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Is Diet Correlated with Feeding Morphology in Neotropical Armoured (Siluriformes: )?

by

Stéphanie L. Lefebvre

A thesis submitted in conformity with the requirements for the degree of Masters of Science Ecology and Evolutionary Biology University of Toronto

© Copyright by Stephanie L. Lefebvre 2014

Is Diet Correlated with Feeding Morphology in Neotropical Suckermouth Armoured Catfishes (Siluriformes: Loricariidae)?

Stéphanie L. Lefebvre

Masters of Science

Ecology and Evolutionary Biology University of Toronto

2014 Abstract

The suckermouth armoured catfishes (Siluriformes: Loricariidae) are a diverse group of predominantly detritivorous inhabiting rivers of South and Central America. Their distinct jaws are specialized for scraping a wide range of substrate. Though it is hypothesized that specialization of loricariid feeding morphology may have played a role in their diversification, little is known about the ecological and evolutionary processes involved. The present study quantifies variation in jaw functional traits and body morphology in a phylogenetic context.

Morphological variation was compared to ’ relative position in assemblage isotope space

(for both δ13C and δ15N) to test for correlations between diet and feeding morphology. Results show that although jaw functional traits are decoupled from body morphology, both are correlated with δ13C values. Partitioning of terrestrial and aquatic resources can be explained by both jaw functional traits and body morphology, however further partitioning of diet is only attributed to the former.

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Acknowledgements

I would like to thank Nathan K. Lujan for providing isotope and jaw data, along with a wealth of information about loricariids, and for organizing the provision of specimens from both the Auburn University Museum Collection (AUM) and the Academy of Natural Sciences of Philadelphia (ANSP). I am deeply grateful to my supervisors, Hernán López-Fernández and Nathan Lovejoy, for guidance, insight, and funding. My supervisory committee members, Jason Weir and Don Jackson, for helpful discussion and guidance. The curators of the fish collections at their respective institutions for allowing me to dissect their specimens – Jon Armbruster (AUM), Mark Sabaj Pérez (ANSP), and Hernán López-Fernández (ROM). I am indebted to Sarah Steele for being a great sounding board to my crazy ideas, for providing the outline to Figure 4 (Methods, section 1.2.6), and for always being there for support. Finally, I’d like to thank the López-Fernández lab members for all the discussions, insight, R code help, and laughs along the way. You guys are awesome.

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Table of Contents

Acknowledgements ...... iii

Table of Contents ...... iv

List of Tables ...... vi

List of Figures ...... vii

List of Appendices ...... viii

1.1 Introduction ...... 1

1.2 Methods ...... 4

1.2.1 Samples ...... 4

1.2.2 Jaw Dissection and Preparation ...... 4

1.2.3 Imaging ...... 5

1.2.4 Jaw Parameters ...... 6

1.2.5 Jaw Functional Traits ...... 7

1.2.6 Body Morphology ...... 8

1.2.7 Phylogenetic Corrections ...... 10

1.2.8 Diet Information ...... 12

1.2.8.1 Diet Categories ...... 12

1.2.8.2 Stable Isotope Analysis ...... 13

1.3 Results ...... 14

1.3.1 Significant Principal Components Test ...... 14

1.3.2 Jaw Functional Traits Analyses ...... 15

1.3.3 Body Morphology Analysis ...... 18

1.3.4 Diet-Morphology Correlations ...... 21 iv

1.4 Discussion ...... 23

1.4.1 Jaw Functional Traits Analyses ...... 23

1.4.2 Body Morphology Analysis ...... 24

1.4.3 Diet Groups ...... 24

1.4.3.1 Scrapers (Gray) ...... 24

1.4.3.2 Wood-Eaters (Purple) ...... 25

1.4.3.3 Insect and Mollusk Eaters (Pink) ...... 26

1.4.3.4 Aufwuch Eaters (Yellow) ...... 27

1.4.4 Habitat Use ...... 28

1.4.5 Diet-Morphology Correlations ...... 29

1.4.5.1 Relationship Between δ13C and Jaw Functional Traits ...... 29

1.4.5.2 Relationship Between δ13C and Body Morphology ...... 30

1.4.5.3 Implications of Diet-Morphology Correlations in Loricariids ...... 30

1.5 Conclusions ...... 31

References ...... 33

Appendix A ...... 39

Appendix B ...... 45

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List of Tables

Table 1. Parameters quantifying morphological variation in loricariid mandibles ...... 6

Table 2. Morphological variables used to quantify aspects of body size and shape in loricariids. 9

Table 3. Diet information identified for a subset of loricariids in this study, based on references to diet in literature...... 12

Table 4. Species abbreviations used in all analyses...... 15

Table 5. Principal components analysis eigenvectors for jaw functional traits and body morphology...... 16

Table 6. Results of PGLS regressions using centroid deviations of δ13C and δ15N against residuals of the first two principal components of the jaw functional traits (f) and body morphology (b) ...... 21

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List of Figures

Figure 1. Representative sample of lower jaws from Loricariidae examined in this study showcasing morphological diversity in the ...... 2

Figure 2. Orientation of lower jaw ramus of hemiurus...... 5

Figure 3. Mandible of Hypostomus macushi illustrating parameters used in this study, as defined in Table 1...... 7

Figure 4. Visual representation of body measurements used to evaluate size and shape differences in the present study...... 10

Figure 5. Multi-locus molecular phylogeny of a subset of loricariids, sequenced by Lujan et al. (unpublished data)...... 11

Figure 6. PC axis significance test for jaw functional traits analysis...... 14

Figure 7. Graphic representation of the first two principal components of jaw functional traits of a phylogenetically-corrected PCA, by means of morphospace (upper panel) and phylomorphospace (lower panel)...... 17

Figure 8. Graphic representation of the first two principal components of body morphology of a phylogenetically-corrected PCA, by means of morphospace (upper panel) and phylomorphospace (lower panel)...... 20

Figure 9. Estimate of concentration of δ13C as a function of jaw functional traits...... 22

Figure 10. Estimate of concentration of δ13C as a function of body morphology...... 23

Figure 11. Despite their different body shapes, head morphology appears convergent in representatives of and ...... 25

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List of Appendices

Appendix A List of species prepared for this study, as well as catalogue numbers of the institutions from which they came ...... 39

Appendix B Species used in the stable isotope analyses...... 45

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1.1 Introduction

The suckermouth armoured catfishes (Siluriformes: Loricariidae) are a taxonomically diverse group of benthic fish inhabiting rivers of South and Central America. With over 900 known species, loricariids are the most species-rich family of catfishes (Eschmeyer and Fricke, 2011). Loricariids are characterized by a dorsoventrally depressed body covered in ossified dermal plates instead of scales, and their mouths are ventrally positioned as an oral disk. This positioning of the mouth allows these fishes to attach to the substrate, which facilitates their scraping mode of feeding. This suckermouth-scraping mode has evolved independently in Neotropical and African Mochokidae from generalized benthic suction feeders (Van Wassenbergh et al. 2008). Loricariid teeth are also ventrally oriented and their flexibility is unique among vertebrates (Geerinckx et al. 2012). The upper jaws, which are composed of two tightly linked premaxillae, are highly protrusible and move independently of the lower jaws. Each ramus of the lower jaw is medially decoupled, allowing them to also move independently from each other (and the upper jaw) while scraping (Geerinckx et al. 2009; Adriaens et al. 2009).

Lujan and Armbruster (2012) measured aspects of jaw morphology and proposed a biomechanical model to predict how morphological variation is linked with functional diversity in loricariids. The present study includes 48 species (27 genera), and incorporates the functional traits established by Lujan and Armbruster (2012) in order to explore loricariid jaw diversity in a phylogenetic context. The phylogeny used is a subset of a newly established molecular phylogeny of the Loricariidae in preparation by Lujan et al (unpublished data).

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Figure 1. Representative sample of lower jaws from Loricariidae examined in this study showcasing morphological diversity in the family. A) xanthellus, B) scaphiryncha, C) furunculus, D) Hypostomus macushi, E) fallax, F) triactis, G) Chaetostoma sp. Xingu, H) lithoides, I) pariolispos, J) monopelte

In the present study, jaw morphological data were combined with dietary (isotope) data in order to explore potential links between trophic niche and feeding morphology. A link between diet and feeding morphology would be especially interesting in loricariids because despite their diverse jaws, they predominantly feed on (dead organic matter) or algae. Increasingly, studies are linking these diet and jaw morphology in Neotropical fishes (Fugi et al. 2001; Novakowski et al, 2004; López-Fernández et al. 2012; Montana and Winemiller, 2013), but most studies focus on predators (piscivores or insectivores), for which prey items are discrete and taxonomically distinguishable to the eye. Such diet discrimination is near impossible for since their stomach contents are often homogenous and undiscernible (Hood et al. 2006; Lujan et al. 2011). This may account for the lack of research focusing on Loricariidae, despite the fact that it is one of the most diverse families of Neotropical freshwater fish, second only to Characidae (Reis et al, 2003). The few studies exploring diet-morphology correlations in loricariids tend to focus on intestinal morphology (Kramer and Bryant, 1995; Delariva and Agostinho, 2001; German et al. 2010), although limited studies of wood-eating loricariids have linked jaw morphology to both gut contents and isotopically defined diet patterns in a non- phylogenetically explicit manner (Armbruster 2003; Nogonaki et al. 2007; Lujan et al. 2011). Dietary information for this study is based on stable isotope data from Lujan et al (2012). Isotopes can give insight into dietary intake averages over time, and are especially useful in detritivores, where the maceration and fast uptake of food results in traditional stomach content

3 analyses not being suitable for discerning individual food items in the gut. The majority of loricariids’ diet consists of a combination of algae and detritus, with occasional ingestion of macroscopic plant matter, insects and mollusks (Lujan et al. 2012).

Stable isotope analyses quantify the ratio between naturally occurring isotopes of an element (typically C and N in diet studies). Since one isotope has more neutrons they differ in atomic mass, with the heavier of the two isotopes being the most stable. For isotopic trophic studies, the ratio of these isotopes is measured and compared with a standardized measurement for that element – if the ratio of heavy to light element is higher than that of the standard, the sample is said to be enriched (Ben-David and Flaherty, 2012). A ratio lower than the standard for that element is considered depleted. In their analysis, Lujan et al. (2012) used the ratios between 13C and 12C, as well as the ratios between 15N and 14N to infer dietary discrimination among sympatric loricariids.

δ13C signatures in freshwater ecosystems vary largely in response to sources of dissolved organic carbon. Values from algae may be upwards of 25‰ higher than those of dissolved inorganic carbon, such as calcite, for example (Peterson and Fry, 1987). However, δ13C values do not vary significantly between trophic levels and can therefore be used to infer the relative contribution of different primary producers in the ecosystem to a consumer’s biomass (Peterson and Fry 1987; Ben-David and Flaherty, 2012). For example, ratios of δ13C can help differentiate between autochthonous (aquatic) and allochthonous (terrestrial) sources of carbon (Peterson and Fry 1987), and previous studies used δ13C values to determine that wood-eating loricariids ( group, as well as species of and ) have a different δ13C signal than those that strictly rely on autochthonous carbon sources (Nogonaki et al. 2007; German and Miles, 2010; Lujan et al. 2012).

δ15N signatures can be used to infer trophic level since 15N is enriched along the chain of consumers. Of the two naturally occurring forms of nitrogen, biochemical reactions responsible for the assimilation amino acids and proteins prefer the heavier and rarer 15N. For most organisms, this enrichment of 15N increases by 3 to 5‰ with each successive trophic level (Minagawa and Wada 1984). It is important to note that as loricariids occupy the same trophic level (German and Miles, 2010), the difference in values of δ15N in this study are expected to be minimal. However, these values will still be biologically relevant and may give insight into both

4 the proportion of protein in the diet (Kelly and del Rio, 2010), and niche partitioning of resources (Layman et al. 2007).

In this study, I will first quantify variation in both jaw functional traits and body morphology in a phylogenetic context. Second, I will test for correlations between jaw functional traits and diet (based on assemblage standardized variation in δ13C and δ15N stable isotope data), as well as body morphology and diet. Links between diet and either jaw function or body morphology would suggest that these features can predict ecological traits. This, in turn, would support an adaptive relationship between phenotype and feeding behavior in loricariids.

1.2 Methods

1.2.1 Samples

This study examined 166 specimens representing 48 species and 27 genera of loricariids. Data on 66 specimens (14 species, 9 genera) were provided by Lujan and Armbruster (2012), and novel data on 100 specimens (34 species, 18 genera) were gathered for this study. New specimens examined were provided by the Auburn University Museum Fish Collection (n=85), the Royal Ontario Museum (n=8), and the Academy of Natural Science of Philadelphia (n=7). Only adult specimens were included in order to reduce confounding effects of allometric changes during ontogeny on the dataset. See Appendix A for the list of specimens used in this study, including geographical information regarding where each sample was collected.

1.2.2 Jaw Dissection and Preparation

For each specimen, both the right premaxilla and right mandible were dissected, and individually treated following the Maceration and Staining of Jaw Bones protocol used by Lujan and Armbruster (2012). This protocol aims to remove all soft tissue while keeping bones, ligaments, and teeth intact, and prepares the jaws to be photographed. Following dissection, jaw elements were dehydrated in individual vials containing 95% ethanol. After at least 24 hours, ethanol was replaced with a solution of 1% KOH and 0.5% alizarin red. KOH macerates soft tissue surrounding the bone, while alizarin red stains ossified structures to highlight details on the surface of the bone. Jaws were kept in the KOH-alizarin solution for 3 days, after which they were returned to 95% ethanol for 24 hours. Any remaining soft tissue was then easily removed using forceps, and the newly exposed bones were left to air dry. This protocol was modified

5 slightly with either small or large jaws by adjusting time spent in each solution accordingly. The smallest jaws were given special attention since too much time spent in 1.0 % KOH would weaken the cartilage and ligaments that bind the dentary to the anguloarticular, and the jaw would separate in two pieces.

1.2.3 Imaging

Digital images of each mandible were taken with a Nikon D100 digital camera mounted on a Zeiss Stemi SV8 stereomicroscope using Camera Control Pro 2 software. Images were taken in at least 2 of the 3 perspectives outlined by Lujan and Armbruster (2012), with most species being photographed in all 3 perspectives (see Figure 2). These perspectives maximize homology and ensure that all jaw regions could be observed in a standardized way using the angular complex as a reference point (Lujan and Armbruster, 2012). The angular complex is parallel to the field of view in both the ventral-horizontal and dorsal-horizontal perspectives, while the vertical-dorsal perspective features the angular complex perpendicular to the field of view. Certain jaws have a morphology that allows all of the linear measurements to be clearly seen in two perspectives, while others are shaped in a way that requires all three perspectives in order to measure all of the parameters in this study. Five linear measurements and one surface area measurement were taken digitally in ImageJ (Rasband 1997), with each image scaled using the established distances of the graph paper used as a background for each image. The premaxilla was neither photographed nor included in analyses because homology and functional relevance of all structures could not be ensured.

Figure 2. Orientation of lower jaw ramus of Hypostomus hemiurus. The orientation is shown in each plane, ventral-horizontal (A), vertical-dorsal (B), and horizontal-dorsal (C), as outlined in Lujan and Armbruster (2012).

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1.2.4 Jaw Parameters

Six measurements were taken for each mandible in accordance with Lujan and Armbruster (2012)’s protocol (see Table 1 and Figure 3). Of these, three are analogous to the input and output lever arms that are standard measurements of feeding biomechanics (Westneat, 2004), while the remaining three are loricariid-specific and were established by Lujan and Armbruster (2012). For clarity, these measurements will henceforth be referred to as parameters throughout the text. These parameters are used for the calculation of jaw functional traits, described below in section 1.2.5.

Table 1. Parameters quantifying morphological variation in loricariid mandibles. It should be noted that the output lever arm is only measured once in traditional feeding biomechanics studies (Westneat 2004), whereas it involves two components in loricariids due to the ventral orientation of their mandible.

Parameters Definition Measurement Traditional (Westneat, 2004) Distance between the center of the area of insertion of the adductor In Input lever arm mandibulae muscle and the anguloarticular condyle

Distance between the anguloarticular condyle and the Out Output lever arm prox tooth closest to the condyle

Distance between the Outdist Output lever arm anguloarticular condyle and the tooth furthest to the condyle Loricariid Specific (Lujan and Armbruster 2012) Distance of the proximal to the TRL Tooth row length distalmost tooth insertions

Perpendicular distance between Variation in height of the coronoid the coronoid arch and the line H1 arch relative to the distal-most formed by the Outdist tooth measurement

Area of insertion of the adductor Area of insertion of the adductor AM area mandibulae muscle mandibulae muscle

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Figure 3. Mandible of Hypostomus macushi illustrating parameters used in this study, as defined in Table 1. Measurements were taken in multiple perspectives, not necessarily the one shown in this figure.

1.2.5 Jaw Functional Traits

The jaw parameters described above were used to calculate five functionally relevant traits, developed by Lujan and Armbruster (2012). These traits quantify aspects of feeding biomechanics, and give insight into the mechanical advantages of the jaw system.

1. Mechanical advantage at the distal-most tooth was calculated as the quotient of the input lever (In) and the distance between the distalmost tooth and the anguloarticular condyle (Outdist). A high value reveals a strength optimized jaw, while a low value reveals a speed-optimized jaw.

2. Mechanical advantage at the proximal tooth was calculated as the quotient of the input lever (In) and the distance between the proximalmost tooth and the anguloarticular condyle

(Outprox). A high value favours strength, while a low value favours speed.

3. The combined measure of torque and distribution of force transmitted through the mandible which reaches the substrate was calculated as the quotient of the perpendicular distance between the coronoid arch and the line formed by the Outdist measurement (H1) and the tooth row length (TRL). This measure quantifies the concentration of force that makes contact with the

8 substrate while scraping. A high ratio shows a concentration of force, while a low ratio shows distributed force.

4. The maximum force entering the mandible per unit substrate contacted was measured as the area of insertion of the adductor mandibulae muscle (AMarea) divided by the squared value of the tooth row length (TRL). A high quotient favours concentrated force, while a low ratio favours distributed force.

5. Lastly, an indicator of jaw protrusion, mechanical advantage, and variation in torque across the tooth row was measured as the angle (∡ x) formed where the tooth row length (TRL) meets the distance of the distalmost tooth and the anguloarticular condyle (Outdist) (see Figure 3). Small angles show minimal protrusion of the jaw, low strength and high torque, while bigger angles favour the opposite with maximal protrusion of the jaw, maximized strength and low torque.

1.2.6 Body Morphology

Body morphology was measured in this analysis using seven exterior linear measures representing body size and shape in loricariids (Table 2, Figure 4). Data for Chaetostoma breve, C. microps, Etsaputu relictum, Panaqolus nocturnus, and were provided by Nathan Lujan (unpublished data from Lujan et al. 2012).

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Table 2. Morphological variables used to quantify aspects of body size and shape in loricariids.

1 It should be noted that due to the anatomy of their jaw structure, loricariid mouths cannot be closed (Geerinckx et al. 2010), and so the measurement for mouth length may have been influenced by the degree which their mouths were naturally open in a resting position based on the morphology of the dentary when the measurements were taken.

Variable Measurement Distance between lanmarks in Figure 4 Body Length Standard Length Distance from the anterior margin 1-2 of the snout to the base of the caudal fin

Snout Length Distance from the anterior margin 1-12 of the snout to the nares

Head Length Distance from the anterior margin 1-4 of the snout to the posterior margin of the supraoccipital

Mouth Length (Lip Diameter)1 Distance from the anteriormost 12-13 margin of the premaxilla to the posteriormost part of the lower lip Body Depth Head Depth Vertical distance from ventrum to 4-5 supraoccipital

Body Depth at Anal-Fin Insertion Vertical distance from ventrum to 6-7 dorsalmost part of the body at the anal-fin insertion

Body Depth at Caudal Peduncle Vertical distance at posterior 8-9 margin of adipose fin insertion Body Width Body Width Body width at cleithrum 10-11

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Figure 4. Visual representation of body measurements used to evaluate size and shape differences in the present study. A) Lateral view, B) dorsal view, C) ventral view. Loricariid body outlines provided by Sarah Steele.

1.2.7 Phylogenetic Corrections

All phylogenetic corrections were based on a subset of a newly developed multi-locus molecular phylogeny of loricariids (Figure 5) based on one mitochondrial gene (Cytb) and two nuclear genes (RAG1 and RAG2) (Lujan et al, unpublished data). This phylogeny was made ultrametric in Mesquite (Maddison and Maddison 2011), with total branch lengths from the root of the tree to any given tip being set to 1 since the phylogeny is not yet time-calibrated. Branches were pruned to correspond with taxa available for the jaw functional traits and body morphometric analyses. It should be noted that this phylogeny has uncovered the tribe Hypostomini as being placed within , rendering the latter paraphyletic. However, since this phylogeny is not yet published and only contains a small subsample of the total diversity that will be included in the upcoming phylogeny, the relationships herein may not reflect the true evolutionary history of the group. Therefore, in this study, I will continue to refer to Hypostomini as being a separate tribe, as established by Armbruster (2004).

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Figure 5. Multi-locus molecular phylogeny of a subset of loricariids, sequenced by Lujan et al. (unpublished data). Only taxa included in the jaw functional traits analysis were included in the tree. Subtribes identified are Loricarini (green), Hypostomini (orange), and Ancistrini (blue). The tree was further pruned to correspond with taxa available for the body morphology analysis.

Phylogenetic correction ensures that values used in the analysis are statistically independent and evenly distributed by removing the effect of evolutionary relationships among taxa (Felsenstein 1985). In order to quantify variation in jaw functional traits and body morphology in loricariids, all measurements were log-transformed to increase normality of the dataset. These log-transformed values were then size-corrected by performing a regression against Standard Length (which was also log-transformed). The residuals of this regression (Revell 2009) were used in phylogenetically-corrected Principal Components Analyses (PCAs), using the R packages “ape” (Paradis et al. 2004) and “phytools” (Revell 2012). Because of highly divergent body sizes and shapes between the subfamilies (Loricarini) and

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Hypostominae (Hypostomini + Ancistrini) in the dataset, all variables in both subfamilies were size corrected separately, and then combined into a new matrix for the PCAs. Phylomorphospace plots (Sidlauskas 2008) were created from each PCA using the “phytools” package in R (Revell 2012). These plots show the evolutionary relationships between occupied regions of morphospace, and allow for an examination of relative rates of evolution in the morphological traits based on distances between taxa.

1.2.8 Diet Information

1.2.8.1 Diet Categories

Though diet information is sparse in loricariids, several studies have described the feeding ecology of certain species. As such, four diet categories have been identified, and will be compared throughout the study (Table 3). These food groups (guilds) are based on identification of macroscopic particles, and do not include fish for which diet was identified as either detritus or of unknown origin.

Table 3. Diet information identified for a subset of loricariids in this study, based on references to diet in the literature. The four diet categories include wood eaters (purple), algae scrapers (gray), insect and mollusk eaters (pink) and aufwuch eaters (yellow). 1Aufwuch consists of small crustaceans, larval insects and pieces of algae attached to rocks and substrate.

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Diet Species Within Group References to Diet in Literature Panaqolus gnomus P. nocturnus Schaefer and Stewart 1993; Nelson et al. 1999; Panaque nigrolineatus Wood Armbruster 2003, 2004; Lujan et al. 2011; Lujan et al. Hypostomus macushi 2012 H. pyrineusi H. taphorni Chaetostoma breve C. microps Algae C. stroumpoulos Hood et al. 2005; Lujan et al. 2011 C. sp. Xingu Lamonthichthys sp. Insects + L. heterodon Burgess 1994 Mollusks L. triactis Scobinancistrus pariolispos Hypancistrus contradens H. delibittera Aufwuchs1 H. furunculus Horeau et al. 1998; Armbruster et al. 2011 H. lunaorum Lithoxus lithoides

1.2.8.2 Stable Isotope Analysis

For dietary comparisons, isotope values for δ13C and δ15N were provided by Lujan (unpublished data from Lujan et al. 2012). These isotope values for syntopic loricariid assemblages were standardized to a centroid value for each locality. Distance from the assemblage centroid to each taxon in the assemblage is the centroid deviation (Lujan et al. 2012). See Appendix B for list of species used, and the mean centroid deviation values for each δ13C and δ15N. The mean centroid deviation of samples from a particular species was calculated for each locality, and this value was used to calculate a mean centroid deviation for each species. This was done so that uneven sample sizes for each locality did not influence a species’ centroid deviation value. Although isotope data did not come from the same specimens as the morphological data, this should not be an issue since it is expected that interspecific variation should be greater than intraspecific variation (Lujan et al. 2012)

Phylogenetically Generalized Least Squares (PGLS) (Grafen 1989; 1992) was used on the mean centroid deviation for each species separately, for each δ13C and δ15N and the residuals of the first two principal components (PCs) of the PCAs for both the jaw functional traits and body morphology datasets. This analysis was a modified Generalized Least Squares regression

14 model using a phylogenetic tree to account for the non-independence of taxa (Felstenstein 1985; Grafen 1989), and assuming that the traits evolved under Brownian motion. The “nlme” package in R was used to run these analyses (Penheiro et al. 2013).

1.3 Results

1.3.1 Significant Principal Components Test

To determine which (PC) axes were significant and retainable for further analysis, eigenvalues of the observed data were compared to simulated eigenvalues using the “picante” package in R (Kembel et al. 2010). Measurements of jaw functional traits and body morphology were randomized within the dataset, and eigenvalues of the randomized matrices were calculated separately along with the mean of these values. This permutation process was completed 1000 times for each dataset to create a distribution of possible eigenvalue means assuming random distribution of the data. The mean of the observed value was compared to the distribution of simulated data, with the expectation that critical axes would have a mean score higher than that of the simulated data. For both jaw functional traits and body morphology, the permutation test determined that only PC1 and PC2 were significant (see Figure 6 for jaw functional traits test – data not shown for body morphology test).

Figure 6. PC axis significance test for jaw functional traits analysis. Randomized eigenvalue means (red) were created and compared with actual eigenvalues obtained in the PCA (black).

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Critical axes have a mean score higher than that of the simulated data. In this case, only the first two axes can be interpreted in the analysis.

1.3.2 Jaw Functional Traits Analyses

In the analysis of five variables of jaw functional traits for 48 species, PC1 and PC2 together represented nearly 74% of the total variation in this dataset (Figure 7, Table 4). Variation along PC1 was explained by mechanical advantage measures to proximal and distal teeth (see section 1.2.5 – functional variables 1 and 2). Low ratios of mechanical advantage were associated with negative scores while high ratios of mechanical advantage were associated with positive scores. As such, the functional interpretation is that PC1 reflects a trade-off between jaw speed (low ratios) and jaw strength (high ratios). Similarly, variation along PC2 is explained by the maximum force entering the mandible per unit of substrate contacted (AM/ (TRL^2)) (see section 1.2.5 – functional variable 3). Low ratios are associated with negative scores while high ratios are associated with positive scores. Therefore, the functional interpretation is that PC2 reflects a gradient of distributed force across the tooth row length (low values) and concentrated force (high values).

Table 4. Species abbreviations used in all analyses. Colours represent the three tribes included in the analysis, with Loricarini (green), Hypostomini (orange), and Ancistrini (white).

An.m macropthalmus Lm.sp Lamonthichthys sp. Pk.s sabaji An.r Ancistrus ranunculus La.s schomburgkii Pk.v Ba.b Baryancistrus beggini La.t Lasiancistrus tentaculatus Psc.l leopardus Ba.x Le.g Leporacanthicus galaxias Psa.s sidereus Ch.b Chaetostoma breve Le.h Leporacanthicus heterodon Psl.a anthrax Ch.m Chaetostoma microps Le.t Psl.d Pseudolithoxus dumus Ch.s Chaetostoma stroumpoulos Li.l Lithoxus lithoides Psl.t Pseudolithoxus tigris Ch.x Chaetostoma sp. Xingu Ne.b brevibacchium Ri.f Rineloricaria fallax De.s Dekeyseria scaphiryncha Ol.p Oligancistrus punctatissimus Sc.p Scobinancistrus pariolispos Et.r Etsaputu relictum Pqo.a Panaqolus albomaculatus Sp.L L020 Fa.n amazona Pqo.g Panaqolus gnomus St.m Sturisoma monopelte He.s subviridis Pqo.n Panaqolus nocturnus Hyo.m Hypostomus macushi Hya.c Hypancistrus contradens Pqe.n Panaque nigrolineatus Hyo.p Hypostomus pyrineusi Hya.d Hypancistrus delibittera Par.n nudiventris Hyo.t Hypostomus taphorni Hya.f Hypancistrus furunculus Pk.ba Peckoltia bachi Hyo.r Hypostomus rhantos Hya.l Hypancistrus lunaorum Pk.b Peckoltia braueri Hyo.n Hypostomus niceforoi

Fishes categorized as feeding on wood, insects, algae or aufwuch occupy different areas of morphospace (Figure 7), indicating that jaw functional traits may influence diet. The guilds

16 are associated with the outermost edges of the defined morphospace, whereas fish that were classified as either of unknown diet or detritivorous -which do not have a colour associated with them- have smaller ranges in jaw functional traits.

The four Chaetostoma species (Ancistrini) included in the analysis are convergent in morphospace with Lamontichthys sp. (Loricarini), despite the fact that these fish are from different tribes. Both Chaetostoma and Lamontichthys are algae scrapers (Hood et al. 2005; Lujan et al. 2011), and are shaded in gray in the PCA (Figure 7). Both these groups display long tooth row lengths and large adductor-mandibulae insertion areas (data not shown). These fish load positively on PC1, which indicates they have jaws optimized for strength. As such, Lamontichthys sp. is far from the cluster of other members of Loricarini in the analysis.

At the opposite end of PC1, Leporacanthicus heterodon and Scobinancistrus pariolispos, have speed-optimized jaws. They also load positively on PC2, which indicates concentrated force. Their diets consist primarily of mollusks and insects (Burgess 1994), and they, along with other species of the Leporacanthicus are shaded in pink.

Shaded in yellow are fish whose diet primarily consists of aufwuchs (Horeau et al. 1998; Armbruster et al. 2011). They include species of Hypancistrus and Lithoxus, which are both in the tribe Ancistrini, and are characterized by distributed force along the length of the tooth row, as well as optimized speed.

The Hypostomini occupy a unique area of morphospace characterized by concentrated force (high loading on PC2). The phylomorphospace reveals a distinct split between the wood- eating Hypostomus cochliodon group (as defined by Armbruster, 2003), and the non-wood eating Hypostomini, represented in this study by H. rhantos and H. niceforoi. The H. cochliodon group is convergent with the other wood-eating loricariids (of the tribe Ancistrini), and are shaded purple in the PCA. Interestingly, Peckoltia bachi is also found among the wood-eating loricariids in this analysis, despite not being a wood eater (Armbruster 2008).

17

Figure 7. Graphic representation of the first two principal components of jaw functional traits of a phylogenetically-corrected PCA, by means of morphospace (upper panel) and phylomorphospace (lower panel). PCA analysis included five size corrected variables for the mean values of 48 species of loricariids. Symbol colours indicate the three tribes included in the analysis, Loricarini (green), Hypostomini (orange), and Ancistrini (blue). Shaded ploygons in the PCA indicate to primary diet category: wood (purple), aufwuchs (yellow), algae (gray), and insects/mollusks (pink). See Table 5 for loadings of each PC axis, and Table 4 for full names of species’ abbreviations.

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Table 5. Principal components analysis eigenvectors for jaw functional traits and body morphology. All analyses were calculated using a phylogenetically-corrected PCA.

Jaw Functional PCA eigenvectors Body Morphology PCA eigenvectors PC1 PC2 PC1 PC2 Eigenvalue 2.288 1.389 Eigenvalue 3.059 2.606 Cumulative percent variance Cumulative percent variance 45.77 73.56 38.24 70.82 explained explained

AM/(TRL^2) -0.317 0.876 Head Length -0.776 0.399 Mechanical Advantage -D 0.661 0.577 Mouth Length -0.545 0.676 Mechanical Advantage -P 0.871 0.299 Head Depth -0.776 -0.361 H1/TRL -0.790 0.445 Cleithral Width -0.682 -0.060 Tooth Row Angle -0.606 0.021 Snout Length -0.818 0.325 Depth at Anal Fin -0.509 -0.816 Depth at Caudal Peduncle -0.382 -0.787

1.3.3 Body Morphology Analysis

The morphospace defined by the eight body morphology variables for 39 species (in which PC1 and PC2 represent a combined 71% of the total variation in the dataset), appears more dispersed than that of jaw functional traits (Figure 8). Some sister taxa occupy vastly different areas of morphospace, and there appears to be an accelerated rate of morphological change along these branches which is made evident in the phylomorphospace plot (Figure 8, lower panel). For example, species in the genus Chaetostoma are highly dispersed in morphospace. In constrast, species of the genus Hypostomus have a well-defined morphospace. This pattern contrasts with that of the jaw functional traits, where intrageneric clustering and more conserved morphology are evident for nearly all genera. PC1shows a gradient in head shape with Head Length, Head Depth and Snout Length loading strongly along this axis (Table 5). On one end of PC1 are long and deep heads and on the other are short and flat heads. Variation along PC2 is explained primarily by variation of body depth, with one end describing deeper bodies and the other describing shallower bodies.

In contrast to the jaw functional traits analysis (Figure 7), the body morphology analysis does not reveal segregation of guilds in morphospace. Rather, there is overlap between the diet polygons (wood and algae, as well as insects and mollusks and aufwuchs), and these guilds occupy vast areas or morphospace, especially along PC1 in the case of the wood-eaters (purple).

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When comparing intrageneric variation in morphospace, the majority of congeners have a similar position along PC2 (body depth), but are divergent along PC1 (head depth). This pattern is consistent when sister taxa across all three tribes are examined. Both Ancistrus species, as well as all three Peckoltia species (tribe Ancistrini) are prime examples. An exception to this trend is Baryancistrus, which differs very little along PC1, but B. beggini has a much deeper body relative to B. xanthellus.

The Hypostomini appear to have similar body morphologies, with deep bodies and short, flat heads. Contrary to the jaw functional traits, this tribe is not convergent with other wood- eating loricariids in body shape (gray), as both ancistrin wood-eaters (Panaqolus nocturnus and Panaque nigrolineatus) have much deeper and longer heads than the hypostomin wood-eaters (Hypostomus pyrineusi, H.taphorni, and H. macushi).

Chaetostoma breve and Panaque nigrolineatus appear to be convergent on a body plan defined by deep bodies and heads, despite having different overall maximum body sizes (C. breve has a maximum size of 30cm, while P. nigrolineatus can grow upwards of 43cm (Fisch- Muller, 2003). They also have different diets, with the former eating algae and the latter feeding on wood.

The genus Leporacanthicus and Scobinancistrus pariolispos (pink) also have similar body sizes and shapes. They are the only members of identified guilds that appear to cluster in the body morphology PCA. Despite their specialized jaws, their body morphology falls near the center of family morphospace, indicating that their proportions are average among loricariids.

It is interesting to note the relatively high divergence of Rineloricaria fallax from other loricarines, and its position within morphospace shared by deep-bodied loricariids. This was due to the separate size correction (see Methods) between the Loricarinae (Loricarini) and (Hypostomini + Ancistrini). Rineloricaria fallax is more robust than its counterparts, which are markedly thin, narrow, and elongate, and this led to the low score on PC2 despite the fact that it does not appear to resemble the surrounding deep-bodied fish. An attempt to resolve this issue was to size correct R. fallax with the more robust Hypostominae, but this caused R. fallax to become an outlier in the analysis (data not shown), and so the original residuals were kept. However, any functional interpretation along PC2 should be made with caution.

20

Figure 8. Graphic representation of the first two principal components of body morphology of a phylogenetically-corrected PCA, by means of morphospace (upper panel) and phylomorphospace (lower panel). PCA analysis included eight size corrected variables for the mean values of 39 species of Loricariids. Symbol colours indicate the three tribes included in the analysis: Loricarini (green), Hypostomini (orange), and Ancistrini (blue). Shaded ploygons in the PCA indicate to primary diet category: wood (purple), aufwuchs (yellow), algae (gray), and

21 insects/mollusks (pink). See Table 5 for loadings of each PC axis, and Table 4 for full names of species’ abbreviations.

1.3.4 Diet-Morphology Correlations

Phylogenetic Generalized Least Squares (PGLS) analyses for jaw functional traits included mean values for 38 taxa, while the body morphology analysis included 31 taxa. These analyses revealed a significant correlation (p=0.0239) between jaw functional traits and centroid deviation values of δ13C, as well as a significant correlation (p=0.0299) between body morphology and centroid deviation values of δ13C (Table 6).

A regression for the significant results of jaw functional traits was also run excluding PC1 in order examine to what extent correlation could be attributed to PC2 alone, rather than a combination of PC axes. Results did not show any change in significance, and the AIC was similar (data not shown) meaning that PC1 did not add important information to the model. Therefore only PC2 will be considered in the interpretation of the jaw functional traits results. For jaw functional traits, the value of the regression slope is negative (-2.2994), indicating that the centroid deviation value of δ13C is inversely proportionate with force concentration in jaws (Figure 9).

Results show that wood-eaters have the greatest centroid deviation of the guilds in the analysis. This is consistent with their relatively greater ingestion and assimilation of terrestrial (allochthonous) sources of carbon (i.e. trees), whereas the more δ13C depleted values of the three other guilds are consistent with their relatively greater ingestion and assimilation of carbon from aquatic sources.

Table 6. Results of PGLS regressions using centroid deviations of δ13C and δ15N against residuals of the first two principal components of the jaw functional traits (f) and body morphology (b) PCAs. Significant results (p< 0.05) are indicated in orange.

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Model Resid. Std. Error Value Std. Error t-value p-value C~PC2f + PC1f 3.382 Intercept -0.3865 1.7303 -0.2233 0.8246 PC2f -2.2994 0.9737 -2.3615 0.0239 PC1f 0.1848 0.8118 0.2277 0.8212 N~PC2f + PC1f 1.649 Intercept 0.0229 0.9331 0.0246 0.9805 PC2f -0.3079 0.5251 -0.5864 0.5613 PC1f -0.3228 0.4378 -0.7373 0.4658 C~PC2b + PC1b 3.377 Intercept -0.2319 1.7522 -0.1323 0.8957 PC2b 1.0272 1.1692 0.8786 0.3874 PC1b -2.6275 1.1465 -2.2917 0.0299 N~PC2b + PC1b 1.868 Intercept -0.0778 0.9693 -0.0802 0.9366 PC2b 0.0564 0.6467 0.0873 0.9311 PC1b 0.5215 0.6343 0.8223 0.1481

Figure 9. Estimate of concentration of δ13C as a function of jaw functional traits. PGLS model-predicted regression shows that jaws optimized for force concentration are inversely proportionate with δ13C intake (t-value = -2.36; p-value=0.0239). See table 6 for all results of the analysis.

Similarly, PC1 was found to be significant (rather than a combined effect of both PC1 and PC2) for the relationship between body morphology and δ13C. Interpretation of results will therefore only include PC1. The value of the regression slope is negative (-2.6275), indicating

23 that the centroid deviation value of δ13C is inversely proportionate with force concentration in jaws (Figure 10).

Figure 10. Estimate of concentration of δ13C as a function of body morphology. PGLS model-predicted regression shows that short heads and snouts, coupled with flat heads are inversely proportionate with δ13C intake (t-value = -2.29; p-value=0.0299). See table 6 for all results of the analysis.

1.4 Discussion

The results of the jaw functional traits analysis show a clear separation of the dietary guilds in morphospace, whereas these guilds overlap in the body morphology analysis. This will be explored in the upcoming section, and will be complemented by a look at the results for each dietary guild in relation to morphospace. Next the relationship between body morphology and habitat use will be discussed, and finally, the implications of the diet-morphology correlations uncovered in the PGLS regressions will be explored and discussed in regards to feeding adaptation in loricariids.

1.4.1 Jaw Functional Traits Analyses

The PCA analysis for jaw functional traits (Figure 7) reveals that taxa are partitioned in morphospace based on their known dietary specializations, as indicated by the separation of

24 dietary guilds in morphospace. A functional gradient is evident between speed-optimized jaws and strength-optimized jaws (PC1), as well as between jaws with force either concentrated or distributed (PC2).

PC1 corresponds to a functional gradient with invertivores with speed-optimized jaws at one end with (including Leporacanthicus, Scobinancistrus, Hypancistrus, and Lithoxus, and algae scrapers with strong jaws on the other (Chaetostoma and Lamontichthysis). In the middle along PC1, we notice the wood-eaters (purple) which seem to have jaws optimized for strength, albeit to a lesser extent than the invertivores. The dietary gradient is also apparent on PC2. Loricariids requiring concentrated force to pry invertebrates from their shells (pink), or to scrape pieces of wood from the substrate (purple) load positively on PC2, whereas the aufwuch-eaters (yellow) require distributed force, presumably to remove the larva off rocks (Grillet and Barrera 1997).

1.4.2 Body Morphology Analysis

The body morphology analysis does not reveal segregation of guilds (coloured groups) in morphospace. Rather, there is overlap between guilds, indicating that taxa with different body shapes may be eating similar diets. The overlap between guilds also suggests that diet may not be closely related to body morphology, especially along PC1 (which represents head shape).

1.4.3 Diet Groups

A closer look at the results for each dietary guild in relation to morphospace may provide insight into association of diet and feeding morphology in loricariids.

1.4.3.1 Algae Scrapers (Gray)

Chaetostoma and Lamontichthys appear to converge on similar jaw functional traits (Figure 7). This was not expected since they are from different tribes. However, dietary information reveals that both are primarily algae scrapers, which suggests that this specialized mode of feeding exerts a constraint on morphospace. Interestingly, these genera are found sympatrically in swift piedmont rivers of the and the Guiana Shield (Lujan and Armbruster 2011), which indicates that they are convergent on the same resources despite living in the same environment.

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Although Lamontichthys sp. was not included in the body morphology analysis due to unavailable data (see Methods), it is interesting to note that this fish does not appear at all similar to Chaetostoma from an external body shape perspective – it has a much more depressed and narrow body, as is characteristic of most Loricarini (Paixao and Toledo-Piza, 2009). However, despite the overall body differences, the heads look quite similar (Figure 11), which coupled with their diet of algae, suggests that there may be a link between diet and morphology in these fish.

Figure 11. Despite their different body shapes, head morphology appears convergent in representatives of Lamontichthys and Chaetostoma. A) Lamontichthys sp., b) Chaetostoma microps. Photographs are not to scale, and the body and mouth pictures are from different individuals of the same species. Individual images provided by Nathan Lujan.

1.4.3.2 Wood-Eaters (Purple)

The analysis of jaw functional traits revealed that the Hypostomini occupy a unique area of morphospace, and the phylomorphospace analysis revealed a distinct split between the H. cochliodon group and the non-wood eating Hypostomini, represented by Hypostomus rhantos and H. nocturnus (Figure 7). The H. cochliodon group is convergent with the other wood-eating loricariids (Schaefer and Stewart 1993; Nelson et al. 1999), and occupy an area of morphospace characterized by concentrated force in jaw function. Convergence within concentrated force morphospace of wood-eaters suggests considerable force is needed to process submerged wood whereas distributed force may limit loricariids to scraping biofilm on the surface of the wood.

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The body morphology analysis shows great variation along PC1 for the wood eaters (Figure 8). This indicates that although Hypostomus and Panaque/Panaquolus have very similar jaw functional characteristics, these are independent of body shape and size. P. bathyphilus has a long and deep head, whereas Hypostomus have short and flat heads. P. nocturnus appears to have an intermediate head shape in comparison to the other wood-eaters. However, the wood-eaters have similar body depths, as they are loading closely along PC2. These results suggest that head morphology is not linked to jaw functionality in these fish.

Peckoltia bachi, is found among the wood-eating loricariids in the both jaw functional traits and the body morphology analyses. Though little is known about P. bachi’s diet, it has been known to live among submerged twigs, and possesses muscular adaptations to grasp twigs in its habitat (Armbruster 2008). It may be possible that P.bachi’s jaws are morphologically and functionally similar in order to attach to woody substrates, perhaps even removing wood from branches in search for food. It would be interesting to explore potential convergence of P. bachi body morphology; however, this could not be verified in this study since exterior morphometrics were not available for this species. Interestingly, Peckoltia was not recovered as monophyletic in the molecular phylogeny (Figure 5), as a result of P. bachi not grouping with other Peckoltia. Initial inclusion of this species in the genus Peckoltia could be due to the convergence of characters used in previous morphological analyses which do not accurately reflect the evolutionary history of this species. In light of this and the results of both jaw functional traits and the body morphology analyses, a taxonomic revision of P. bachi could be warranted.

1.4.3.3 Insect and Mollusk Eaters (Pink)

Based on the analysis of jaw functional traits, Leporacanthicus heterodon and Scobinancistrus pariolispos are shown to have converged on speed-optimized jaws. In addition, both are also very positively loaded on PC2, which indicates concentrated force (Figure 7). Species in the genus Leporacanthicus and S. pariolispos are characterized as having few very long premaxillary teeth. These teeth, which are upwards of three times the length of the dentary teeth in species of Leporacanthicus, are hypothesized to be used for mining insects from wood, as well as extracting snails from their shells (Burgess 1994). It is thus not surprising that their jaws are optimized for speed and concentrated force, both useful in catching and extracting prey from the substrate.

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Despite not including measurements from the premaxilla in the present study, the specialization of this feeding mode is captured in measurements from the mandible. The dentary must have also converged to meet the demands of invertivory, and we can see evidence of this in the jaw functional traits PCA (Figure 7), where Leporacanthicus and S. pariolispos occupy a unique area of morphospace.

The insect and mollusc eaters are the only dietary group to have similar body morphologies (Figure 8). They are clustered in morphospace, and have relatively average sized heads and body depths. These results suggest that body morphology and jaw function may be linked in this group of loricariids.

1.4.3.4 Aufwuch Eaters (Yellow)

Aufwuch eaters are characterized by their speed-optimized jaws with force distributed along the tooth row length. They occupy a unique area of morphospace in regards to their jaw functional traits. Distributed force would allow these fish to effectively scrape larvae, crustaceans and algae from rocks, where most of their prey is found (Armbruster et al. 2011).

The body morphology analysis reveals that these fish are very dispersed throughout morphospace, along both PC1 and PC2 (Figure 8). This appears to be in part due to Hypancistrus’ conserved body morphology which differs significantly from that of Lithoxus lithoides’ body morphology. Hypancistrus have much deeper bodies, as well as longer and deeper heads, and their morphospace overlaps that of the other invertivorous group (shaded in pink).

L. lithoides appears to be at the edge of morphospace in all three analyses. From a body shape perspective, it has the most depressed body of all loricariids in the analysis. In addition, the head and snout are also exceptionally dorso-ventrally depressed compared to most loricariids included in the analysis. These traits are consistent with its habitat requirements, as L. lithoides is found under rocks in small rivers and streams (Armbruster 1998).

The results of the analyses do not suggest that jaw functional traits and body morphology is linked in these insectivorous fish.

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1.4.4 Habitat Use

The gradient along PC1 of the body morphology PCA (Figure 8) appears to give insight into habitat use, specifically along a water-velocity gradient. This gradient has been reported in other Neotropical species (Casatti and Castro 2006), although it seems to be to a lesser extent in loricariids. As such, we would expect to find that species with long and deep heads (notably Chaetostoma and Panaque) would be found in fast moving waters as their robustness would be advantageous against the current. This is indeed the case for both Chaetostoma which are found in fast-moving rocky waters (Salcedo 2006), and Panaque which live in fast-moving Amazonian headwaters (Nelson et al. 1999). At the opposite end of PC1, Lithoxus and Pseudolithoxus dwell under rocks in rivulets (Armbruster 1998; Lujan and Brindelli 2011), which can be described as slower moving water. In addition, Hypostomus, which is found intermediately on PC1, has been known to live in shallow pools and lakes which have a slow current (Armbruster 1998). However, some species may be found in rivers with swift flow (Burgess 1989), which could explain its deep body.

Mouth Length is loading positively on PC2 of the body morphology analysis, which is a gradient of body depth. Since mouth length is a measurement of oral disk diameter, it may give a hint as to suction surface. As expected, loricariids with dorso-ventrally flattened bodies have longer mouth lengths (Table 5), potentially to attach themselves in fast moving currents.

Body size and shape are known to be important for accessing food sources in pelagic fish. However, since loricariids are limited to the bottoms of lakes and rivers, their body shape may be more associated with their habitats and the substrates on which they live rather than their specific food sources. For example, Lithoxus lithoides has a dorso-ventrally compressed body, which allows it to live under rocks (Armbruster 1998). However, in certain taxa, there appears to be a disconnect between body size, shape, and the food resources consumed. For example, despite Chaetostoma and Lamonthichthys’ very different body shapes (Figure 11), they have similar diets, and both were collected from the Marañon River in northern (Lujan and Armbruster 2012). It should be noted that detailed habitat and dispersal data is lacking in loricariids, and this severely limits inferences that can be made about how body size and shape may be important for food acquisition or niche differentiations. Further studies should therefore incorporate

29 information about habitat use and co-existence in loricariids in order to test if fish with similar body sizes and shapes share ecological niches.

1.4.5 Diet-Morphology Correlations

1.4.5.1 Relationship Between δ13C and Jaw Functional Traits

The PGLS regression revealed a significant correlation (p=0.0239) between jaw functional traits and the concentration of δ13C. Since only PC2 of jaw functional traits is significantly correlated with diet, it is the only axis of variation that can be interpret from the analysis. The value of the regression slope is negative (-2.2994), indicating concentration of δ13C is inversely proportionate with force concentration in jaws (Figure 9).

Studies have shown that wood-eating loricariids have a different δ13C signal than those that strictly rely on autochthonous carbon sources (Nogonaki et al. 2007; German and Miles, 2010; Lujan et al. 2012). These findings are consistent with those of this study, as we can clearly see that there is no overlap between the wood-eaters (purple) and the known non-wood eating loricariids. For the most part, the wood eaters have a bigger centroid deviation value than the other guilds. This is not surprising since the mean centroid deviation calculated for each locality sampled would have been influenced by a high proportion of autochthonous carbon sources. Because allochthonous carbon sources have a different δ13C signal, it is expected that the deviation from the mean centroid would be greater. It is interesting to note that certain fish not associated with a diet guild have similar centroid deviations for δ13C to wood-eaters. It can therefore be hypothesized that Hypostomus rhantos, H. niceforoi, Panaqolus albomaculatus, Rineloricaria fallaa, Pseudolithoxus dumus and Baryancistrus beggini also have diets consisting of allochthonous carbon sources.

The aufwuch eaters, algae scrapers and insect/mollusk eaters have overlapping centroid deviation values for δ13C, which could indicate that they obtain their food from enriched autochtonous sources of carbon. Certain taxa that were considered either generalists, detritivores, or of unknown dietary composition have similar centroid deviation values to the pink, yellow and gray groups, indicating that they too probably consume a diet rich in aquatic sources.

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Conversely, taxa with high centroid deviation values are likely consuming terrestrial carbon sources since their values are similar to those of the wood-eaters.

1.4.5.2 Relationship Between δ13C and Body Morphology

A significant correlation (p=0.0299) was uncovered between body morphology and concentration δ13C (Table 6, Figure 10). PC1 was the only axis found to be significant (rather than a combined effect of both PC1 and PC2). Interpretation of results is therefore limited to only include PC1. The value of the regression slope is negative (-2.6275), indicating that the centroid deviation value of δ13C is proportionate with head length (Figure 10), since taxa with shorter heads have smaller centroid deviations of δ13C.

The same trend is observed as with the correlation between δ13C and jaw functional traits, wherein the wood-eaters have a higher centroid deviation than the other groups. The position of the insect/mollusk eaters in the regression is striking since they are completely contained within the same space as the aufwuch eaters, indicating that they have overlapping body morphology along PC1 as well as overlapping centroid deviation values for δ13C. It is obvious that the only axis that separates these two groups is that of PC2 for jaw functional traits.

1.4.5.3 Implications of Diet-Morphology Correlations in Loricariids

Morphological variation with regards to jaw functional traits and body morphology were quantified and tested independently for correlations with diet, by means of species’ relative position in assemblage isotope space (for both δ13C and δ15N) and diet categories (Table 3). Despite the expectation that jaw functional traits would be linked to body morphology and that both could be used to predict diet, the results of this study only partially support this. Results showed that jaw functional traits do not appear to be linked to body morphology in Loricariidae. Jaw functional traits were correlated with δ13C, an indication of the carbon source (aquatic versus terrestrial). Jaw functional traits were not correlated with δ15N, a general indication of proportions of protein in the diet. Partitioning of morphospace of jaw functional traits (Figure 7) indicate a link between jaw morphology and diet categories (Table 3). Convergence of jaw functional traits among taxa exploiting similar resources indicated that jaw functional traits may be used to predict diet categories across the family. This study does not explicitly test whether functional traits associated with the mandible are specialized for particular purposes (e.g., wood

31 eating), however the divergence of jaw functional traits along the δ13C gradient suggest there may be a difference in performance capability to exploit different carbon sources.

Body morphology was also correlated with δ13C, which may be explained by habitat use (water-velocity gradient) of various body shapes and the potential differences in the proportion of autochthonous versus allochthonous resources among different habitat types. Due to the current lack of detailed distribution and habitat data for taxa included in this study, only general statements regarding this association can be made. However, further analyses of habitat- morphology associations may shed light on the processes driving the pattern of the δ13C-body morphology correlation observed in this study.

Questions of diet-morphology relationships addressed in this study are only the first steps in understanding the ecology of this group of fishes in an evolutionary context. Loricariidae is the second most taxonomically diverse lineage in the Neotropics (Reis et al. 2003) and it was qualitatively described as having relatively high ecological diversity (Lujan et al. 2012). This study supports the initial observations of Lujan et al. (2012) by quantifying functional diversity with regards to feeding ecology. It has yet to be tested whether this functional diversity can be attributed to the taxonomic richness of Loricariidae, or whether there is an adaptive component that has accelerated the rates of morphological and species diversification in this group.

1.5 Conclusions

Despite being taxonomically diverse, loricariids show relatively little dietary diversity and share the same trophic level – they are predominantly detritivores in Neotropical systems. It has been hypothesized that they partition their food resources on a nutrient gradient, (Lujan et al. 2011; Hood et al. 2005; Nogogaki et al. 2007), yet little research has shown an explicit link between diet and feeding morphology in loricariids. The present study was the first to quantify the diversity of jaw functional traits in loricariids in an explicit phylogenetic context, and has demonstrated that these fish are not only taxonomically diverse, but their jaws are also functionally diverse. Recorded dietary information for certain taxa indicates that their jaws are specialized for their diets (wood-eating, invertivory, algae-scraping). Body morphology was also quantified in a phylogenetic context, and revealed that jaw functional traits are decoupled from

32 body morphology. Loricariids with different body sizes and shapes converge on similar jaw functional traits if they have similar diets.

Both jaw functional traits and body morphology show correlations with δ13C isotope data. Jaw functional traits were inversely correlated with centroid deviation values of δ13C, and body morphology was also inversely correlated with δ13C values. These results are the first quantified links between diet and feeding morphology in loricariids. This suggests that both jaw function and body morphology can predict ecological traits, which, in turn, suggests an adaptive relationship.

This study is evidence that more research is warranted to fully understand the relationship between diet and morphology in loricariids, and perhaps begins to grasp how this family of fish has become so diverse.

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Appendix A

List of species prepared for this study, as well as catalogue numbers of the institutions from which they came. Geographical information includes GPS coodinates from the sampled locality. All fish were collected in Brazil (BR), (G), or Venezuela (V).

Inst. Catalog # Species Country Latitude Longitude

AUM 42105 Ancistrus macropthalmus V 3.96731 -67.2535

AUM 42105 Ancistrus macropthalmus V 3.96731 -67.2535

AUM 42105 Ancistrus macropthalmus V 3.96731 -67.2535

AUM 42105 Ancistrus macropthalmus V 3.96731 -67.2535

ANSP 199612 Ancistrus ranunculus BR 3.39040 -52.2243

AUM 54990 Baryancistrus beggini V 3.88218 -67.0136

AUM 54990 Baryancistrus beggini V 3.88218 -67.0136

AUM 54990 Baryancistrus beggini V 3.88218 -67.0136

AUM 54990 Baryancistrus beggini V 3.88218 -67.0136

ANSP 193015 Baryancistrus xanthellus BR 3.50355 -52.4408

ANSP 199686 Chaetostoma sp. Xingu BR 3.27209 -52.5534

ANSP 199686 Chaetostoma sp. Xingu BR 3.27209 -52.5534

AUM 54474 Dekeyseria scaphiryncha V 4.02372 -66.9773

AUM 54474 Dekeyseria scaphiryncha V 4.02372 -66.9773

AUM 54270 Dekeyseria scaphiryncha V 4.72977 -67.8191

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AUM 54270 Dekeyseria scaphiryncha V 4.72977 -67.8191

AUM 53524 Hemiancistrus subviridis V 4.38418 -67.7747

AUM 54989 Hemiancistrus subviridis V 3.88218 -67.0136

AUM 54989 Hemiancistrus subviridis V 3.88218 -67.0136

AUM 54989 Hemiancistrus subviridis V 3.88218 -67.0136

AUM 54993 Hypancistrus contradens V 3.88218 -67.0136

AUM 54993 Hypancistrus contradens V 3.88218 -67.0136

AUM 53528 Hypancistrus delibittera V 4.38418 -67.7747

AUM 53528 Hypancistrus delibittera V 4.38418 -67.7747

AUM 58530 Hypancistrus furunculus - - -

AUM 58530 Hypancistrus furunculus - - -

AUM 58530 Hypancistrus furunculus - - -

AUM 58530 Hypancistrus furunculus - - -

AUM 54470 Hypancistrus lunaorum V 4.07870 -66.8585

AUM 39854 Hypancistrus lunaorum V 4.08042 -66.8651

AUM 42163 Hypancistrus lunaorum V 3.10036 -66.4628

AUM 42163 Hypancistrus lunaorum V 3.10036 -66.4628

AUM 48692 Hypostomus hemiurus G 3.50207 -59.0339

ROM 87216 Hypostomus hemiurus G 5.15091 -58.1952

ROM 87216 Hypostomus hemiurus G 5.15091 -58.1952

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ROM 87216 Hypostomus hemiurus G 5.15091 -58.1952

AUM 48768 Hypostomus macushi G 3.8950 -59.2937

AUM 49801 Hypostomus macushi G 3.8950 -59.2937

AUM 48160 Hypostomus macushi G 3.66467 -59.3428

AUM 53885 Hypostomus rhantos V 5.34648 -66.0333

AUM 53675 Hypostomus rhantos V 4.75346 -66.3726

AUM 54306 Hypostomus rhantos V 4.29481 -66.2889

AUM 48172 Hypostomus taphorni G 4.18268 -59.0638

ROM 86837 Hypostomus taphorni G 4.90681 -58.2447

ROM 86837 Hypostomus taphorni G 4.90681 -58.2447

ROM 86837 Hypostomus taphorni G 4.90681 -58.2447

AUM 39278 Lasiancistrus tentaculatus V 5.34637 -66.0335

AUM 39278 Lasiancistrus tentaculatus V 5.34637 -66.0335

AUM 39278 Lasiancistrus tentaculatus V 5.34637 -66.0335

AUM 39278 Lasiancistrus tentaculatus V 5.34637 -66.0335

AUM 39279 Leporacanthicus galaxias V 5.34637 -66.0335

AUM 39279 Leporacanthicus galaxias V 5.34637 -66.0335

AUM 42144 Leporacanthicus galaxias V 4.05736 -66.9326

AUM 42144 Leporacanthicus galaxias V 4.05736 -66.9326

ANSP 193009 Leporacanthicus heterodon BR 3.50355 -52.4408

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AUM 56909 Leporacanthicus triactis V 5.38683 -66.1159

AUM 56909 Leporacanthicus triactis V 5.38683 -66.1159

AUM 56909 Leporacanthicus triactis V 5.38683 -66.1159

AUM 58516 Leporacanthicus triactis V 5.38683 -66.1159

AUM 39040 Lithoxus lithoides G 2.22654 -58.2938

AUM 39040 Lithoxus lithoides G 2.22654 -58.2938

AUM 39040 Lithoxus lithoides G 2.22654 -58.2938

AUM 39001 Lithoxus lithoides G 2.22654 -58.2938

ROM 93530 Neblinichthys brevibacchium G 5.48681 -60.7777

ROM 93534 Neblinichthys brevibacchium G 5.48681 -60.7777

ANSP 199539 Oligancistrus punctatissimus 'short snout' BR 3.20568 -52.1119

ANSP 193072 BR 3.22557 -51.4411

AUM 48547 Peckoltia braueri G 2.95963 -59.9625

AUM 48547 Peckoltia braueri G 2.95963 -59.9625

AUM 48547 Peckoltia braueri G 2.95963 -59.9625

AUM 48547 Peckoltia braueri G 2.95963 -59.9625

AUM 39588 V 5.44198 -66.1507

AUM 39588 Peckoltia sabaji V 5.44198 -66.1507

AUM 39588 Peckoltia sabaji V 5.44198 -66.1507

AUM 39588 Peckoltia sabaji V 5.44198 -66.1507

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AUM 39313 Peckoltia vittata V 5.42863 -66.1362

AUM 39313 Peckoltia vittata V 5.42863 -66.1362

AUM 39313 Peckoltia vittata V 5.42863 -66.1362

AUM 39313 Peckoltia vittata V 5.42863 -66.1362

AUM 44440 Pseudacanthicus leopardus G 3.91755 -59.1002

AUM 43443 Pseudancistrus sidereus V 2.36280 -66.5648

AUM 43443 Pseudancistrus sidereus V 2.36280 -66.5648

AUM 43443 Pseudancistrus sidereus V 2.36280 -66.5648

AUM 39246 Pseudolithoxus anthrax V 4.08042 -66.8651

AUM 39246 Pseudolithoxus anthrax V 4.08042 -66.8651

AUM 39246 Pseudolithoxus anthrax V 4.08042 -66.8651

AUM 39246 Pseudolithoxus anthrax V 4.08042 -66.8651

AUM 42118 Pseudolithoxus dumus V 3.28998 -66.6000

AUM 42118 Pseudolithoxus dumus V 3.28998 -66.6000

AUM 42118 Pseudolithoxus dumus V 3.28998 -66.6000

AUM 42118 Pseudolithoxus dumus V 3.28998 -66.6000

AUM 42110 Pseudolithoxus tigris V 3.96731 -67.2535

AUM 42110 Pseudolithoxus tigris V 3.96731 -67.2535

AUM 42110 Pseudolithoxus tigris V 3.96731 -67.2535

AUM 42110 Pseudolithoxus tigris V 3.96731 -67.2535

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ANSP 199622 Scobinancistrus pariolispos BR 3.39040 -52.2243

ANSP 193077 Spectracanthicus L020 'bola blanca' BR 3.22557 -51.4411

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Appendix B

Species used in the stable isotope analyses. Mean centroid deviation for a species was calculated as the mean of the mean of each centroid deviation for that species at a given locality.

Species Mean centroid deviation (δ13C) Mean centroid deviation δ15N)

Ancistrus macrophthalmus -1.1241 0.1994

Baryancistrus beggini 0.5517 0.2425

Baryancistrus xanthellus -2.9246 0.7764

Chaetostoma breve -1.6536 0.4203

Chaetostoma microps -1.6082 -0.0524

Chaetostoma stroumpoulos 0.0975 0.0803

Dekeyseria scaphirhyncha 0.0219 -2.2046

Etsaputu relictum -0.6993 0.6747

Farlowella nattereri -0.414 -0.7258

Hemiancistrus subviridis -0.0219 0.6926

Hypancistrus contradens -2.2276 0.8413

Hypancistrus furunculus -0.3681 0.2303

Hypancistrus lunaorum -1.401 0.7272

Hypostomus macushi 2.9494 1.6004

Hypostomus niceforoi 0.8039 -0.367

Hypostomus pyrineusi 0.4748 -0.1336

Hypostomus rhantos 1.8828 -1.2128

Hypostomus taphorni 0.3751 -0.7367

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Lamontichthys sp -2.2577 0.1555

Lasiancistrus schomburgkii -0.5223 -0.1429

Lasiancistrus tentaculatus -1.45 -0.87

Leporacanthicus galaxias -1.1188 0.9339

Leporacanthicus triactis -2.2826 0.9852

Lithoxus lithoides 0.3889 1.1112

Oligancistrus punctatissimus 0.0518 0.6212

Panaqolus albomaculatus 1.2416 0.3424

Panaqolus gnomus 0.4444 -0.1858

Panaqolus nocturnus -0.2341 -0.4424

Panaque bathyphilus 0.8088 0.0532

Peckoltia braueri -1.8378 1.269

Pseudacanthicus leopardus -0.68 1.9229

Pseudancistrus sidereus 0.1102 0.2475

Pseudolithoxus anthrax -0.057 0.2845

Pseudolithoxus dumus 1.5667 0.3256

Pseudolithoxus tigris -0.4127 0.6909

Rineloricaria fallax 1.5462 -0.2841

Scobinancistrus pariolispos -1.4668 0.9447

Sturisoma monopelte -1.3319 -0.0056

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