affect the conclusions drawn, is how UV reflectance relates to structural wear to the epidermis and moulting. We know these are issues affecting UV reflectance in birds (e.g. doi.org/10.1111/j.1095-8312.2002.tb02085.x). The epidermis of juveniles (and arboreal/nocturnal?) snakes could wear faster and/or moult more frequently, and this could contribute to results. Fig. 2a seems to suggest that individuals can vary in their overall UV reflectance (i.e. intra-individual UV reflectance of different colour patches is correlated – another analysis worth doing), which would be consistent with this idea. Additional measurement of individuals at different stages in the moult cycle would be very instructive and give more confidence in conclusions in my view.\nRevised as suggested; We have now added an extensive supplementary discussion section (Supplementary Text) on 1) skin, 2) scales, 3) shed/moult cycles, and 4) shine to address these concerns (and those of Reviewer #3).\nImportantly, we note that each individual can also be used as a control for itself in assessing the impact of shed state. Different scales on the same body are all at the same point in the shed cycle due to snakes moulting their entire epidermis as a single layer, and these scales can be directly compared. For example, the ventral scales of the “unreflective” snake on the left in original Fig. 2a (now Fig. 3a) are actually quite strongly UV reflective, even though the ventral scales are at the same shed cycle point as this snake’s dorsal scales. We include below another image of this same individual that emphasizes this comparison by simultaneously showing some ventral scales and some dorsal scales (some ventral scales are also visible in the original figure). This result was also true more broadly across the dataset, as we reported in the original manuscript that “UV reflectance on one body surface did not reliably predict reflectance on the other surface (all R2 = 0-0.11)” (Lines 76-77). We thus concluded that our overall results are unlikely to reflect something as simple as shed state.\nHowever, it is difficult to keep live snakes still enough for the required slow shutter speeds without significant unwanted medical intervention with veterinary oversight (these snakes were not intended for museum preservation like the others). Thus, our pilot efforts yielded unusable photos with motion blur, at non-standard illuminance angles, and without colour standards (see below), so we did not pursue repeated measures. However, these informal observations were fully consistent with Fig. 3’s display of variation across the phylogeny that variation among species was significant - and the expectation that no amount of shedding seems likely to make the Lichanura (below, panel d) UV reflective, as all that is visible on both dorsal and ventral surfaces is specular reflectance (and this exercise reminded us how amazed we are at having generated a dataset with so little specular reflectance visible to interfere with analysis - it’s a difficult lighting challenge). Note that none of these four species were in the original dataset, and we’ve not included them further.\nMy final substantial concern, which is mentioned in SI Fig 6 but I think needs to be brought to the main methods, is how gloss was considered and handled in analyses. This is related to the previous point – as well as species differences in gloss, glossiness also varies with moult and condition. Glossiness is interesting in that it is a component of the stimulus that a viewer will see looking at the snake, with recent work showing gloss can have antipredator and sexual functions, but it is different to other aspects of colouration in that it will vary with the relative positions of the illuminate and viewer, skin condition, and lighting directionality. As glossiness depends on dermal microstructure it could also plausibly be involved in locomotion, hydrophobicity etc. Clearly some of the UV reflectance in images is due to specular reflections – it sounds like these were avoided in measurement? What is the reasoning for this? Unfortunately I was unable to access the original image files to get a feel for how glossiness varies within and between species in your sample.\nRevised as suggested; we have now added a more extensive supplementary discussion section (Supplementary Text) on shine and also revised the main text methods to explain how human scorers avoided it (Lines 312-316) but computer scoring included it (Lines 336-339).\nAs in the collage above, specular reflectance was indeed the most annoying of the nuisance variables in our dataset, which as this reviewer notes is why we highlighted it in Fig S6. We did standardise the direction, position, and diffusion of all lights in order to both minimise and standardise where specular reflection appeared (Lines 284-287). This standardisation of directionality allowed human observers to simply avoid those patches as having “no scoreable data”, while the computer scores did include specular reflectance as UV reflectance. One test of whether this effect drove our ecological results was to directly compare the two metrics - one that fully included gloss and one that fully avoided it - and their persistent positive correlation (Fig S6b-d) suggested that the overall measurement impact of glossiness wasn’t the issue of greatest concern for the global dataset (although it did explain much residual variation specifically for the snakes with very low UV indices under manual scoring, low x-axis values in Fig S6b,c).\nHowever, we are also concerned that this reviewer was unable to access the entire dataset of photos that we had made available for review - please see the link below and let us know if you have any other difficulties! We invite reviewers to flip through them as desired.\nhttps://drive.google.com/drive/folders/1EvFojHAqmO13hr1yY1U0AcogM_7KxbyO\n(formal deposition embargoed until acceptance at: https://doi.org/10.7302/2ktf-6k49)\nSmaller points:\nL31-32 “essential for their communication” – ambiguous – rephrase.\nRevised as suggested, Lines 30-32, “However, the ability to perceive ultraviolet (UV) wavelengths (300-400 nm) is found in many other animals, and UV colour is used frequently in visual communication within and across species3, 4.”\nL39 There are other functions of colouration – for example anti-parasite colouration, colour used to lure or flush food, colour used for social signalling. Some of these functions make the same prediction as the anti-predator and sexual hypotheses. Could unique predictions for these functions be tested? If not, I think this issue needs to be acknowledged.\nRevised to clarify, although much of this revision as it pertains to non-reproductive hypotheses is actually now in the Discussion (Lines 153-186). We appreciate that some juvenile snakes do use brightly coloured caudal lures to attract prey, which would result in similar expectations regarding ontogenetic colour shifts, but would be restricted to tails, not heads/chins as we found (Line 79). However, caudal lures are documented mainly in a few pit vipers and in death adders (Elapids from Australia), and these known lurers are represented by only five pit viper species in our dataset. Additionally, our extensive literature review above also suggested that most tests of intraspecific communication couldn't rule out signals relevant for reproduction (mate choice, access to breeding sites, honest signals related to immune fitness for reproduction, etc.), although we scored some of these studies as \"both\" if survival was explicitly addressed, but mainly these would conflate with the hypotheses for reproduction and survival. Because we didn’t find outcomes supporting sexual or social signalling in our own study, we focused this clarification on mechanisms underlying survival and their lack of mutually exclusive predictions without additional data types.\nL64 What does P>0.1 mean here? “all Pagel’s lambda < 0.2; P > 0.1)” -> “all Pagel’s lambda < 0.2 and P(≠0) > 0.1)”?\nRevised as suggested, Lines 74-76: “UV reflectance on both dorsal and ventral surfaces showed little phylogenetic signal, even when accounting for phylogenetic uncertainty (all Pagel’s lambda < 0.2, and all p > 0.1). ”\nL130 Most natural surfaces (leaves, soil, rocks, bark, water) have low UV reflectivity, at least in the wavelengths most UV sensitive animals are sensitive to. Exceptions include surfaces like snow, light sand, then objects like fruits and flowers. I can’t access the cited study but it seems to focus on much shorter wavelengths than most UV sensitive animals are sensitive to. So I am quite sceptical of the UV camouflage idea.\nPartially revised as suggested - testing background reflectance is the next critical step that requires additional data, which we now highlight better in the Discussion (Lines 203-207). However, we note that trees in the tropics are literally covered in other life - fungi and lichens, epiphytes of all varieties, detritus, etc. - that could generate highly complex background patterns of UV reflectance and absorbance. We simply don’t have spectral reflectance profiles for the vast majority of these habitat elements across the tropics, as most work on reflectance spectra of plants and lichens is done at high latitude and/or high elevation. However, we did find (and now additionally cite) one study that measured both Neotropical lichens and their host tree bark in Costa Rica and released their raw data. We plotted their data here, and UV reflectance (below 390nm) is common and high in both:\nLichens\n1.0\n0.8\n0.6\n0.4\n0.2\n0.0\n400 600 800 1000\nWavelength (nm)\n10\necnatcelfeR\nBark\nUV Visible 1.0\n0.8\n0.6\n0.4\n0.2\n0.0\n400 600 800 1000\nWavelength (nm)\necnatcelfeR\nUV Visible\nWhile this is only one paper with one method for measuring reflectance (spectrometer only), we are cautiously encouraged by the plot above and hope our work’s publication inspires more research groups to take on this challenge of broadly quantifying background reflectance with both spectrometers and full spectrum imaging. We also revised the Discussion to further clarify the remaining hypotheses and what would be needed to test them, especially as pertains to crypsis, which remains the simplest hypothesis and therefore first in line to reject.\nRevised Discussion, Lines 165-173: “First, UV colouration could function to reduce detection by diurnal predators while nocturnal snakes sleep during the daytime, as both plants30 and their epiphytes31 can have UV reflectance. In this case, UV patterning could make a snake harder to detect by UV-sensitive birds living in trees, as in peppered moths on crustose lichens32. Nearly all arboreal snakes, both diurnal and nocturnal, are countershaded in the visible spectrum, offsetting lighter bellies with darker dorsal patterning. While some elements of these human-visible patterns are likely neutral, both green patterns (e.g., Fig. S1e) and blotchy patterns (e.g., Fig. 2a) are so universal and repeatable in arboreal taxa that “avoidance of detection” while exposed on tree branches is widely assumed to underlie the maintenance of such colour patterns31. Thus, the additional UV reflectance that we have documented to these otherwise broadly-visible pattern elements should not be assumed a priori to function differently.”\nRef 31, source of Costa Rican lichen data: Guzmán Q JA, Laakso K, López-Rodríguez JC, Rivard B, Sánchez-Azofeifa GA. Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest. Ecol Indic 111, 105999 (2020). Raw data: https://doi.org/ 10.7910/DVN/Y1J0UQ\nRevised Discussion, Lines 203-207: “Experimental tests involving reflectance measurements across the complex background conditions found in nature (e.g., with native lichens, fungi, etc. while in situ on tree branches), combined with predator responses to many combinations of snake colour patterns across these backgrounds, are the critical next step for determining the relative importance of these mechanisms across snake species.”\nL132 Could there be a bit more precision in what is meant? A startle display generally involves some behavioural component, which does not seem to align with the animal being asleep: “predator encounters that wake sleeping snakes”?\nRevised as suggested, Lines 173-176, “However, UV patterns could additionally function as a sort of startle or “signal boosting” colouration displayed by abruptly-awoken snakes to aid in escape immediately following predator encounters of sleeping snakes in a well-lit daytime environment32, 33, 34.”\nL195 “Natural ambient light” – was there any further requirement? In very overcast conditions there would be very little UV environmental light available for photography.\nL198 As ColorCheckers are not calibrated beyond visible and they do not seem to be used except to provide a scale bar, maybe just streamline and avoid confusion for future readers by saying the images had a scale bar in them?\nRevised as suggested, Lines 287-290, “We photographed specimens against a blue, black, or white matte background (Hengming; Guangzhou, China) with a 40% grey reflectance standard (Labsphere; North Sutton, USA) to standardise photos across variation lighting conditions and a 50mm scale bar.”\nL216 What were the criteria for presence/absence and % cover? As you have calibrated image data and perform a quantitative analysis on a subset of data, it would be informative to explain why you subjectively quantified presence/absence and %cover for the main analysis (relates to main points 2 and 3).\nRevised as suggested, clarified methods on Lines 308-312: “First, we scored the dorsal side of each snake for the presence or absence of UV reflectance by comparing pixels on the snake’s body to the 40% reflectance standard because pixels without reflectance looked uniformly dark in comparison (see Fig. 2a), and then we qualitatively estimated the overall proportion of the body with this reflectance (coverage).”\nFundamentally, these choices were simply logistical: some snakes moved/were moved between photos so that mspecs did not align properly, didn’t lie perfectly flat during photography due to body shape (i.e., had a lot of ventral surface visible in a dorsal image or vice versa), or otherwise did not have suitable RAW files. However, all photos were suitable for manual scoring by humans that could easily account for all of this variation. It ended up being quite interesting to compare where the two approaches differed, as they each had different strengths despite being in global alignment (Fig. S6). But overall, the manual scoring of UV reflectance was pretty straightforward and repeatable among scorers (see Data File 1), and we invite the reviewers to compare visible-to-UV “photo pairs” and scores themselves, too. We note that one of our author team members is not a herpetologist but 12\nwas able to understand and execute a trial set of independent scores with minimal direction.\nL220-221 Was this done using pixel values or by eyeballing? It is not clear.\nRevised as suggested, Lines 318-320: “We also qualitatively scored the brightness of the UV-reflective colour as being either less, more, or of similar brightness to the 40% colour standard.”\nL263 – I’m confused by this – for interspecific analyses the sampling unit is the species – why is there a loss of statistical power? Or did the species sample change?\nYes, due to the comments two points above, our number of species was lower for the computer-scored analyses, so the species sample changed and thus was reported in this line.\nFig 2 B&C – wouldn’t it be clearer if the same colour categories were presented in both (i.e. add ‘blue’, ‘orange’)?\nWe assume this comment referred to “Fig 1b,c” as we had no blue or orange in Fig 2. For Fig. 1c (now Fig 2c in the revised manuscript), the colour patches needed to be of a size and location that was reliable to isolate and measure (e.g., bright blue “cheek” stripes in Leptophis are visible in both dorsal and ventral photographs during manual scoring by a human, but neither camera perspective is ideal for measuring the lateral side of snake heads). These were the five colour groups in which we were the most confident and had the most robust sampling.\nFig 3 b – colour contrast to what?\nRevised as suggested for clarity (now Fig. 4b), and also Lines 366-372: “To directly assess the perceived chromatic contrast of entire snake colour patterns, we used the mean chromatic colour distance (∆S, the Euclidean distance between points in receiver colour space) as calculated by the LEIA analysis on the RNL-clustered image. ∆S summarizes the degree of colour contrast as a distance metric between two patches (e.g., ∆S between two pixels of the same colour will be 0) rather than directly comparing average brightness, and mean ∆S represents an average of these values across the whole organism. For example, a zebra would have a higher mean ∆S than a grey horse, even if they might have the same average luminance.”\nSI Fig. 7 I think it should be clearer in the main text that results in several instances depended on the phylogeny used, and that quite a few results are borderline significant. In terms of the hypothesis testing the manual and computer scored metrics rarely produce the same result (1/7 significant results are common).\nOverall, though, we were pleasantly surprised at how similarly these models and metrics performed, and we think this figure demonstrates that the results were in global alignment rather than discordance. We recommend assessing p-values specifically in the context of the boxplots, as this is the logic for how we evaluated model performance. First, we compared the boxplots between the two metrics and asked: were values consistent, such that those that were low in one metric also generally low in another and vice versa, even despite the differences in sample size (answer: yes). Then, given these boxplot distributions of the data by ecological category, were the analyses using the two phylogenies in strong conflict: specifically, did they 1) call categories significantly different when the boxplots were actually highly similar (answer: no - although this can legitimately occur with particular trait distributions across a phylogeny, it didn’t here), or did they 2) give p-values near 1 for one tree but near 0 for the other and thus show high conflict (answer: no).\nBecause the Zaher tree was the more underpowered test because it dropped so many of the non-colubrids (which non-randomly represent the earlier diverging taxa on longer branches) that were present in the Tonini tree, we explicitly expected that near-significant but above threshold p-values were likely for tests that were significant with the Tonini tree. This is indeed both the pattern and direction explaining the mild level of discordance between the two tests. We thus upweighted the Tonini results in the main text as the more robust test overall, but presented both in the supplement for the more specialised subset of readers like this reviewer who may be interested in details of model performance across phylogenies.\nYours sincerely,\nWill Allen\nThank you for your constructive comments!\nReferee #1:\nThis study investigates the presence of UV coloration in 110 snake species using ultraviolet photography and spectrophotometry, and assesses potential drivers (predation, sexual selection) for the evolution of UV signalling in these taxa. In the field of visual ecology, it is certainly interesting to know which species reflect UV colouration. This has been documented in multiple other species, including insects, birds and fish. However, it is challenging to provide convincing evidence that selective pressures act on UV coloration without more detailed visual modelling, understanding how these visual signals are displayed against background habitats, and ideally behavioural evidence of how potential signal receivers respond to UV signals. UV reflectance can also be a by-product of the physical properties of pigments or structural colours. While the number of species sampled is impressive, the broad conclusions that the authors make from the title, ‘Predators drive the evolution of ultraviolet colouration in snakes’ and conclusory sentences, ‘Our results show that predator-driven evolution of UV reflectance across snakes not only exists, but also provides a plausible process by which such patterns are maintained over evolutionary time’ are not supported by the data.\nRevised as suggested; we have removed “predators” from the title, as well as extensively revised language in the abstract, results, and discussion to better align with the level of uncertainty about causal inference that exists without the important, direct experimental evidence that this reviewer recommends.\nMajor points\nSpectral sensitivity curves and visual modelling: More information needs to be provided on the spectral sensitivity curves shown in Figure 3a, as there are some issues that may impact the visual modelling. It states that curves were from micaToolbox (bluetit [i.e., diurnal bird], human, and dog) and from the literature (owl43 and snake44).’ However, two species: Nocturnal bird vision and Dog vision state they are UV-, but clearly show the sensitivity curves extending into the UV. Filtering properties of corneas and lenses (e.g. filtering wavelength below 400nm) and oil droplets in birds may be altering the spectral sensitivity curves and need to be considered, otherwise the results from the modelling may be inaccurate. These details should be specified in the methods section and spectral sensitivity curves should be adjusted to show this.\nRevised as suggested; We have added more detail on the spectral sensitivity curves (new Supplementary Text, Supplementary Table 1), and species with low sensitivity in the UV part of the spectrum are now labelled as “UV-weak” rather than “UV-” in the figure (now Fig. 4a). Note also that in part due to this lack of detail on owl oil droplets, we have exchanged the owl model for the better established violet-sensitive peafowl (curves available in micaToolbox), as both this system and bluetit are both already adjusted for oil droplet filtering.\nChromacy: Also, the choice of taxa viewing the snake’s colour patterns also need careful consideration as you have a combination of UV+ and UV- sensitive species but also di-, tri- and tetra-chromatic visual systems. Contrast measures are generally going to be higher for those with higher levels of chromacy.\nRevised as suggested; We have now implemented a much improved order and grouping approach in Fig. 4 (originally Fig. 3), adding not only the peafowl but also gecko visual systems (both well characterised and available in micaToolbox) to create an intuitive “experimental design” of two systems per chromacy level that vary in UV sensitivity. We also conducted a multiple regression to test the significance of these two factors (chromacy and UV sensitivity) in predicting mean dorsal colour contrast, and yes, both are highly significant.\nRevised Results, Line 121-126: “To test whether the higher colour contrast for UV-sensitive visual systems was only the result of these visual systems’ higher chromacy, we fit a multiple regression model predicting colour contrast as a function of chromacy (2, 3, or 4 cones) and UV sensitivity (λ for the shortest peak sensitivity of any cone). Both UV max sensitivity and chromacy were significant predictors of colour contrast (P < 0.001), suggesting that the importance of UV reflectance in our results is not solely a consequence of our choice of visual systems.”\nNocturnal vision: The result stating that, ‘Nocturnal snakes also had significantly higher UV reflectance than diurnal snakes (t = 2.05; P = 0.046)’ does not support the hypothesis that predators are driving the amounts of UV reflectance in colour patterns. In nocturnal environments, most of the UV light from ambient conditions has disappeared. Also, in dim light conditions vertebrates switch over from cone-based vision to rod-based vision, which is not UV sensitive.\nRevised extensively (Lines 153-206) as suggested to clarify that we are considering interactions between predators and arboreal, nocturnal snakes explicitly during daylight hours when they are sleeping on branches. See also the response to Reviewer #2 above.\nVentral vs dorsal: If UV-contrast was driven by predators, then why is UV colouration also displayed at higher levels on ventral surfaces, as predators are unlikely to view the ventral surface during the predation sequence, ‘Dorsal UV reflectance was both lower overall and more concentrated into patches along the body than ventral reflectance (χ2 = 40.206; P < 0.001).’\nRevised Discussion to clarify the non-mutually exclusive selection mechanisms (and the direction of selection) that could generate discordance between ventral and dorsal surfaces.\nRevised Lines 187-206, “Additionally, our data cannot confirm that selection on UV colouration is directional towards higher UV reflectance, whether broadly on ventral surfaces or on patched dorsal surfaces on nocturnal, arboreal snakes. An alternative explanation is that dorsal UV reflectance is selected against in diurnal and terrestrial snakes, such that UV reflectance is only retained when it is selectively neutral, as on a rarely-visible surface like a belly. We note that these mechanisms are also not mutually exclusive, and both processes could interact simultaneously to produce a snake’s full colour phenotype. However, the latter mechanism would be a wholesale departure from the way UV colouration is currently conceptualised in both animal and plant systems, and it would require further experimental testing. Overall, the pervasive restriction of UV reflectance to patches or distinct body regions on the dorsum suggests that UV reflectance on low- visibility ventral surfaces may simply be under weaker selection (as in moths35) and that selection on the dorsum is not only strong, but in the direction of signal stabilisation rather than diversification (as in tropical birds38). This result would run counter to most theory on the evolution of “hidden channel” communication, in which UV signals are expected to have reliable species-specific information that should generate increased signal diversity4, but would be entirely consistent with crypsis. Experimental tests involving reflectance measurements across the complex background conditions found in nature (e.g., with native lichens, fungi, etc. while in situ on tree branches), combined with predator responses to many combinations of snake colour patterns across these backgrounds, are the critical next step for determining the relative importance of these mechanisms across snake species.”\nAlso, Revised Lines 166-179: “ Nearly all arboreal snakes, both diurnal and nocturnal, are countershaded in the visible spectrum, offsetting lighter bellies with darker dorsal patterning. While some elements of these human-visible patterns are likely neutral, both green patterns (e.g., Fig. S1e) and blotchy patterns (e.g., Fig. 2a) are so universal and repeatable in arboreal taxa that “avoidance of detection” while exposed on tree branches is widely assumed to underlie the maintenance of such colour patterns31. The additional UV reflectance that we have documented to these otherwise broadly-visible colour patterns should not be assumed a priori to function differently. However, UV patterns could additionally function as a sort of startle or “signal boosting” colouration displayed by abruptly-awoken snakes to aid in escape immediately following predator encounters of sleeping snakes in a well-lit daytime environment32, 33, 34. High UV reflectance has been found in other nocturnal lineages, especially within insect groups like moths, which also have higher reflectance on hindwings that are hidden at rest but deployed during diurnal disturbance35 in the same manner as snake venters11.”\nMinor issues\nL154-155: ‘One fundamental insight from this work is that none of this UV reflectance is predictable from the snake’s visible colour pattern alone.’ I do not think that most in the field of visual ecology would hypothesis that UV reflectance could be predicted by visible reflectance, so I find this a strange conclusion from the study. Colours are often described by whether they contain a UV component or they don't, for example: blue versus UV-blue, but there has never been any predictions that I have seen that states that by understanding the reflectance in the visible you would be able to know anything about the amount or presence of UV reflectance of the same colour patch.\nRevised as suggested to clarify intent, as we fully agree with this great example about blue vs. UV-blue, etc. We more meant that researchers should not simply make decisions about which species are likely to have (or not have) UV reflectance because they are making an unconscious judgement about taxa based on their visible patterning, rather than implying that researchers have been assuming that every organism that was a certain colour should additionally have (or not have) UV reflectance.\nThe authors state L89 that ‘This repeated, non-random evolutionary convergence across habitat specialisations strongly supports the conclusion that predators play a critical role in the evolution of UV reflectance across snake species’; however, the study does not investigate the visual characteristics of the background the snakes are viewed against, so it is hard to make inferences from this.\nRevised as suggested to clarify that these results more strongly reflect a rejection of neutrality and remaining more agnostic about agents of selection, Lines 103-106: “This repeated evolutionary convergence across the same habitat specialisations is inconsistent with a conclusion that neutral processes are driving the evolution of UV reflectance across these snake species, suggesting instead that UV colour is under natural selection.”\nL251: ‘Create luminance channel function by averaging together the long- and medium wavelength-sensitive channels, which is the standard in visual ecology’. This needs a citation and it depends on the taxa. For example, fish are thought to process luminance using their double cones, but also use double cones for processing chromatic information. Whereas birds have single cones for colour vision but are thought to only process luminance information through double cones. So it is a little more complicated than stated.\nRevised as suggested, Lines 377-379: “For cone-catch models that did not include a luminance channel for edge intensity analysis (dog, human, and snake), we created one using the ‘Create luminance channel’ function by averaging together photoreceptor channels following the literature (see Supplementary Table 1).”\nWe have also added λ and Weber fraction information for each receiver to this new max\nSupplementary Table 1, and added an additional section “Additional Quantitative Color Pattern Analysis (QCPA) parameters” to Supplementary Text.\nL254: There are multiple ways of measuring contrast, so this needs to be explained in more detail here, rather than rely on referencing the QCPA paper or the supplementary information. This doesn’t tell you how these measures are calculated, which is important for the results. For example, in Figure 2, it needs to be made clear what the units refer to.\nRevised as suggested, we have now clarified units in both Fig. 3 and 4 (originally Fig. 2-3), and added text to the Methods:\nRevised lines 366-371: “To directly assess the perceived chromatic contrast of entire snake colour patterns, we used the mean chromatic colour distance (∆S, the Euclidean distance between points in receiver colour space) as calculated by the LEIA analysis on the RNL-clustered image. ∆S summarizes the degree of colour contrast as a distance metric between two patches (e.g., ∆S between two pixels of the same colour will be 0) rather than directly comparing average brightness, and mean ∆S (ΔS) represents an average of these values across the whole organism.”\nRevised Lines 323-327: “Then, scores were combined into a snake’s UV reflectance index by first averaging scores across the two observers, and then multiplying the mean brightness score by the mean proportion of the body with UV reflectance (coverage). We performed these calculations separately for dorsal and ventral surface indices and summed them for an overall reflectance index per snake, and all three of these indices were retained for downstream statistical analysis.”\nAgain, many thanks to all reviewers for their thoughtful comments on this work!\nReviewer #1 (Remarks to the Author):\nThe authors have done a thorough revision of their manuscript, and I feel that it is much stronger as a result of this. I have a few remaining comments:\nL374-L376: The reference to average brightness in this explanation is confusing. If you are using deltaS for colour contrast measurements, this is the difference in chromaticity of two colour patches, and is not a measure of brightness. The example of a Zebra and a grey horse is measuring difference in brightness, as the colour contrast for black and white would be 0. The discussion between colour contrast and brightness contrast needs disentangling as it does not make sense as it is currently written. A better example would be how blue and yellow would combine to make green.\nFigure 4a: Can the authors please specify which ocular filters/ oil droplets were considered when calculating the spectral sensitivity curves for each species? As mentioned in the MICA toolbox these should be considered and specified when using the data for visual modelling. Examining the shape of the curves, all the UV – or UV weak species appear to have the relevant opsin spectral sensitivity curves multiplied by the ocular media or oil droplets, except for the dog. I would find it unlikely that dogs do not have some kind of UV blocking properties in their cornea etc that would limit the transmission of UV to the retina and this reduce the Beta curve that are shown at 360nm. Can the authors provide a reference to show that these do or do not exist?\nL111 onwards: It should be mentioned that the relationship between deltaS and conspicuousness may not be linear, as shown in:\nSantiago, C., Green, N. F., Hamilton, N., Endler, J. A., Osorio, D. C., Marshall, N. J. and Cheney, K. L. (2020). Does conspicuousness scale linearly with colour distance? A test using reef fish. Proceedings of the Royal Society B: Biological Sciences, 287 (1935) 20201456. doi: 10.1098/rspb.2020.1456\nReviewer #2 (Remarks to the Author):\nDear Authors,\nOverall I am impressed by the attention given to revisions, which have really improved the manuscript in my view. I have a few thoughts and pieces of feedback remaining, some of them new following revisions:\nI understand the investigation of colour production mechanisms is likely the next big challenge in this line of research, but providing some initial information on your hypothesis that UV reflection is structural and can overlay pigmentary colours, would be very useful. This could draw on comparative evidence from lizards, or if you are able to push the boat out and include a SEM image, that would be amazing.\nI still do not think “(all Pagel’s lambda < 0.2, and all p > 0.1)” is reported right. The tests of Pagel’s lambda are whether lambda differs from zero or one. As lambda is low, I assume the test reported is that it is not significantly different from zero, but this should be reported “p(≠0) =” as noted in my previous review.\nYou are absolutely right that we lack good quality information on background reflectance in natural habitat. I really would have hoped someone would have been funded to take a comprehensive look at this by now! I had not seen the Guzmán et al. paper measuring bark and lichen reflectance in Costa Rica and looked it up. The authors have low confidence in their UV measurements, and do not report these in their main text (“After careful consideration, bands at the edges of the spectrometer range (the shortest and longest wavelengths) were omitted due to relatively low signal-to-noise ratios of these wavelength regions. As a result, the wavelength range of 450–1000 nm (171 bands) was retained for all the ensuing data analysis.”). Thus, I am not aware of studies that report high UV bark reflection – data is limited, but most reports are of low bark UV reflection, or limited UV contrast with non UV reflecting stimuli – e.g.:\nCampbell SA, Borden JH. Bark reflectance spectra of conifers and angiosperms: implications for host discrimination by coniferophagous bark and timber beetles. The Canadian Entomologist. 2005;137(6):719-722. doi:10.4039/n04-082\nIt is however a good point that lichens can be UV reflective – there is better data of this e.g. https://doi.org/10.1016/j.rse.2020.111955 and the Majerus paper cited.\nL99 (track changes version) Doesn’t this now suggest they are coupled?\nL173 “other ecological factors that can covary with habitat usage” I think these need to be indicated.\nL444 “We note that computer-scored metric required the highest quality photos in raw format, so these represent a subset of ~30% of all snakes measured and a concomitant reduction in statistical power. (N = 65 species).” I think the main methods need to be clearer that it was not possible to create mspecs for some individuals because of animal movement & consequent impossibility of image alignment.\nSnake images throughout – why have the images not been standardised to the reflectance standard (some are pink, or various shades of grey)? Doing so would facilitate comparison.\nThe SI does a good job of addressing the concerns raised by myself and other reviewers about the possibilities for scale thickness, shed state, oils, shine, and selection on non-UV colour to explain results. I think the section reads a bit too much like a ‘response to reviewer comments’ at the moment – which it is, but I suggest editing the tone to incorporate these as valid possibilities to be evaluated (at the moment it reads a bit too much like things to be ruled out). It still seems quite plausible to me that juveniles are found to be more UV reflective than adults in the analysis because they shed more frequently, or are oilier, rather than natural selection on UV colour.\n“The additional UV reflectance that we have documented to these otherwise broadly-visible colour patterns should not be assumed a priori to function differently “ UV/white colour/countershading – worth considering that background matching countershading of snakes viewed from below (which may happen for arboreal snakes) would need to reflect UV to better match the UV in downwelling light (difficult to be reflective enough though – looking up at arboreal snakes they are generally silhouetted).\nYours sincerely,\nWill Allen\nRevised as suggested; note that our major revision was to remove mention of the data from the literature search from the introduction as requested, and instead detail these results as a new first subsection of Results.\nReviewer #1 (Remarks to the Author):\nThe authors have done a thorough revision of their manuscript, and I feel that it is much stronger as a result of this. I have a few remaining comments:\n1.) L374-L376: The reference to average brightness in this explanation is confusing. If you are using deltaS for colour contrast measurements, this is the difference in chromaticity of two colour patches, and is not a measure of brightness. The example of a Zebra and a grey horse is measuring difference in brightness, as the colour contrast for black and white would be 0. The discussion between colour contrast and brightness contrast needs disentangling as it does not make sense as it is currently written. A better example would be how blue and yellow would combine to make green.\nRevised as suggested (new manuscript line 399-404): “Chromatic ∆S summarises the degree of colour contrast as a distance metric between two patches (e.g., ∆S between two pixels of the same colour will be 0) rather than directly comparing average chromaticity, and mean chromatic ∆S represents an average of these values across the whole organism. For example, the blue, red, and yellow plumage of a scarlet macaw would have a higher chromatic ∆S than a uniformly green bird, even if they might have the same average chromaticity.”\n2.) Figure 4a: Can the authors please specify which ocular filters/ oil droplets were considered when calculating the spectral sensitivity curves for each species? As mentioned in the MICA toolbox these should be considered and specified when using the data for visual modelling. Examining the shape of the curves, all the UV – or UV weak species appear to have the relevant opsin spectral sensitivity curves multiplied by the ocular media or oil droplets, except for the dog. I would find it unlikely that dogs do not have some kind of UV blocking properties in their cornea etc that would limit the transmission of UV to the retina and this reduce the Beta curve that are shown at 360nm. Can the authors provide a reference to show that these do or do not exist?\nRevised as suggested: We have added a sentence to the caption of figure 4 referring the reader to Supplementary Table 1, where we have added a column and citations for UV transmission of ocular media/oil droplets for each of the receivers in our analysis to that table.\nRevised manuscript, Fig 4 caption: “See Supplementary Table 1 for details and citations of visual systems used, including λmax, oil droplets/ocular media affecting UV transmission, and calculation of luminance channels.”\n3.) L111 onwards: It should be mentioned that the relationship between deltaS and conspicuousness may not be linear, as shown in:\nSantiago, C., Green, N. F., Hamilton, N., Endler, J. A., Osorio, D. C., Marshall, N. J. and Cheney, K. L. (2020). Does conspicuousness scale linearly with colour distance? A test using reef fish. Proceedings of the Royal Society B: Biological Sciences, 287 (1935) 20201456. doi: 10.1098/rspb.2020.1456\nRevised as suggested with new citation included (new manuscript line 147-150).\nReviewer #2 (Remarks to the Author):\nDear Authors,\nOverall I am impressed by the attention given to revisions, which have really improved the manuscript in my view. I have a few thoughts and pieces of feedback remaining, some of them new following revisions:\n1.) I understand the investigation of colour production mechanisms is likely the next big challenge in this line of research, but providing some initial information on your hypothesis that UV reflection is structural and can overlay pigmentary colours, would be very useful. This could draw on comparative evidence from lizards, or if you are able to push the boat out and include a SEM image, that would be amazing.\nAs a manuscript on the ecological relevance of colouration that did not take any direct data on colour production, we are hesitant to overspeculate about potential cellular mechanisms in the main text. We appreciate that this may mean that our supplementary discussion may be overlooked by some readers who only read the main text, but we think that this is preferable to prioritising conclusions about data we did not collect over data that we did present.\n2.) I still do not think “(all Pagel’s lambda < 0.2, and all p > 0.1)” is reported right. The tests of Pagel’s lambda are whether lambda differs from zero or one. As lambda is low, I assume the test reported is that it is not significantly different from zero, but this should be reported “p(≠0) =” as noted in my previous review.\nRevised to meet the intent of the comment without introducing unnecessary confusion, lines 94-97: “UV reflectance on both dorsal and ventral surfaces showed little phylogenetic signal, even when accounting for phylogenetic uncertainty (all Pagel’s lambda < 0.2 and all p > 0.1, and thus not significantly different from zero).”\n3.) You are absolutely right that we lack good quality information on background reflectance in natural habitat. I really would have hoped someone would have been funded to take a comprehensive look at this by now! I had not seen the Guzmán et al. paper measuring bark and lichen reflectance in Costa Rica and looked it up. The authors have low confidence in their UV measurements, and do not report these in their main text (“After careful consideration, bands at the edges of the spectrometer range (the shortest and longest wavelengths) were omitted due to relatively low signal-to-noise ratios of these wavelength regions. As a result, the wavelength range of 450–1000 nm (171 bands) was retained for all the ensuing data analysis.”). Thus, I am not aware of studies that report high UV bark reflection – data is limited, but most reports are of low bark UV reflection, or limited UV contrast with non UV reflecting stimuli – e.g.:\nCampbell SA, Borden JH. Bark reflectance spectra of conifers and angiosperms: implications for host discrimination by coniferophagous bark and timber beetles. The Canadian Entomologist. 2005;137(6):719-722. doi:10.4039/n04-082\nIt is however a good point that lichens can be UV reflective – there is better data of this e.g. https://doi.org/10.1016/j.rse.2020.111955 and the Majerus paper cited.\nAfter further reviewing the suggested article on lichens, we have decided not to include it in our literature cited list as its focus is on ground lichens in boreal forests while our paper explores hypotheses behind the higher UV reflectance in arboreal snakes in primarily tropical habitats.\n4.) L99 (track changes version) Doesn’t this now suggest they are coupled?\nThank you for catching this typo; the sentence was supposed to read “...UV reflectance could not be reliably predicted…” rather than “...could be…” We have edited the sentence to reflect this change (new manuscript lines 99-103).\n5.) L173 “other ecological factors that can covary with habitat usage” I think these need to be indicated.\nRevised as suggested (new manuscript lines 168-170). This sentence now includes an example of one such ecological factor (diet), with a new reference.\n6.) L444 “We note that computer-scored metric required the highest quality photos in raw format, so these represent a subset of ~30% of all snakes measured and a concomitant reduction in statistical power. (N = 65 species).” I think the main methods need to be clearer that it was not possible to create mspecs for some individuals because of animal movement & consequent impossibility of image alignment.\nRevised as suggested (new manuscript lines 420-424): “We note that the computer- scored metric required the highest quality photos in raw format, in which the visible and UV photos of the specimen could be perfectly aligned, which was not always possible (e.g., if the specimen was moved slightly in between photos). Usable image pairs represent a subset of ~30% of all snakes measured and a concomitant reduction in statistical power (N = 65 species).”\n7.) Snake images throughout – why have the images not been standardised to the reflectance standard (some are pink, or various shades of grey)? Doing so would facilitate comparison.\nSnake images have been rebalanced and standardised as suggested.\n8.) The SI does a good job of addressing the concerns raised by myself and other reviewers about the possibilities for scale thickness, shed state, oils, shine, and selection on non-UV colour to explain results. I think the section reads a bit too much like a ‘response to reviewer comments’ at the moment – which it is, but I suggest editing the tone to incorporate these as valid possibilities to be evaluated (at the moment it reads a bit too much like things to be ruled out). It still seems quite plausible to me that juveniles are found to be more UV reflective than adults in the analysis because they shed more frequently, or are oilier, rather than natural selection on UV colour.\nWe have extensively revised this section as suggested. We changed the overall tone to present these possibilities more so as valid ideas to be considered when explaining the mechanisms behind intraspecific differences in UV reflectance rather than factors to be ruled out completely.\n9.) “The additional UV reflectance that we have documented to these otherwise broadly-visible colour patterns should not be assumed a priori to function differently “\nUV/white colour/countershading – worth considering that background matching countershading of snakes viewed from below (which may happen for arboreal snakes) would need to reflect UV to better match the UV in downwelling light (difficult to be reflective enough though – looking up at arboreal snakes they are generally silhouetted).\nRevised as suggested (new manuscript lines 190-193): “In addition, higher amounts of UV reflectance on the ventral surfaces of these snakes could aid in crypsis when viewed from below by terrestrial or understory-dwelling predators, as these colours would presumably contrast less with the UV-intense backdrop of the sky.”\nYours sincerely,\nWill Allen\nReviewer #2 (Remarks on code availability):\nI had a look and everything seems in order. I don't have time to run the code though. The images could be a good resource for other studies."}]

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