Microhabitat Partitioning Correlates with Opsin Gene Expression in Coral Reef

Home , Cheilodipterus, Nectamia, Ostorhinchus, Ostorhinchus cookii, Ostorhinchus cyanosoma, Ostorhinchus doederleini

1 Microhabitat partitioning correlates with opsin gene expression in coral reef

2 cardinalfishes (Apogonidae)

4 Martin Luehrmann (ML) 1, Fabio Cortesi (FC) 1, Karen L. Cheney (KLC) 1,2, Fanny de Busserolles

5 (FbB)1, N. Justin Marshall (JM) 1

7 1Queensland Brain Institute, The University of Queensland, Sensory Neurobiology Group, 4072,

8 Brisbane, QLD, Australia

9 2School of Biological Sciences, The University of Queensland, 4072, Brisbane, QLD, Australia

11 Corresponding Author: Dr Martin Luehrmann

12 Sensory Neurobiology Group, Queensland Brain Institute, University of Queensland, Brisbane |

13 QLD 4072 | Australia, Fax number: +61 (0)7 33654522

14 Email: [email protected]

16 Keywords

17 Microhabitat partioning, opsin gene expression, fish, cardinalfish, LWS, RH2, SWS2, vertebrate

18 visual system evolution, eye size, retinal topography

20 Headline: Visual adaptation to microhabitats in reef fish Author Manuscript

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/1365-2435.13529

This article is protected by copyright. All rights reserved 1 2 DR MARTIN LUEHRMANN (Orcid ID : 0000-0002-4060-4592) 3 DR KAREN CHENEY (Orcid ID : 0000-0001-5622-9494) 4 5 6 Article type : Research Article 7 Editor : Christine Miller 8 Section : Evolutionary Ecology 9 10 11 Microhabitat partitioning correlates with opsin gene expression in coral reef 12 cardinalfishes (Apogonidae) 13 14 Martin Luehrmann (ML) 1, Fabio Cortesi (FC) 1, Karen L. Cheney (KLC) 1,2, Fanny de Busserolles 15 (FbB)1, N. Justin Marshall (JM) 1 16 17 1Queensland Brain Institute, The University of Queensland, Sensory Neurobiology Group, 4072, 18 Brisbane, QLD, Australia 19 2School of Biological Sciences, The University of Queensland, 4072, Brisbane, QLD, Australia 20 21 Corresponding Author: Dr Martin Luehrmann 22 Sensory Neurobiology Group, Queensland Brain Institute, University of Queensland, Brisbane | 23 QLD 4072 | Australia, Fax number: +61 (0)7 33654522 24 Email: [email protected] 25 26 Keywords 27 microhabitat partioning, opsin gene expression, fish, cardinalfish, LWS, RH2, SWS2, vertebrate 28 visual system evolution, eye size, retinal topography 29 Abstract 30 Author Manuscript 31 1. Fish are the most diverse vertebrate group, and they have evolved equally diverse visual 32 systems, varying in terms of eye morphology, number and distribution of spectrally distinct 33 photoreceptor types, visual opsin genes and opsin gene expression levels.

This article is protected by copyright. All rights reserved 34 2. This variation is mainly due to adaptations driven by two factors: differences in the light 35 environments and behavioural tasks. However, while the effects of large-scale habitat 36 differences are well described, it is less clear whether visual systems also adapt to 37 differences in environmental light at the microhabitat level. 38 3. To address this, we assessed the relationship between microhabitat use and visual system 39 features in fishes inhabiting coral reefs, where habitat partitioning is particularly common. 40 4. We suggest that differences in microhabitat use by cardinalfishes (Apogonidae) drive 41 morphological and molecular adaptations in their visual systems. To test this, we 42 investigated diurnal microhabitat use in 17 cardinalfish species and assessed whether this 43 correlated with differences in visual opsin gene expression and eye morphology. 44 5. We found that cardinalfishes display six types of microhabitat partitioning behaviours 45 during the day, ranging from specialists found exclusively in the water column to species 46 that are always hidden inside the reef matrix. 47 6. Species predominantly found in exposed microhabitats had higher expression of the short- 48 wavelength sensitive violet opsin (SWS2B) and lower expression of the dim-light active rod 49 opsin (RH1). Species of intermediate exposure, on the other hand, expressed opsins that are 50 mostly sensitive to the blue-green central part of the light spectrum (SWS2As and RH2s), 51 while fishes entirely hidden in the reef substrate had a higher expression of the long- 52 wavelength sensitive red opsin (LWS). 53 7. We also found that eye size relative to body size differed between cardinalfish species, and 54 relative eye size decreased with an increase in habitat exposure. 55 8. Retinal topography did not show co-adaptation with microhabitat use, but data suggested co- 56 adaptation with feeding mode. 57 9. We suggest that, although most cardinalfishes are nocturnal foragers, their visual systems – 58 and possibly those of other (reef) fishes – have also adapted to the light intensity and the 59 light spectrum of their preferred diurnal microhabitats.

60 Introduction 61 Animal visual systems are functionally diverse, with differences at the morphological and 62 the molecular level. In fish, this diversity is mainly driven by differences in the availability of light 63 (Hauser and Chang, 2017; Land and Nilsson, 2002), but can also be due to differences in habitat 64 complexity (Collin andAuthor Manuscript Shand, 2003; Hughes, 1977) or specific behavioural tasks, e.g. foraging or 65 sexual selection (reviewed in Hauser and Chang, 2017; Price, 2017). In aquatic environments, 66 differences in light mainly arise from wavelength selective light absorption and scattering due to 67 depth, the size of suspended particles, and the reflectance of such particles or the substrate 68 (Lythgoe, 1979). For example, the deep-sea has a blue-shifted light environment and consequently, This article is protected by copyright. All rights reserved 69 deep-sea species generally possess photoreceptors that are maximally sensitive to blue light (~ 480 70 nm) (Partridge et al., 1992). 71 72 Morphologically, visual systems may differ in eye size, shape, and at the retinal level in 73 functional type, number and/or distribution of neural cells including photoreceptors. Morphological 74 changes to boost sensitivity in low-light conditions, for example, may include rod-dominated 75 retinas, increased relative eye size, or a higher photoreceptor-to-ganglion cell summation ratio (de 76 Busserolles and Marshall, 2017; Kelber and Roth, 2006; Warrant, 2004). 77 78 At the molecular level, the part of the electromagnetic spectrum to which a photoreceptor is

79 maximally sensitive (λmax) may vary, primarily due to changes in its photopigments (Hunt and 80 Collin, 2014). Photopigments are molecules comprised of opsins - membrane-bound proteins with 81 receptor function - to which a vitamin A-derived chromophore is covalently bound. While in 82 vertebrates only two chromophore types (Vitamin A1 or A2) occur, opsins are more variable. They

83 are classified according to their λmax values, their phylogeny, and their specificity to 84 morphologically distinct photoreceptor types (Hunt et al., 2014). Opsins may alter photoreceptor

85 λmax via i) variations in their amino acid sequences, or ii) via differential expression of the different 86 opsin genes (reviewed in Carleton et al., 2016). In vertebrates, five opsin classes are found: rod- 87 specific rhodopsin (RH1) used for scotopic vision, and four cone specific classes used for photopic 88 and colour vision: SWS1 (short-wavelength-sensitive 1, ultraviolet); SWS2 (short-wavelength- 89 sensitive 2, violet/blue); RH2 (rhodopsin-like 2, blue-green/green); LWS (long-wavelength- 90 sensitive, yellow/red)(Hunt et al., 2014). In percomorph fishes, gene duplication has resulted in a 91 more diversified repertoire consisting of rod-specific RH1, single cone specific SWS1, SWS2B

92 (violet), SWS2A and SWS2A (blue), and double cone specific RH2B (blue-green), RH2A 93 (green), and LWS (Cortesi et al., 2015; Hunt and Collin, 2014). 94 95 In fish, visual systems adapt to large-scale lighting differences due to habitat depth, type 96 (e.g. reef vs. open ocean), or season (Lythgoe, 1979; Lythgoe et al., 1994; Muntz, 1982). However, 97 fish vision may also be tuned to light differences between habitats on smaller scales for species 98 sharing the same general habitat at similar depths. For example, in some African cichlids, opsin

99 gene expression differsAuthor Manuscript depending on the associated substrate (e.g. rock vs sand) (Sabbah et al., 100 2011). The photoreceptor spectral sensitivities of surfperch living among California’s kelp forests 101 are tuned to light in structurally distinct parts of that general habitat (e.g. canopied vs not-canopied) 102 (Cummings and Partridge, 2001). However, although suggested (Lythgoe, 1979; Marshall et al., 103 2003), it remains to be tested whether this phenomenon may be acting on an even smaller –

This article is protected by copyright. All rights reserved 104 microhabitat – scale, and thus contributing to the remarkable diversification of colour vision among 105 fishes living on coral reefs, one of the most diverse ecosystems on earth, where species based 106 habitat partitioning, at times within a single coral head, is particularly common (reviewed in 107 Williams, 1991). 108 109 Here, in order to control for potentially confounding factors like phylogenetic constraint, we 110 focused on a group of closely related reef fishes with remarkable visual system diversity, the 111 cardinalfishes (Apogonidae) (Fishelson et al., 2004; Luehrmann et al., 2019). These fishes are 112 common on shallow tropical coral reefs, are one of the most abundant reef fish families, and are 113 predominantly nocturnal foragers (Marnane and Bellwood, 2002). However, during the day they 114 aggregate in large multi-species groups in and around the reef matrix, in particular caves and 115 branching corals (e.g. Porites cylindrica) (Gardiner and Jones, 2005; Greenfield and Johnson, 116 1990), where they carry out social behaviours, such as pair formation and mating (reviewed in 117 Vagelli, 2011). A previous survey of seven species found that in these multi-species aggregations 118 fish display fine-scale microhabitat partitioning among the same diurnal refuge sites, with some 119 species found predominantly outside, and others within or below reef structures (Gardiner, 2010). 120 121 To test whether their visual system setup is related to microhabitat use, we compared the 122 microhabitat partitioning behaviour of 17 cardinalfish species to morphological and molecular 123 differences in their visual systems. First, we conducted an ecological assessment of habitat 124 partitioning in these focal species. Second, we tested whether their opsin gene expression, and/or 125 relative eye size – as a proxy for light sensitivity (Land, 1990), correlated with diurnal microhabitat 126 use. We used our previous opsin expression data which showed that cardinalfishes express multiple 127 visual opsins, and that based on differences in opsin gene expression and spectral sensitivities, 128 species can be placed into five, possibly functionally distinct, groups (Luehrmann et al., 2019). 129 Third, the retinal photoreceptor and/or ganglion cell topographies of five cardinalfish species from 130 different microhabitats were determined to gain additional insight into these fishes’ adaptations to 131 their environment. Finally, visual system diversity was also tested for correlation with cardinalfish 132 feeding ecology and activity period. 133

134 Materials and MethodsAuthor Manuscript 135 Microhabitat use assessment 136 Underwater visual surveys were conducted on SCUBA to determine microhabitat use of 23 137 cardinalfish species (Table 1) on reefs surrounding Lizard Island (14º 40’S, 145º 28’E), Great 138 Barrier Reef, Australia (Fig. 1). Fish counts were conducted between 6.30 am and 4 pm, from 3-14 This article is protected by copyright. All rights reserved 139 March 2017. Data for Apogonichthyoides melas and Pterapogon cf. mirifica was taken from counts 140 between 10 Feb. and 20 April 2015, as these species were not found during counts in 2017. Counts 141 were performed as spot-counts at 111 sites distributed over eight different locations at depths 142 between 1 and 6 m, with a site defined as a separate coral head, outcrop or boulder located > 5 143 meters apart (Fig. 1b). When a site was encountered, we approached slowly and waited for several 144 minutes to ensure fish behaviour was not disturbed. Then, we recorded individual animal numbers 145 to 20 and estimated larger groups to the nearest 50. We avoided double counting of sites by 146 navigating around the locations systematically. We counted fish in four distinct microhabitat 147 partitions defined as per Fig. 1c. For microhabitat partitioning analysis, we only used species for 148 which at least ten individuals were counted at > 3 different sites, and then calculated the frequency 149 of occurrence at each microhabitat partition as a proportion of total individuals counted per species 150 (Fig. S1, Table 1). To identify patterns of microhabitat use, we then used hierarchical cluster 151 analysis [Ward.D2, bootstrap=100, R-package: pvclust (R Core team, 2014; Suzuki and 152 Shimodaira, 2006)] (Fig. 2). 153 154 155 Relative eye size 156 Cardinalfish species used for anatomical studies (n = 24, Table S1) were either collected on 157 the reefs surrounding Lizard Island between February 2015 and April 2017, or obtained through an 158 aquarium supplier (Cairns Marine Pty Ltd, Australia). Fishes from Lizard Island were collected on 159 SCUBA or snorkel using clove oil, hand nets and barrier nets, under the following permits: Great 160 Barrier Reef Marine Park Authority (GBRMPA) Permit G12/35005.1, GBRMPA Limited Impact 161 Permit UQ006/2014 and Queensland General Fisheries Permit 140763. After collection, animals 162 were returned to the lab and anaesthetized using a clove oil solution (10% clove oil, 40% ethanol, 163 50% sea water) before being euthanized by decapitation. 164 165 The standard length (SL) of each individual was measured, eyes were removed from the 166 socket and the horizontal eye diameter was measured to the nearest 0.1 mm using callipers. After 167 removal of the cornea, the lens was extracted and its diameter measured (Table S1). Species were 168 identified based on morphology and colouration and, where possible, subsequently confirmed via

169 RNA-sequencing andAuthor Manuscript by cross-referencing COI-sequences to public databases (boldsystems.org) 170 (Luehrmann et al., 2019). 171 172 Analyses were performed using base R (R Core team, 2014) and the CAPER package

173 (Orme, 2013). Relative eye size, lens diameter, eye diameter and standard length were log10

This article is protected by copyright. All rights reserved 174 transformed. As the ratio between lens diameter and eye diameter was highly proportionate 2 175 [phylogenetic least squares regression (PGLS), F1,21=367.9, r =0.94, p<0.001; Fig. 3a], further 176 comparative analyses were performed on eye diameters only. Relative eye size was calculated as

177 the ratio of log10 eye diameter to log10 standard length. As data was non-normally distributed 178 (Shapiro-Wilk, w=0.981, p=0.03), analysis of variance for the entire data set was performed using a 179 Kruskal-Wallis test. Differences between cardinalfish relative eye sizes on the genus level were 180 identified through post-hoc pairwise comparisons [Dunn-test; (Dunn, 1961)]. To account for 181 multiple comparisons, p-values were adjusted using a Bonferroni corrections (Table S2). Genera for 182 which three or fewer individuals were measured were omitted from the analysis (Table S1). 183 184 Retinal cell topography 185 In five cardinalfish species (see Figure S3), enucleated eyecups were fixed in 4% 186 paraformaldehyde (PFA) in 0.1 M Phosphate Buffered Saline (PBS) at room temperature for at least 187 24 hours, then stored at 4°C. Retinal wholemounts were prepared following the methods outlined in 188 Coimbra et al. (2006) and Ullmann et al. (2012). Few individuals were investigated in this study 189 due to the challenge in processing such small eyes using this method. However, previous studies (de 190 Busserolles et al., 2014a,b) have shown a low intraspecific variability in retinal topography in 191 fishes, and the analysis of two individuals of Ostorhinchus doederleini (Fig. S2), suggests low 192 intraspecific variability in cardinalfishes also. Using the stereological software StereoInvestigator 193 (Microbrightfield), topographic distribution of photoreceptors and ganglion cells was assessed using 194 the optical fractionator technique designed by West et al. (1991) and modified by Coimbra et al. 195 (2012). The counting frame and grid sizes were carefully chosen to maintain the highest level of 196 sampling and achieve an acceptable Schaeffer’s coefficient of error (CE <0.1; Glaser and Wilson, 197 1998; Slomianka and West, 2005) following the sampling protocols described in de Busserolles et 198 al. (2014a,b) (see Table S3 for a summary of counting parameters). For ganglion cell analysis, 199 displaced amacrine cells were included in the counts as they were difficult to distinguish from 200 ganglion cells based on morphological criteria alone. The inclusion of amacrine cells in the analysis 201 has previously been shown not to influence the overall topography of fish retinae (e.g. Collin and 202 Pettigrew, 1988c). Topographic maps were constructed using R v3.1.2 (R Core team, 2014) with 203 the results exported from StereoInvestigator according to Garza-Gisholt et al. (2014). The upper

204 limit spatial resolvingAuthor Manuscript power (SRP), expressed in cycles per degree (cpd), was estimated for each 205 individual using the ganglion cell peak density as described by Collin and Pettigrew (1989). Note 206 that, since amacrine cells were included in the ganglion cell counts, SRPs will be slightly 207 overestimated. 208

This article is protected by copyright. All rights reserved 209 Opsin gene expression, activity patterns and foraging mode 210 We used proportional opsin gene expression data from our previous work on 26 cardinalfish 211 species collected from the same locations (Luehrmann et al., 2019, Table S5). These included all of 212 the species used for microhabitat partitioning analysis (Table 1) and those for which relative eye 213 sizes and retinal topography maps were obtained (Tables S1, S3). We also characterised each 214 species as being nocturnally or diurnally active, and their foraging mode as exclusively 215 benthivorous, benthivorous and planktivorous, or exclusively planktivorous based on previously 216 published research (see Table S5 for references). 217 218 Phylogenetic comparative analyses 219 We tested whether the ecological parameters (microhabitat use, foraging mode, activity 220 period) correlated with visual system composition (relative eye size, proportional opsin gene 221 expression) of cardinalfishes using PGLS. For comparative analyses, we used the cardinalfish 222 phylogeny from Luehrmann et al. (2019). Each predictor was independently tested against each 223 dependent variable and no correlations between predictors were assessed due to different sample 224 sizes. To account for multiple testing, p-values were adjusted using Bonferroni corrections: for 225 eight tests each in the cases of proportional opsin gene expression versus microhabitat and foraging 226 mode, respectively; and for seven tests each in the cases of proportional opsin gene expression 227 versus activity period and versus relative eye size, respectively (Fig. 5, Tables S5, S6). Analyses 228 were performed in R version 3.1.2 (R Core team, 2014) using the CAPER package (Orme, 2013).

229

230 Results 231 Microhabitat distribution 232 We found marked variability in abundance and microhabitat distribution among different 233 cardinalfish species (Table 1; Fig. S1). Several species displayed microhabitat specialisations (e.g., 234 Rhabdamia gracilis, Nectamia savayensis, N. fusca, Taeniamia zosterophora, Zoramia leptacantha, 235 Ostorhinchus compressus), while others showed more generalist microhabitat preferences (e.g., 236 most Cheilodipterus and Ostorhinchus species) (Fig. S1). 237 238 Hierarchical cluster analysis revealed that cardinalfishes can be broadly classified into six Author Manuscript 239 habitat specialisation clusters (Fig. 2a), based on the microhabitat(s) they were most frequently 240 found in (Fig. 2b). Cluster 1 contained only R. gracilis, which was exclusively found away from, 241 but within 1-2 m of, the reef structure in midwater (microhabitat A; bootstrap, p<0.01). Cluster 2 242 contained species (Fibramia thermalis, Zoramia viridiventer) predominantly found in exposed

This article is protected by copyright. All rights reserved 243 locations either away from structure (microhabitat A) or close to structure (microhabitat B), e.g. 244 hovering above the tips of branching corals (p<0.01). Cluster 3 consisted of species of the genera 245 Taeniamia, Ostorhinchus, Cheilodipterus and Zoramia that were predominantly found in exposed 246 locations close to structures (microhabitat B), but that were rarely also found exposed and away 247 from structure (microhabitat A) or in cover (microhabitat C)(p<0.01). Cluster 4 consisted of species 248 (Ostorhinchus cookii, O. compressus and O. doederleini) that were predominantly found in cover, 249 either at the bottom of corals underneath branches, beneath rock ledges, or between the tips of 250 branching corals (microhabitat C, p<0.01). They were, however, easily spotted from outside. 251 Cluster 5 comprised species (Pristiapogon exostigma, O. nigrofasciatus) that were always hidden, 252 e.g. under ledges, between coral branches (microhabitat C), or inside caves (microhabitat D), where 253 they were sometimes hard to spot (p<0.05). Finally, cluster 6 comprised species (Nectamia 254 savayensis, N. fusca) found exclusively hidden inside the reef matrix, mostly deep inside branching 255 corals (microhabitat D, p<0.05). 256 257 Relative eye size 2 258 Eye diameter was proportional to body size (PGLS, F1,21=85.11, r =0.79, p<0.001), but 259 showed considerable variation between species (Kruskal-Wallis, χ2=116.434, df=10, p<0.001; Fig. 260 3, see Table S1 for an overview of morphometric measurements). Post-hoc pairwise comparisons of 261 relative eye size at the genus level furthermore revealed three distinct size categories in this family 262 (Fig. 3d, Table S2). Members of the genus Nectamia had the largest eyes relative to their body 263 sizes. Species of the genera Ostorhinchus, Cheilodipterus, Pristiapogon, Taeniamia and Zoramia, 264 on the other hand, had intermediate sized eyes, while showing greater variability. Ostorhinchus 265 species, in particular, showed a wide range of eye-diameter-to-standard-length ratios. Sphaeramia 266 nematoptera had consistently large eyes, but not statistically larger than Ostorhinchus (Dunn, z=- 267 2.121, p=0.036), Cheilodipterus (z=-1.04, p=0.2) and Taeniamia genera (z=2.103, p=0.035) due to 268 the broad range of eye sizes in these groups. R. gracilis had the smallest eyes overall, even when 269 compared to the Zoramia (z=-4.373, p<0.001) and Taeniamia (z=-4.628, p<0.001) species, which 270 had the second smallest relative eye sizes. Apogon crassiceps appeared to have even smaller eyes, 271 however, as only three specimens were sampled, this species was omitted from the analysis. In 272 summary, species that have intermediate sized eyes showed greater variability than species with

273 consistently large or smallAuthor Manuscript eyes (Fig. 3, Tables S1, S5). 274

275 Microhabitat partitioning correlated with relative eye size (PGLS, F5,11=7.66, p=0.02; Fig. 276 5a, Table S6). Relative eye size showed a positive correlation to decreased microhabitat exposure, 277 with R. gracilis (microhabitat A) having the smallest, and N. savayensis and N. fusca (microhabitat

This article is protected by copyright. All rights reserved 278 D) having the largest eyes. Interestingly, species occurring predominantly in both completely 279 hidden (microhabitat D) and partially hidden (microhabitat C) microhabitats (cluster 5), had 280 surprisingly small eyes (P. exostigma, O. nigrofasciatus; Fig. 5a). Relative eye size showed no 281 significant correlation to either activity period or foraging mode (Table S6). 282 283 Retinal neural cell topography 284 Topographic maps of ganglion cell densities revealed two specialization types, one 285 characterized by increased cell density in the central and temporo-ventral part of the retina (R. 286 gracilis, T. fucata), and one characterized by increased cell density in the central part of the retina 287 (area centralis), which extends into a weak horizontal streak (O. cyanosoma) (Fig. 4). 288 289 Photoreceptors were mostly arranged in a square mosaic pattern composed of one single 290 cone surrounded by four double cones. However, in some species, this pattern was not consistent 291 over the entire retina with some areas showing more irregular single cone patterns (Fig. S4). 292 Photoreceptor cell topographies differed between genera, and in one case between species of the 293 same genus (Ostorhinchus notatus differed from O. cyanosoma and O. doederleini; Fig. 4). 294 Topographic maps of total cone and double cone densities were nearly identical and revealed three 295 specialisation types (Fig. 4, Fig. S3): an area centralis (T. fucata); an increase in cell density in a 296 large area of the central and temporo-ventral part of the retina and extending into a weak horizontal 297 streak (O. notatus); and a pronounced horizontal streak with two areae centralis (O. cyanosoma and 298 O. doederleini). For those species for which both ganglion cells and photoreceptors were 299 investigated (T. fucata, O. cyanosoma), total photoreceptor cell distributions were similar to the 300 ganglion cell distributions. Single cone topography was noticeably different from double cone 301 topography in two species (T. fucata, O. notatus). These two species showed the highest proportion 302 of single cones of all species investigated and T. fucata had irregular single cone patterns (Fig. S4). 303 In T. fucata, single cone distribution showed two large areas of increased cell density in the nasal 304 and temporal part of the retina, while double cone distribution showed a single area centralis around 305 the optic nerve (Fig. 4). In O. notatus, single cone density was highest in the temporal region of the 306 retina, extending into a horizontal streak, whereas double cone density was highest in the temporo- 307 ventral part of the retina (Fig. 4).

308 Author Manuscript 309 No clear relationship between retinal topography and microhabitat use and/or activity 310 pattern could be identified. Species occupying the same microhabitat partition had very different 311 topographies (e.g. T. fucata and O. cyanosoma; Fig 4, Table S5) and species mainly differing in 312 activity pattern had similar topographies (e.g. O. cyanosoma and O. doederleini; Fig 4, Table S5).

This article is protected by copyright. All rights reserved 313 However, topography and foraging mode seemed to correlate, with pure planktivores having an area 314 temporo-centralis (R. gracilis, T. fucata), while generalists (i.e., benthic and pelagic feeders) 315 possessed streaks (O. cyanosoma, O. doederleini; Fig. 4, Table S5). Moreover, the type of 316 specialisation appeared to follow the phylogeny, with closely related species having similar retinal 317 topographies (Fig. S3). 318 319 Total cell numbers and densities of both ganglion cells and photoreceptors varied between 320 species, but appeared to be of similar order of magnitude (Table S4). Peak ganglion cell density 321 ranged from 8,289 cells/mm2 in T. fucata to 23,051 cells/mm2 in R. gracilis. However, spatial 322 resolving power was similar in the three species assessed, with an average of 7.6 cycles per degrees. 323 324 Opsin gene expression

325 We found that SWS2B (PGLS, F5,11=9.283, p=0.009), RH2A (F5,11=10.31, p=0.006) and

326 LWS (F5,11=11.17, p=0.004) cone opsin expression, and the rod-opsin to cone-opsin ratio

327 (F5,11=20.37, p<0.001) correlated with microhabitat partitioning (Fig. 5a, Tables S5, S6). LWS was 328 highly expressed in Nectamia species, and, at lower levels, in Fibramia, but in virtually no other 329 species. Therefore, LWS expression appeared to be high in species exclusively occupying hidden 330 microhabitats (microhabitat D). SWS2B, in contrast, was highly expressed in species exclusively 331 occupying exposed microhabitats (microhabitat A, R. gracilis; microhabitat B, Z. viridiventer). 332 RH2A, while expressed in all species, showed the highest expression (> 80% of double cone gene 333 expression) in species occupying in-between microhabitats (clusters 2 – 5). RH1 expression 334 correlated negatively with microhabitat exposure, and thus was lowest in R. gracilis, followed by F. 335 thermalis and Z. viridiventer. However, in all remaining species, RH1 expression was nearly 336 identical and accounted for > 90% of total opsin expression (Fig. 5a, Table S5). Activity period, 337 foraging mode and relative eye size were not significantly related to any opsin expression profiles 338 tested (Table S6). 339

340 Discussion 341 Our results show that microhabitat partitioning among different cardinalfish species 342 correlates with adaptations in their visual systems. We found that a reduction in relative eye size, 343 and therefore light sensitivity,Author Manuscript was present in species from exposed microhabitats compared to 344 species found hidden in the substrate. Opsin gene expression was also related to microhabitat use, 345 with exposed species expressing a shorter-wavelength-shifted and hidden species expressing a 346 longer-wavelength-shifted cone opsin palette, probably reflecting each microhabitat’s light 347 environment (Fig. 5c). As to whether microhabitat partitioning could also explain differences in This article is protected by copyright. All rights reserved 348 retinal neural cell topography, our results were inconclusive. Instead, a possible link between retinal 349 topography and foraging mode was identified. 350 351 However, these trends were driven mainly by the few species showing extreme forms of 352 adaptations to light conditions in microhabitats situated at the extreme ends of the light intensity 353 and colour spectrum (microhabitats A and D). Most other species fall somewhere in between, with 354 visual systems that seem suited to a broader colour and intensity range (see Figure 2). Since 355 selection pressure is expected to be relaxed under those conditions, phylogenetic inertia may play a 356 major role in shaping the visual systems in in-between cardinalfishes. This is also supported by the 357 strong phylogenetic signal (Pagel’s λ) when correlating relative eye size, SWS2B expression and 358 LWS expression with microhabitat (Table S6). 359 360 Microhabitat partitioning behaviour occurs in many animals due to resource competition, 361 such as for food, suitable mating sites, or shelter from predators (e.g., Ross, 1986). With few 362 exceptions, most cardinalfish species forage nocturnally and away from their diurnal refuge sites 363 (Barnett et al., 2006; Marnane and Bellwood, 2002). For these species partitioning at their diurnal 364 refuge sites is unlikely to be due to competition for food. An exception may be found in species 365 with high expression of violet opsin (SWS2B) that also occur in exposed microhabitats and feed 366 diurnally (R. gracilis). They may benefit from shorter-wavelength-shifted visual systems compared 367 to other species (Luehrmann et al., 2019) in feeding contexts in midwater microhabitats since UV- 368 sensitivity can aid planktivory (e.g. Flamarique, 2016). Moreover, lower expression of rod opsin 369 (RH1) in R. gracilis compared to other cardinalfish species (Luehrmann et al., 2019) may be a 370 reflection of their diurnal lifestyle, though an in-depth analysis of total cone and rod photoreceptor 371 numbers alongside the expression data would be needed to support this reasoning. Other 372 cardinalfish species are well adapted to dim-light through higher RH1 expression compared to 373 diurnal reef fishes (Luehrmann et al., 2019; Musilova et al., 2019; Stieb et al., 2016). However, 374 even among those nocturnally foraging cardinalfishes the repertoire of cone opsins they use is on 375 par with those of diurnal coral reef fishes (Luehrmann et al., 2019; Musilova et al., 2019). It 376 remains to be tested whether cardinalfishes are capable of dim-light colour vision which could 377 improve night time foraging efficiency, as reported from some gecko and anuran species (Kelber

378 and Roth, 2006). Author Manuscript 379 380 Cardinalfishes are heavily preyed on, making efficient defence mechanisms critical for their 381 survival (e.g., Beukers-Stewart and Jones, 2004). Consequently, competition for shelter may drive 382 microhabitat partitioning in this family, with those forced into the open needing to develop other

This article is protected by copyright. All rights reserved 383 means of protection. Indeed, several species generally found in microhabitats away from structure 384 (microhabitat A and B), such as R. gracilis, Z. viridiventer, T. zosterophora, or Z. leptacantha, are 385 of silvery-translucent or pale appearance, providing excellent camouflage when viewed against a 386 blue water background (Marshall and Johnsen, 2011; Marshall et al., 2018). These species also 387 form large schools, possibly further reducing predation risk (Pitcher, 1986). In contrast, species 388 found in more sheltered microhabitats, e.g., O. doederleini, O. cookii, O. compressus, or those 389 always hidden inside the reef matrix, e.g., N. savayensis, are darker in overall body colour, or like 390 most Ostorhinchus species, have dark horizontal stripes. These species are also often solitary or live 391 in smaller groups (Randall et al., 1990). Light inside caves and crevices on tropical coral reefs is 392 dim and red-shifted, the latter presumably caused by encrusting red-algae or other red-pigmented 393 encrusting organisms, like sponges (Fig. 5c, Marshall et al., 2003). Higher expression of LWS (red- 394 sensitive) opsin, along with a complete absence of SWS2B expression, particularly in Nectamia 395 species, may be an adaptation to the dim and/or red-shifted light conditions present in these 396 microhabitats. 397 398 A longer-term effect of visual adaptation to different microhabitat light spectra may be an 399 enhanced ability to recognize con- or heterospecifics under those lighting conditions, e.g., for 400 predator avoidance or mate choice. For example, many cardinalfish species considered ‘nocturnal’ 401 carry out courtship and mating behaviours at their resting sites during the day (reviewed in Vagelli, 402 2011). Mate colouration and visual co-adaptation may be important for sexual selection, as seen in 403 cichlid speciation (Terai et al., 2006; Seehausen et al., 2008). Colour or pattern based heterospecific 404 recognition, on the other hand, may be essential for the assortative aggregation behaviour of 405 cardinalfishes at their diurnal refuge sites (Gardiner and Jones, 2005; Greenfield and Johnson, 406 1990), or predator recognition. Indeed, most cardinalfish species are colourful and many sport stripe 407 patterns, as well as violet and/or UV-markings, which are visible through their relatively UV- 408 transparent ocular media and SWS photopigments (Marshall, 2000; Siebeck and Marshall, 2001). 409 However, unlike some reef fish (e.g., damselfishes) in which UV facial patterning can be slightly 410 different between males and females and even between individuals (Siebeck et al., 2010), 411 cardinalfishes do not exhibit sexual dimorphism. Males can only be distinguished from females by 412 their enlarged jaws when incubating eggs during breeding season (Barnett and Bellwood, 2005).

413 Author Manuscript 414 The relationship of eye sizes to habitat exposure and brightness found here, with species 415 occupying the most sheltered and dimmest microhabitats having the largest eyes and species 416 occupying the least sheltered and brightest microhabitats having the smallest eyes, is consistent 417 with previous studies in fishes (Schmitz and Wainwright, 2011), and confirm the importance of

This article is protected by copyright. All rights reserved 418 light availability as a driver of eye size evolution. However, some species (P. exostigma, O. 419 nigrofasciatus) found in both completely (microhabitat D) and partially hidden microhabitats 420 (microhabitat C) had surprisingly small eyes, suggesting that other factors, such as phylogeny 421 (Table S6, de Busserolles et al., 2013) or predation (Beston et al., 2017), may have influenced their 422 eye size evolution. 423 424 In fishes, the retinal topography usually reflects their habitat type, with visual streaks found 425 in species living in open environments with an uninterrupted view of the horizon, and areae 426 centralis found in species living in more enclosed environments (Terrain theory by Collin and 427 Pettigrew, 1988a; Collin and Pettigrew, 1988b; Hughes, 1977). Here, the lack of a relationship 428 between microhabitat type and retinal topography in cardinalfishes could be explained by several 429 factors: 1) we focused on the cone topography, but many of the species studied here are nocturnal 430 and therefore may rely more on their rod photoreceptors; 2) habitat partitioning in this study was 431 only assessed during the day and no data is available on habitat partitioning at night. Hence, it is 432 possible that a correlation between microhabitat partitioning and retinal topography exists, but that 433 it was missed due to different activity periods of species; 3) retinal topography in cardinalfishes 434 may carry a strong phylogenetic signal (Fig S3). A phylogenetic constraint in retinal topography 435 was first suggested in mammals (Stone 1983) and has since been observed in a number of animals, 436 including in deep-sea fishes (de Busserolles et al., 2014a); 4) instead of diurnal microhabitats, 437 retinal topography in cardinalfishes may be influenced by their feeding ecology. The streak in 438 benthivorous/plantivorous species may allow them to scan a broad area of the sand-water interface, 439 providing high acuity while minimising eye movements (Collin and Pettigrew, 1988b). On the other 440 hand, a higher density of cells in the temporo-ventral part of the retina in obligate planktivores may 441 provide higher acuity to distinguish prey situated in front and above in the water column (Collin 442 and Pettigrew, 1988a; de Busserolles et al., 2014a). 443 444 Conclusion 445 Our findings suggest that microhabitat partitioning is factor contributing to visual system 446 diversification in cardinalfishes, specifically those adapted to extreme microhabitats, whereas many 447 show visual systems suited to broader microhabitat conditions. The colour vision of these nocturnal

448 foragers is presumablyAuthor Manuscript linked to daytime activities in and around coral heads and the close-set 449 nature of these social and other activities may in particular drive this site-system co-adaptation. 450 While there remains much to learn around the colours and their use in these engaging fish, our 451 findings indicate that the availability of diverse microhabitats contributes to evolutionary sensory

This article is protected by copyright. All rights reserved 452 diversification among diverse ecosystems, such as tropical coral reefs, and perhaps in similar ways 453 in terrestrial systems. 454 455 Authors’ contributions

456 ML, FC, KLC, FdB, NJM conceived the ideas and designed the methodology; ML and FC collected 457 the data; ML analysed the data; ML led the writing of the manuscript; all authors contributed 458 critically to the drafts and gave final approval for publication.

459 460 Acknowledgements 461 We thank the staff at Lizard Island Research Station for support during field work and Cairns 462 Marine Pty Ltd for sourcing and supplying additional fish. This work was supported by an 463 Australian Research Council Discovery Project (DP150102710) awarded to KLC and JM, an ARC 464 Laureate Fellowship (FL140100197) to JM, a UQ Development Fellowship to FC, and FdB was 465 funded by an ARC DECRA (DE180100949). 466 467 Data Accessibility 468 All data is provided either in the main manuscript, the supplementary material, or is available 469 through publications cited accordingly, as well as through Dryad 470 (https://doi.org/10.5061/dryad.3xsj3txbr). 471 472 References 473 Barnett, A. and Bellwood, D. R. D. (2005). Sexual dimorphism in the buccal cavity of paternal 474 mouthbrooding cardinalfishes (Pisces: Apogonidae). Mar. Biol. 148, 205–212. 475 Barnett, A., Bellwood, D. R. and Hoey, A. S. (2006). Trophic ecomorphology of cardinalfish. 476 Mar. Ecol. Prog. Ser. 322, 249–257. 477 Beston, S. M., Wostl, E. and Walsh, M. R. (2017). The evolution of vertebrate eye size across an 478 environmental gradient: phenotype does not predict genotype in a Trinidadian killifish. 479 Evolution (N. Y). 71, 2037–2049. 480 Beukers-Stewart, B. . and Jones, G. . (2004). The influence of prey abundance on the feeding

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This article is protected by copyright. All rights reserved 639 TABLE 1. Summary of cardinalfish species sampled in microhabitat assessment. n = total 640 individuals counted across all sampling sites and locations. N = number of sampling sites at 641 which each species was found. 642 Species Individuals (n) Sites (N) Apogon crassiceps* 3 3 Apogonichthyoides melas* 2 2 Cheilodipterus artus 227 19 Cheilodipterus macrodon 18 7 Cheilodipterus quinquelineatus 1800 57 Fibramia thermalis 65 3 Nectamia fusca 35 3 Nectamia savayensis 50 6 Nectamia viria* 10 1 Ostorhinchus compressus 104 14 Ostorhinchus cookii 44 11 Ostorhinchus cyanosoma 2247 50 Ostorhinchus doederleini 235 24 Ostorhinchus nigrofasciatus 52 29 Ostorhinchus novemfasciatus* 3 2 Pristiapogon exostigma 44 11 Pristiapogon kallopterus* 9 3 Pterapogon cf. mirifica* 2 2 Rhabdamia gracilis 1410 6 Taeniamia fucata 2811 13 Taeniamia zosterophora 75 3 Zoramia viridiventer 4835 15 Zoramia leptacantha 510 6 643 * Omitted from microhabitat partitioning analysis 644 FIGURE 1. Sampling location and microhabitat assessment. (a) Location of the field site 645 relative to the Australian mainland. (b) Overview of the sampling locations (grey circles) 646 around Lizard Island, Queensland, Australia. (c) Schematic of microhabitat classification 647 used for partitioning assessments. Microhabitat A: fully exposed, 1 m above or next to 648 structure (coral head, coral outcrop, boulder); microhabitat B: fully exposed, directly above Author Manuscript 649 or adjacent to structure; microhabitat C: semi-hidden (visible from outside), between coral 650 branches, in crevices, under overhangs or ledges; microhabitat D: entirely hidden (not visible 651 from outside), inside coral outcrops, deep inside crevice/cave structures.

This article is protected by copyright. All rights reserved 652 653 654 FIGURE 2. (a) Clustering (1-6) of microhabitat counts across the four different microhabitat 655 categories (A – D) using a Ward.D2 cluster analysis. Different microhabitat partition clusters 656 are indicated by numbers 1 – 6. Significance levels of bootstrap analysis are designated by: 657 ** = p<0.01, * = p<0.05. (b) Mean (± SD) microhabitat (A – D: A, fully exposed away from 658 structure; B, fully exposed adjacent to structure; C, semi-hidden; D, entirely hidden) 659 distribution of species comprised in each identified cluster (1 – 6). 660 Author Manuscript

663 relative eye size inAuthor Manuscript three cardinalfish species, from left to right: Sava Cardinalfish (Nectamia 664 savayensis); Cook’s cardinalfish (Ostorhinchus cookii); Luminous cardinalfish (Rhabdamia 665 gracilis). Relationships of (b) horizontal eye diameter and lens diameter, and (c) eye diameter 666 and standard length. Fitted lines represent the phylogenetically corrected linear regressions

This article is protected by copyright. All rights reserved 667 using PGLS. (d) Comparison of relative eye size by genus as per Mabuchi et al. (2014). 668 Different letters indicate significant differences based on Dunn’s post-hoc tests. Genera 669 without letters were excluded from the analysis (see Table S1). 670

671 Author Manuscript v 672 FIGURE 4. Topographic distribution of retinal neural cells in different cardinalfish species. 673 (a) Ganglion cells (GC), (b) photoreceptors (total cone TC, double cone DC, and single cone 674 SC). For two species, both ganglion and photoreceptors cells have been mapped. Black lines

This article is protected by copyright. All rights reserved 675 represent isodensity contours and values are expressed in densities x 103 cells/mm2. Arrows 676 indicate the orientation of the retinas: V = ventral, T = temporal. Scale bars = 1 mm. 677 (a) T GC

3.6 4 4 9 3.9 4 5 10 4.2 5 10 11 10 9 3.6 6 4.5 7 1 11 4 13 12 4.8 6 9 11 1 15 10 6 5 11 V 13 12 4.2 6 12 5 17 1 14 1 5.4 4 18 5.1 5.1 6 13 18 19 4.5 4 .4 8 1 17 9 20 5 4. 1 6 8 4.8 1 20 7 3 6.3 6.3 8 1 5.7 9 6 12 16 5.7 3.9 5.4 10 11 1 5.4 8 3 1 17 18 1 6 5.1 5 9 13 1 8 4 7 4 7 4.5 8 12 12 1 .8 1 4.2 5.7 1 1 6 1 2 6 7 1 7 7 1 3.6 8 6.3 6 6 6 18 1 1 4.2 4.5 10 12 14 16 18 20 3.9 5 4 6 8 10 12 14 8 4.8 1 3.5 4 4.5 5 5.5 6 6.5 1 10 R. gracilis T. fucata O. cyanosoma

(b) TC DC SC

1 .6 5 5.5 1.4 1.8 3.6 1.6 2 6 3.6 2.4 2.2 5.5 2 6 6 .2 1.8 7 .5 4 2.8 6.5 .4 2.4 2.2 3.6 5 6 9 3.6 2.6 3.2 7.2 2.8 10 .8 3.4 6.5 7 3.2

7.8 4.2 3.6 3 9.5 7 7.5 4 6.6 4.8 7.5 .8 8.5 .2 5.4 .4 2 7.5 8 8 3 3 2.6 7 5.4 6 3 2.2 2 2.4 4.2 .2 2.2 6.5 2 1.8 4.8 2.4 7 4.8 2 6.5 2 2 8 1.6 1.6 7.5 7.5 1. 4.8 5.4 1.4 1.8 6 7.5 1.5 2 2.5 3 3.5 6.5 5.4 3 4 5 6 7 8 1.6

7 5 6 7 8 9 10

5.5 2.4

6 2 2 2 7.5 8 2. 2 2.2 5.5 .4 8 8.5 2.6 9 6.5 2.8 6 10 9.5 3 11 10.5 7 7.5 3 11.5 7 8 12 . 8.5 5 2.8 3. 9 2.6 8 10 3.4 13 9.5 2.4 7.5 3.2 3 9.5 1 1 1 2 0 3 2. 4 9 6 .5 12.5 2.8

1 2 2. 1 12 2 2 2.6 .5 .4 3.6 7.5 11.5 3.4 2 .5 2 .2 0 . 1 8.5 2 0

O. notatus fucata T. 8.5 1 7 8 3.2 9 2 1 12 9 9.5 2 .4 1 9 12.5 10 8

. .

5 1 1 2 3 0. 2 3 13.5 5 . 9 5 1 2 2 . 11 1 4 3 6 7 8 9 10 11

1 8 9 10 11 12 13 14 2.2 2 2.5 3 3.5 4

1 5.6 4.5 1.4 6.3 5 1.2 1.4 7 1.6 5.5 1.4 1.8 5.6 7.7 8.4 4.5 6 6.5 9.1 7 2 2.2 6.3 9.8 5 7.5 2 5.5 1.4 2.4 7 7 9.8 10.5 11.2 5.5 7.5 8 2.4 9 1.8 2.8 7.7 11.2 6 8.5 1.6 2.6

2 6 8.4 .1 6.5 2. . 9 2 7 3 11.9 3 12.6 9.5 2.6 2.8 11.9 9 2.6 7.5 10.5 9.8 2.6 2.2 10.5 7 2.4 8.5 8 7.5 9.1 9 9.8 8 1.8 .1 6.5 7 1.8 2 9.1 7 .5 2.4 1. 8.4 7.5 2.2 6 8.4 6 6 6.5 1.4 7.7 8.4 2 5.5 7 1.8 7.7 6 1.6 O. cyanosoma 7 5 6 7.6 8 9 7 5 6.5 1 1.2 7 5.5 1.4 .7 6 7 8 9 10 11 12 6.3 5 1.2 .4 1 1 1.5 2 2.5 3

4.8 4. 0.8 4.8 2 4.8 5.6 5.6 0.8 5.4 6.4 6.4 5.4 1 1 6.4 7.2 1.2 5.4 6.6 1.2 1 7.2 8 6 7 6 1.4 8 8.8 6.6 8 .2 1.4 8 7.2 7. 1.6 1.6 .8 9.6 10.4 9.6 11.2 7.8 8.4 9 1.8 2 2 10.4 11.2 11 8.4 1.8 .2 9.6 10 2.2 12.8 12.8 9 .2 2.2 2.4 10.8 2.8

12 2.4 2 13.6 10.8 2 2 1 . . 0.2 9 2 11.2 1 9.6 9 2.2

Author Manuscript 1 9 9 7.8 2 2.6 8.4 1.8 10.4 12 9.6

9.6 2 11.2 6 1.8 .

7 2 7 .2 8.8 7.8

4 8 . 8.8 10. 7 .4 2 .2 1.6 9.6 .2 7.8 8.8 8 8.8 7 6.6 7.2 2 6 1.6 8 8 6. 6 6.6 1.4 1.4 7.2 6 8 10 12 14 1 1.5 2 2.5 O. doederleini 1.2 678 4 5 6 7 8 9 10 11

This article is protected by copyright. All rights reserved 679 FIGURE 5. Phylogenetic comparative analysis (PGLS) of cardinalfish visual system characteristics 680 in relation to ecological parameters and visual system specialisations. (a) Proportional opsin gene 681 expression and relative eye size in cardinalfishes categorised by microhabitat partitioning clusters. 682 Bonferroni adjusted p-values are shown where: * < 0.05, ** < 0.01, *** < 0.001. (b) Cardinalfish 683 phylogeny used for PGLS analysis (see Luehrmann et al., 2019). Asterisks indicate species used 684 and spheres indicate maximum likelihood support values. (c) Light environment in different 685 microhabitats on coral reefs at Kaneohe Bay, Hawaii (after Marshall et al., 2003). Orange line, light 686 inside a cave 1 m recessed. Blue line, light on the reef outside the cave. Measurements in relative 687 photons/sr/nm. Author Manuscript

688

Lizard Island B (14°40′S, 145°27′E) Great Barrier Reef C Australia Australia A B C D

This article is protected by copyright. All rights Author Manuscript reserved C C

1 km (a) N. savayensis fec_13529_f2.pdf N. fusca 6 * O. nigrofasciatus

P. exostigma 5

** O. doederleini

C. macrodon

O. compressus ns

O. cookii 4

Z. leptacantha

T. zosterophora

O. cyanosoma

C. quinquelineatus

C. artus ** T. fucata 3 More More exposed More hidden Z. viridiventer **

F. thermalis 2

R. gracilis 1

2.0 1.0 0.0 Euclidean distance (b)

1.0 0.8 1 2 3 0.6

Frequency of occurrence (%) Frequency of occurrence A BC D ABCD ABCD Microhabitat category Relative eye size (d) Log eye diameter (mm) (b) (a) 0.35 0.40 0.45 0.50 0.55 0.5 0.6 0.7 0.8 0.9 1.0 . . . . 0.6 0.5 0.4 0.3 0.2 Rhabdamia gracilis Rhabdamia Apogon Log lens diameter lens (mm) Log moreexposed This article is protected by copyright. All rights b,c Ostorhinchus

Authora,b,c Manuscript Cheilodipterus

Fowleria R fec_13529_f3.pdf Ostorhinchus cookii Ostorhinchus 2 = 0.94= Fibramia (c) Nectamia a . . . . 1.9 1.8 1.7 1.6 1.5 Pristiapogon b Log standard length (mm) length standard Log reserved Rhabdamia z morehidden b,c Taeniamia Nectamiafusca

Zoramia b R 2 =0.79 Sphaeramia a,c 10mm (b) (a) O. doederleini O. cyanosoma O. notatus T. fucata V

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1 1 8 2 2 6 . 2

1 1.5 2 2.5 1 1.5 2 2.5 3 2 2.5 3 3.5 4 1.5 2 2.5 3 3.5 4 6 8 10 12 14 Proportional opsin gene expression (%) (a) 0 20 40 60 80 100 020 40 60 80 100 020 40 60 80 100 00 20 40 60 80 100 R p(adj) = <0.001***= p(adj) SWS2B H Eyesize RH1 SWS2Aβ SWS2Aα R p(adj) = 0.313= p(adj) 2 2 = 0.858= = 0.438= 6 5 4 3 2 1 p(adj) = 0.675= p(adj) R 2 cluster = 0.337= R p(adj) = 0.009**= p(adj) 2 = 0.721= This article is protected by copyright. All rights Author Manuscript Relative eye size 0.40 0.50 RH2A RH2B R p(adj) = 0.006**= p(adj) LWS 2 = 0.744= 6 5 4 3 2 1 cluster fec_13529_f5.pdf R p(adj) = 0.004**= p(adj) 2 p(adj) = 0.198= p(adj) R R p(adj) = 0.02*= p(adj) = 0.761= 2 2 = 0.489= = 0.676= (b) (c) normalised intensity

(photons/sr/nm) 0.2 0.1 0 0 0 0 0 700 600 500 400 300 Kurtus gulliveri Kurtus reserved column water cave Nectamiasavayensis* Nectamiaviria Wavelength (nm) Wavelength Apogonichthyoides melas* Apogonichthyoides Nectamiabandanensis Pristiapogon exostigma* Pristiapogon Ostorhinchus doederleini* Ostorhinchus Ostorhinchus compressus* Ostorhinchus Ostorhinchus notatus* Ostorhinchus Cheilodipterus quinquelineatus* Cheilodipterus p > 95%> p Cheilodipterus macrodon* Cheilodipterus Sphaeramianematoptera* Ostorhinchus nigrofasciatus* Ostorhinchus Ostorhinchus novemfasciatus* Ostorhinchus Cheilodipterus artus* Cheilodipterus Ostorhinchus angustatus* Ostorhinchus Taeniamia fucata*Taeniamia Taeniamia zosterophora*Taeniamia Nectamiafusca* 0.3 Apogonichthyoides brevicaudatus Apogonichthyoides Pterapogon cf. mirifica* cf. Pterapogon p > 80%> p Fibramia thermalis* Fibramia Zoramia viridiventer*Zoramia Ostorhinchus holotaenia Ostorhinchus Ostorhinchus cyanosoma* Ostorhinchus Rhabdamia gracilis*Rhabdamia Pristiapogon fraenatus* Pristiapogon Ostorhinchus cookii* Ostorhinchus Apogon crassiceps* Apogon Zoramia leptacanthav*Zoramia Fowleria variegata* Fowleria

0 1.0 0.5

(photons/sr/nm) normalised intensity normalised