https://orcid.org/0000-0002-5540-1851
Figures
Abstract
Body and head shape among fishes both vary between environments influenced by water velocity and across ontogeny. Although the shape changes associated with variation in average water velocity and ontogeny are well documented, few studies have tested for the interaction between these two variables (i.e., does ontogenetic shape variation differ between velocity environments). We use geometric morphometrics to characterize shape differences in Trichomycterus areolatus, a freshwater catfish found in high and low-velocity environments in Chile. We identify a significant interaction between velocity environment and body size (i.e., ontogeny). Ontogenetic patterns of shape change are consistent with other studies, but velocity environment differentially affects the ontogenetic trajectory of shape development in T. areolatus. Shape change over ontogeny appears more constrained in high-velocity environments compared to low-velocity environments.
Citation: Searle PC, Mercer M, Habit E, Belk MC (2021) Ontogenetic shape trajectory of Trichomycterus areolatus varies in response to water velocity environment. PLoS ONE 16(6): e0252780. https://doi.org/10.1371/journal.pone.0252780
Editor: Peter Eklöv, Uppsala Universitet, SWEDEN
Received: October 20, 2020; Accepted: May 24, 2021; Published: June 11, 2021
Copyright: © 2021 Searle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data set used for analysis has been uploaded to Dryad. The public DOI is doi:10.5061/dryad.rn8pk0p8f and URL is https://doi.org/10.5061/dryad.rn8pk0p8f.
Funding: Funding for this work was supported by grants to MCB by the Roger and Victoria Sant Foundation and the Department of Biology, Brigham Young University, as well as EH by projects 032904 3/R Dirección de Investigación, Universidad del Bío-Bío and 204.310.041-1.0 Dirección de Investigación, Universidad de Concepción. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Morphometric traits in animals and plants are shaped by the selective pressures of their environments resulting in interspecific variation in shape [1–4]. Shape responds sensitively to environmental pressures such as predation, resource use, competition, temperature, water velocity, and water availability [5–10]. For example, head and body size changed in two Australian snakes (Pseudechis porphyriacus and Dendrelaphis punctulatus) following introduction of a toxic cane toad (Bufo marinus), and head shape changed among species in the Neotropical cichlid genus Geophagus depending on prey availability [11,12]. Organisms vary in form (i.e., shape) among species largely in response to variation in habitat use or trophic niche and corresponding environmental variation among habitats [2,12].
Environmental variation can also lead to intraspecific morphometric differentiation [13–17]. Examples include differences in head shape in wall lizards (Podarcis bocagei) between saxicolous and ground-dwelling habitats; wing morphology in speckled wood butterflies (Parage aegeria) along a latitudinal gradient; tail, head and ear length in West African Dwarf goats (Capra aegagrus hircus) among agro-ecological zones and swimming performance and shape in Creek Chub (Semotilus atromaculatus) due to urbanization [18–21]. Such intraspecific phenotypic variation can be the result of genetic [22] or plastic variation [23–25].
Stream zonation is an outgrowth of the river continuum concept, which suggests that as streams move from their headwaters to their mouths, they differ in many environmental variables [26]. Across a stream continuum (i.e., across zones) there are multiple environmental variables that vary including: substrate size, stream width, depth, flow volume, gradient, and water velocity, as well as biotic variables such as prey type and availability [27]. Each of these variables may contribute to shape differences observed between fish from different stream zones. Of these variables, water velocity has been demonstrated as a strong predictor of intraspecific variation in shape in fishes [28]. Typically, high-velocity environments favor a narrower body shape, whereas low-velocity environments favor a more robust body shape [28]. This general response has been well documented in many fishes including centrarchids [29], characids [30], cichlids [31], cyprinids [32] and salmonids [33]. Although velocity is typically considered the primary selective agent in these studies, it is often difficult to separate water velocity from the other, usually covarying, variables that differ between stream zones.
In addition to variation in shape in response to the environment, an organism’s shape changes over the course of development [34,35]. Since D’Arcy Wentworth Thompson’s influential book, On Growth and Form [36], ontogenetic shape change has been well documented among invertebrates: crustaceans [37] and insects [38]; as well as vertebrates: reptiles [39], birds [40] and mammals [41]. Most fishes hatch or are born several orders of magnitude smaller in size compared to adults. Because of this dramatic change in body size as they grow, fish occupy multiple niches over the course of their ontogenetic development, and they can experience different selective pressures within each sequential niche [42]. Often associated with these ontogenetic niche shifts are similarly dramatic ontogenetic shape changes [43–45]. Generally, juveniles have larger eyes and heads relative to body size; whereas, adults have smaller eyes and heads relative to body size [46,47]. Studies from numerous fish taxa have documented similar shape changes [43–45,47,48]. Although many studies have addressed the change in form over developmental stages in organisms with reference to allometry [46,49], few studies have addressed how differing selective environments interact with ontogenetic patterns to produce phenotypic variation within species [50].
The potential interaction between environment and ontogenetic shape trajectories in fishes has been quantified in relatively few studies. In the sexually dimorphic livebearer, Brachyraphis rhabdophora, males exhibited parallel ontogenetic shape trajectories such that shape differences between juveniles and adults were maintained between predation environments. However, females exhibited convergent ontogenetic shape trajectories such that shape differences were more pronounced in juvenile females compared to adult females between predation environments [51]. Similarly, three-spined sticklebacks (Gasterosteus aculeatus) exhibited differential ontogenetic shape trajectories between two marine (with different habitat structure) and one freshwater habitat resulting in morphologically distinct adults [52] (Also see [53–58]). Taken together, these studies provide evidence that the interaction between environmental variation and ontogeny could result in differential shape trajectories within species. However, few studies have specifically quantified the interaction between water velocity environment across the ontogenetic shape trajectory in fishes.
In this paper we characterize shape variation in Trichomycterus areolatus across ontogeny in high-velocity and low-velocity stream environments. Trichomycterus areolatus is a freshwater catfish found throughout Central Chile. It is a small (up to 140 mm standard length), generalist, benthic carnivore that feeds mostly on insect larvae and crustaceans [59–61]. Trichomycterus areolatus is a good candidate for studying the potential interactive effect of water velocity environment on ontogenetic shape trajectories because they are one of the most broadly distributed species in Chilean rivers and streams, and they occur in all water velocity environments (i.e., stream zones) [26]. Furthermore, all size classes of T. areolatus are found in all stream zones, they appear to occupy the same stream section throughout their entire lives, and there is no evidence of migration among stream sections [27]. To investigate the potential interaction between environments characterized by differences in water velocity and ontogeny (i.e. do ontogenetic shape trajectories differ between high and low-velocity environments), we used landmark-based geometric morphometrics [62] to quantify body and head shape across ontogenetic trajectories of T. areolatus in contrasting velocity environments. We document an interaction between velocity environment and ontogenetic shape variation in T. areolatus.
Materials & methods
Study site and collection
The Andalién River (Concepción province, Chile, 36.740673 S, 73.016947 W) is a small coastal drainage (48 km) that lacks geographic or reproductive barriers to gene flow (i.e., no waterfalls or other flow barriers) along its entire length. In addition, the river exhibits strong zonation patterns in habitat structure and environmental variables. The river can be divided into three distinct zones: the rhithron (higher gradient stream characterized by high current velocity, large substrate, and small stream size), the transition (with intermediate characteristics), and the potamon (lower gradient river characterized by low current velocity, small substrate and large stream size) [27]. We recognize that these stream zones differ in several ways (Table 1, modified from [26]), but these variables covary with stream velocity in predictable ways. Water velocity is most different between the transition and potamon zones, thus we group the rithron and transition zones as a high-velocity environment, and the potamon zone as a low-velocity environment. As in many studies where a continuous environment is divided into discrete segments for comparison [15,63,64], there are several other variables that potentially differ between high and low-velocity environments and that could create selective differences between environments. For this reason, we refer to these as water velocity environments and we acknowledge that other stream variables may contribute to observed variation in shape in T. areolatus.
We collected T. areolatus from the Andalién River and two of its tributary streams (Nonguén and Queule Rivers) in 2003 and 2004 using electrofishing backpack equipment. All collections were done under the auspices of Dirección de Investigación, Universidad de Concepción and the Undersecretariat of Fisheries (Collections were made before IACUC protocols were required for field studies in Chile, but we followed the Guidelines for Use of Fishes in Field Research provided by the American Society of Ichthyologists and Herpetologists, the American Fisheries Society and the American Institute of Fisheries Research Biologists [65]). Specimens were originally collected for a study comparing distribution patterns of fish assemblages in the Andalién River drainage [27]. According to guidelines in [65], we retained specimens based on population density at each location. The majority of fish were released, but a representative sample of the entire size range of the specimens was randomly retained as museum vouchers. It is these specimens retained as vouchers that form the basis of this study. Because the density of T. areolatus in the rithron zone was low, fewer specimens were retained (n = 20). Because these specimens from the rithron did not represent the full range of body sizes available in the other two zones, we combined samples from the rithron zone and the transition zone. In addition, water velocities in the rithron and transition zones were higher and more similar to each other than velocities in the potamon zone (Table 1). To determine if the inclusion of specimens collected in the rithron changed the statistical outcome or interpretation of the results, we ran the overall shape analysis with and without the samples from the rithron. Neither the statistical significance, nor the estimated least squares means of shape differed between the two analyses, so we report results from analysis of the full data set.
Trichomycterus areolatus is sexually monomorphic [66], so we did not distinguish between males and females in our sampling and analysis. We euthanized specimens with an overdose of BZ-20 (20% ethyl p-aminobenzoate) and assigned ID numbers. We preserved specimens in ethyl alcohol and measured and photographed them at Brigham Young University. We used a Canon EOS Digital Rebel XT DSLR camera with a Canon EF-S 18–55 mm f3.5–5.6 lens. Some specimens were damaged or preserved in unnatural positions such that they could not be included in the analysis. Mean sizes and size distributions were similar between high and low-velocity environments. Specimens used for the analysis of lateral body shape from high-velocity environments (n = 183) had a mean standard length of 55.2 mm (SD = 19.5 mm; range = 22.4–116.3 mm); and specimens from low-velocity environments (n = 103) had a mean standard length of 58.3 mm (SD = 23.5 mm; range = 23.5–115.1 mm). Specimens used for the analysis of head shape from high-velocity environments (n = 182) had a mean standard length of 58 mm (SD = 22 mm; range = 22.4–134.9 mm); and specimens from low-velocity environments (n = 113) had a mean standard length of 58.6 (SD = 24.3 mm; range = 23.5–138.8 mm). We photographed the right lateral view of the body, and the dorsal view of the head of each fish for morphometric analysis and included a mm-scale ruler in the photograph for scaling. Preserved specimens are deposited in the Monte L. Bean Life Science Museum at Brigham Young University in Provo, Utah, USA.
Geometric morphometrics
We used landmark-based geometric morphometrics to quantify body and head shape in T. areolatus [67]. Prior to landmarking, we meticulously reviewed digital images to confirm that each specimen was not rotated dorsally or ventrally, was straight on the dorso-ventral and anteroposterior axis, had a closed mouth, and the operculum was in a relaxed, closed position. Where possible we re-photographed specimens, but if the error could not be corrected, we removed the specimen from the analysis. Most specimens were included in both the body and head shape analysis, but a few were used in only one or the other analysis. We digitized landmarks and semi-landmarks using the program tpsDig [68]. One researcher landmarked all specimens in random order without reference to collection location (i.e., velocity environment) or body size. Two other researchers independently inspected landmarked images to confirm homologous and consistent placement of landmarks. For analysis of lateral body shape, we used 13 landmarks defined as follows: 1) rostral-most point, 2) center of eye, 3) posterior tip of operculum, 4) juncture of the ventral margin of the operculum with the ventral outline of the body, 5) vertical projection of the x-value of landmark 4 on the dorsal outline, 6) posterior tip of spine on preoperculum, 7) midpoint between landmarks 5 and 9 on the dorsal outline, 8) anterior origin of pelvic fin, 9) anterior origin of dorsal fin, 10) anterior origin of anal fin, 11) midpoint between landmarks 4 and 8 on the ventral outline, 12) dorsal projection from anterior extent of caudal fin, and 13) ventral projection from anterior extent of caudal fin. Landmarks 7 and 11 are sliding semilandmarks (Fig 1).
Landmarks used in the analysis of shape of the lateral body view of T. areolatus.
The dorsal view of the head represents a symmetrical structure, so we landmarked only the right half for analysis [69]. We used 7 landmarks defined as follows: 1) anterior extent of premaxilla at midline of head, 2) midline of head projected from point 7, 3) lateral edge of nostril, 4) medial margin of eye, 5) lateral margin of eye, 6) lateral extent of the head projected from point 5, and 7) posterior tip of opercular spine (Fig 2).
Landmarks used in the analysis of shape of the head of T. areolatus.
We generated shape variables from our landmark data using tpsRelW [70]. tpsRelW uses a generalized Procrustes analysis to remove non-shape variation (i.e., position, orientation, and scale) [71,72], and generates shape variables in the form of partial warps and uniform components (i.e., W, the weight matrix). The program then calculates a series of relative warps that result from a principal components analysis of the weight matrix [62,67,73]. We used these relative warps as our shape variables for analysis. In addition, we used centroid size (a multivariate measure of size) derived from this analysis to represent the stage of ontogenetic development. We excluded relative warps that individually accounted for < 1% of shape variation to avoid inflating the real degrees of freedom associated with analysis of shape variation [17,74]. Consequently, we used the first 12 of 22 relative warps for the body (accounting for 96.15% of total shape variation) and the first 9 of 10 relative warps for the head (accounting for 99.91% of total shape variation).
Statistical analysis
To determine the effects of velocity environment and ontogeny on shape variation in T. areolatus, we used a multivariate linear mixed model [16,17,74]. We analyzed body and head shape separately, using relative warps as the response variable. We used location (rithron/transition versus potamon) as a discrete predictor in the model to represent either high or low-velocity environments, and we used centroid size as a covariate predictor in the model to represent ontogenetic stage of development. We included the interaction between velocity environment and centroid size (ontogeny) to test for different patterns of shape variation across ontogeny between velocity environments. The multivariate linear mixed model required that the matrix of shape variables (relative warps) be vectorized such that each individual specimen was represented by 12 rows (body) or 9 rows (head) of data, and each row corresponded to one relative warp [74]. Thus, the response variable is transposed from a row in a matrix to a vector column of responses. This vectorization creates the need for an index variable that preserves the identity of specific relative warps. This index variable is used as a predictor variable in the model much like time is used as a predictor in a typical repeated measures design [15,74–76]. Relative warps are principal components, and as such they are orthogonal to each other, they have a mean of zero, and their ordination is arbitrary relative to each other. For example, individuals that would have a positive score on one component would not necessarily score positively on any other component. For this reason, the index variable, by preserving the identity of each relative warp, is necessary to test our hypotheses of shape differences among groups. Thus, it is the two-way interactions between velocity environment and the index variable, and centroid size and the index variable, and the three-way interaction between velocity environment, centroid size, and the index variable that allow us to test the hypothesis of significant shape differences between velocity environments across ontogeny on all relative warps simultaneously [51,74,75,77]. We included individual ID number as a random effect in our analysis because each specimen had multiple shape variables (i.e., relative warps) as response variables. We estimated degrees of freedom using the Kenward–Roger method [78] and conducted analyses using Proc MIXED in SAS (SAS version 9.4, SAS Institute Inc., Cary NC, USA). To determine which relative warps differed across ontogeny and between velocity environments, we plotted least squares means and associated 95% confidence intervals for small and large individuals separately in both velocity environments.
To quantify the magnitude and direction of shape change between velocity environments over ontogeny we used a phenotypic change vector analysis (PCVA) [79–81]. Because PCVA requires two categorical variables to form the two vectors that are compared, we used size at maturity (51 mm SL) [66] to divide the sample between juveniles and adults, and then divided the adults into small adults and large adults by dividing the size range of adults in half (adults ranged in size from 51mm to 139 mm, dividing line between small adults and large adults = 103 mm SL) [66]. We used juveniles as the small size class and large adults as the large size class to characterize the PCVA across the entire size range. The PCVA tests for differences in the magnitude and/or direction of ontogenetic shape change between velocity environments across all relative warps used in the analysis. We tested for significant differences in magnitude and direction of shape change between small and large individuals in different velocity environments using ASReml-R version 4 [82] using modified R [83] scripts from [74,84].
To visualize shape variation between velocity environments at small and large sizes we calculated divergence vectors as described in [85,86]. These divergence vectors characterize differences in shape across all relative warps between velocity environments for small and large size classes separately. We calculated the divergence vector as the sum of the products of the first eigenvector (from a principal components analysis of the least squares means for each relative warp in the two velocity environments) times the associated relative warp scores for each individual. We then used these divergence scores for each individual as a regressor on shape in tpsRegr [87] to generate a thin-plate spline visualization of the extremes of shape variation between velocity environments. These thin-plate spline plots of shape deformation represent shape divergence across all relative warps between velocity environments. Data used for all analyses are available in the Dryad Digital Repository (doi:10.5061/dryad.rn8pk0p8f).
Results
Body shape of T. areolatus (right lateral view) differed significantly by centroid size (over ontogeny), and between velocity environments, and centroid size and velocity environment exhibited a significant interaction (see the two-way and three-way interaction with the index variable in Table 2). Ontogenetic shape change in the body was mainly associated with relative warp 1, with minor contributions from relative warps 4, 5, and 6. Shape differences associated with velocity environment were mainly evident on relative warp 1, with minor contributions from relative warps 5, 6, 8, and 10 (Fig 3). The magnitude of shape change of the body (p = 0.0024), but not the direction (p = 0.3889) differed significantly between velocity environments. Fish from the high-velocity environment had a significantly lower magnitude of shape change over ontogeny compared to fish from the low-velocity environment (DHigh = 0.0339, DLow = 0.0494,). Correspondingly, the change in shape over ontogeny in the high-velocity environment mainly involves a slight reduction in the proportional length of the head relative to the body and a slight deepening of the body in the midsection (Fig 4, right side). In contrast, the change in shape over ontogeny in the low-velocity environment includes a substantial reduction in the proportional length of the head relative to the body and a substantial narrowing of the body in the midsection (Fig 4, left side). In addition, shape differs between high-velocity and low-velocity environments at both ends of the ontogenetic spectrum (Fig 3). Smaller T. areolatus from the low-velocity environment had proportionally longer heads and deeper bodies and heads (dorsoventrally) compared to specimens from the high-velocity environment (Fig 4, upper); whereas, larger T. areolatus from the low-velocity environment had proportionally shorter heads compared to specimens from the high-velocity environment (Fig 4, lower).
Least squares means (error bars represent 95% confidence intervals of the mean) for each of 12 relative warps from the multivariate linear mixed model of body shape variation of T. areolatus. High-velocity environment is represented by closed circle symbols and solid connecting lines, and low-velocity environment is represented by open circle symbols and dashed connecting lines. Small and large ontogenetic stages are represented by centroid sizes of 35.00 and 150.00, respectively.
Thin plate spline deformations of divergence in body shape between high-velocity and low-velocity environments for large ontogenetic stage and small ontogenetic stage. Vertical arrows represent the direction of ontogenetic shape change from small to large. Horizontal arrows represent divergence between velocity environments.
Head shape of T. areolatus (dorsal view) differed significantly over ontogeny (centroid size), between velocity environments, and ontogeny and velocity environment exhibited a significant interaction (see the two-way and three-way interaction with the index variable in Table 2). Ontogenetic shape change in the head was associated with relative warps 1, 2, 3, 5, and 6. Shape differences in the head associated with velocity environment were evident on relative warps 1–7 (Fig 5). The direction of shape change of the head (p = 0.0024), but not the magnitude (p = 0.0886) differed significantly between velocity environments. The multivariate direction of the ontogenetic trajectory of head shape differed by 47.63° between velocity environments. This difference in direction of the ontogenetic trajectory of head shape between velocity environments represents a crossing norm of reaction in that relative warp scores for the large and small ends of the ontogenetic trajectory alternate in sign or magnitude between high and low-velocity environments (warps 1–6; Fig 5). Visually, the change in shape over ontogeny in the low-velocity environment involves a substantial reduction in head width and an especially marked reduction in relative eye size (Fig 6, left side). In contrast, the change in shape over ontogeny in the high-velocity environment involves an increase in head width and a slight elongation of the head anterior of the eye (Fig 6, right side). Head shape differs between high-velocity and low-velocity environments at both ends of the ontogenetic spectrum (Fig 5). Smaller T. areolatus from the high-velocity environment had narrower heads, and smaller eyes compared to small specimens from the low-velocity environment (Fig 6, upper); whereas, larger T. areolatus from the high-velocity environment had broader and longer heads, compared to specimens from the low-velocity environment (Fig 6, lower).
Least squares means (error bars represent 95% confidence intervals of the mean) for each of 9 relative warps from the multivariate linear mixed model of head shape variation of T. areolatus. The high-velocity environment is represented by closed circle symbols and solid connecting lines, and the low-velocity environment is represented by open circle symbols and dashed connecting lines. Small and large ontogenetic stages are represented by centroid sizes of 5.00 and 20.00, respectively.
Thin plate spline deformations of divergence in head shape between high-velocity and low-velocity environments for large ontogenetic stage and small ontogenetic stage. Vertical arrows represent the direction of ontogenetic shape change from small to large. Horizontal arrows represent divergence between velocity environments.
Discussion
Velocity environments differentially shape the ontogenetic trajectory of shape in T. areolatus. Two patterns emerge from our data that inform how these two velocity environments differentially affect ontogenetic shape trajectories. First, in both head and body, differences in shape exist between environments at the smallest ontogenetic sizes. This pattern is similar to that observed in B. rhabdophora between high and low-predation environments—even the smallest individuals were divergent in shape between environments [51]. Development of shape is highly plastic in fishes [88], and induced effects from hatchery environments are especially well documented [89]. In cases where fish shape is induced by environment, shape typically does not differ at the earliest stages of ontogenetic development (before environmental effects are manifest), but rather diverges as a consequence of time spent in the divergent environments [88]. This is not consistent with our data. However, it could be that important shape divergence between environments occurs at the larval stage or the larval to juvenile transition [89] and is thus already manifest by the smallest stage at which we sampled.
The second important pattern is that the magnitude of overall shape change in both body and head is substantially lower in fish from the high-velocity environment compared to fish from the low-velocity environment. This suggests that shape at all stages may be more constrained in the high-velocity environment. Higher water velocities, along with other potentially selective effects, produce more convergent forms relative to environments with lower water velocities [90]. Where interactive effects have been identified in determining shape of fishes, one environmental effect is often more constraining than the other, thus creating conditions for significant interactions [17]. For example, Utah chub (Gila atraria) exhibit less variation in shape in response to diet in high predation environments, compared to low predation environments, suggesting that predation constrains fish shape more than diet [17]. Similarly, female B. rhabdophora from high predation and low predation environments converge in shape as adults, apparently in response to the demands of pregnancy on shape. Thus, pregnancy exerts a stronger effect on shape than does predation in females of this species [51]. In T. areolatus, high-velocity environments appear to constrain shape to a greater extent than low-velocity environments.
Multiple variables differ between velocity environments (i.e., stream zones [27]), and it is not clear from our data which of these variables are most important in determining shape variation over ontogeny. However, most studies that report differences in shape of stream fishes based on differences in environments focus on variation in stream velocity or surrogate variables such as stream gradient or flow rate [28–32]. Effects of water velocity are well documented [29–33]. Generally, narrower body and head shapes are favored in high-velocity environments which require steady swimming, whereas robust body and head shapes are favored in low-velocity environments which require unsteady swimming [28,91]. Our results were consistent with this pattern across the ontogenetic stages we sampled. T. areolatus sampled from high-velocity environments had narrower bodies and heads than T. areolatus sampled from low-velocity environments, and the general shape of body and head changed relatively little in the high-velocity environments. Overall, water velocity seems to be a likely constraint on variation in shape in the high-velocity environment, but water velocity appears to be relatively less of a constraint in its effect on shape in the low-velocity environment.
Generally, juvenile fish have larger heads (relative to body size) and narrower bodies, whereas adults have smaller heads (relative to body size) and more robust bodies [92–95]. Although proportional size of the head in T. areolatus changes over ontogeny consistent with the pattern observed in other studies, body shape does not become more robust with increasing size. This pattern of narrow body shape in adults may be associated with the benthic nature of T. areolatus, and changes in habitat use over ontogeny. Body shape of T. areolatus is convergent with body shape of other taxa that inhabit the benthic environment in high-velocity systems [90]. It may be that species that inhabit the hyporheic environment in high-velocity environments are constrained in shape such that more robust body forms may be selected against because of the small size of openings available in the substrate. A comparison of ontogenetic shape trajectories among these convergent species may lend support to this idea [90].
The presence of shape variation between velocity environments within the Andalién River is surprising, given the relatively small size of the river (48 km) and the apparent lack of geographic or reproductive barriers to gene flow (i.e., no waterfalls or other flow barriers that would preclude movement between velocity environments). With no evidence of genetic isolation between velocity environments, the observed morphometric variation is unlikely to be based on underlying genetic differences. It is more likely an example of phenotypic plasticity in response to environmental conditions [24,25], but much of the induced difference must occur during the larval to juvenile transition at smaller sizes than we sampled. A common-garden experiment covering all sizes (larvae to adult) would be needed to directly address this question [96].
Acknowledgments
We thank the undergraduate and graduate students at Brigham Young University and the Universidad de Concepción that helped collect, measure, and photograph the fish. We thank Jillian Campbell for landmarking the photos and preparing the data for analysis.
References
- 1. Casatti L, Castro RMC. Testing the ecomorphological hypothesis in a headwater riffles fish assemblage of the Rio Sao Francisco, Southeastern Brazil. Neotrop Ichthyol. 2006;4(2):203–14. WOS:000239040600006.
- 2. Bock WJ. Concepts and methods in ecomorphology. J Biosci. 1994;19(4):403–13. WOS:A1994PW58500006.
- 3. Bhat A. Ecomorphological correlates in tropical stream fishes of southern India. Environmental Biology of Fishes. 2005;73(2):211–25.
- 4. Motta P, Kotrschal K. Correlative, experimental, and comparative evolutionary approaches in ecomorphology. Netherlands Journal of Zoology. 1992;42(2–3):400–15.
- 5. Cattau CE, Fletcher RJ, Kimball RT, Miller CW, Kitchens WM. Rapid morphological change of a top predator with the invasion of a novel prey. Nature Ecology & Evolution. 2018;2(1):108–15. WOS:000426514800018. pmid:29180705
- 6. Marchand LJ, Tarayre M, Dorey T, Rantier Y, Hennion F. Morphological variability of cushion plant Lyallia kerguelensis (Caryophyllales) in relation to environmental conditions and geography in the Kerguelen Islands: implications for cushion necrosis and climate change. Polar Biol. 2021;44(1):17–30.
- 7. Pergams ORW, Lawler JJ. Recent and Widespread Rapid Morphological Change in Rodents. PLOS ONE. 2009;4(7):e6452. pmid:19649284
- 8. Chivers DP, Zhao XX, Brown GE, Marchant TA, Ferrari MCO. Predator-induced changes in morphology of a prey fish: The effects of food level and temporal frequency of predation risk. Evol Ecol. 2008;22(4):561–74. WOS:000256963300005.
- 9. Hugueny B, Pouilly M. Morphological correlates of diet in an assemblage of West African freshwater fishes. Journal of Fish Biology. 1999;54(6):1310–25.
- 10. Webb PW. Body Form, Locomotion and Foraging in Aquatic Vertebrates. American Zoologist. 1984;24(1):107–20.
- 11. Phillips BL, Shine R. Adapting to an invasive species: Toxic cane toads induce morphological change in Australian snakes. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(49):17150–5. pmid:15569943
- 12. Blasina G, Molina J, Cazorla AL, de Astarloa JD. Relationship between ecomorphology and trophic segregation in four closely related sympatric fish species (Teleostei, Sciaenidae). C R Biol. 2016;339(11–12):498–506. WOS:000387441300007. pmid:27562196
- 13. Pakkasmaa S, Piironen J. Water velocity shapes juvenile salmonids. Evol Ecol. 2000;14(8):721–30. WOS:000170783200004.
- 14. Hendry AP, Taylor EB, McPhail JD. Adaptive divergence and the balance between selection and gene flow: Lake and stream stickleback in the misty system. Evolution. 2002;56(6):1199–216. WOS:000176820900011. pmid:12144020
- 15. Meyers PJ, Belk MC. Shape variation in a benthic stream fish across flow regimes. Hydrobiologia. 2014;738(1):147–54. WOS:000340479400011.
- 16. Mercer M, Searle PC, Cifuentes R, Habit E, Belk MC. Morphometric Response of Galaxias maculatus (Jenyns) to Lake Colonization in Chile. Diversity. 2020;12(6):13. WOS:000551690100001.
- 17. Williams TJ, Johnson JB, Belk MC. Interaction between predation environment and diet constrains body shape in Utah chub, Gila atraria (Cypriniformes: Cyprinidae). Biol J Linnean Soc. 2017;122(1):147–56. WOS:000409213700011.
- 18. Taylor-Cox ED, Macgregor CJ, Corthine A, Hill JK, Hodgson JA, Saccheri IJ. Wing morphological responses to latitude and colonisation in a range expanding butterfly. PeerJ. 2020;8:29. WOS:000590404900004. pmid:33240660
- 19. Kaliontzopoulou A, Carretero MA, Llorente GA. Intraspecific ecomorphological variation: linear and geometric morphometrics reveal habitat-related patterns within Podarcis bocagei wall lizards. J Evol Biol. 2010;23(6):1234–44. WOS:000277710100011. pmid:20406345
- 20. Ofori SA, Hagan JK, Kyei F. Morphometric characterization and differentiation of West African Dwarf goat populations in Ghana. Tropical Animal Health and Production. 2021;53(1):69. pmid:33398459
- 21. Kern EMA, Langerhans RB. Urbanization Alters Swimming Performance of a Stream Fish. Frontiers in Ecology and Evolution. 2019;6(229).
- 22.
Stearns S. The Evolution of Life Histories: New York: Oxford University Press; 1992.
- 23. Nonaka E, Svanback R, Thibert-Plante X, Englund G, Brannstrom A. Mechanisms by which phenotypic plasticity affects adaptive divergence and ecological speciation. Am Nat. 2015;186(5):E126–E43. WOS:000363928900003. pmid:26655782
- 24. Fitzpatrick BM. Underappreciated consequences of phenotypic plasticity for ecological speciation. International Journal of Ecology 2012;2012:1–12.
- 25. West-Eberhard MJ. Phenotypic plasticity and the origins of diversity. Annu Rev Ecol Syst. 1989;20:249–78. WOS:A1989CA83100011.
- 26. Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE. The river continuum concept. Can J Fish Aquat Sci. 1980;37(1):130–7.
- 27. Habit E, Belk M, Victoriano P, Jaque E. Spatio-temporal distribution patterns and conservation of fish assemblages in a Chilean coastal river. Biodiversity and Conservation. 2007;16(11):3179–91. WOS:000248910700011.
- 28. Langerhans RB. Predictability of phenotypic differentiation across flow regimes in fishes. Integrative and Comparative Biology. 2008;48(6):750–68. WOS:000262760700006. pmid:21669830
- 29. Brinsmead J, Fox MG. Morphological variation between lake- and stream-dwelling rock bass and pumpkinseed populations. Journal of Fish Biology. 2002;61(6):1619–38. WOS:000181220000023.
- 30. Sidlauskas B, Chernoff B, Machado-Allison A. Geographic and environmental variation in Bryconops sp. cf. melanurus (Ostariophysi: Characidae) from the Brazilian Pantanal. Ichthyological Research. 2006;53(1):24–33.
- 31. Langerhans RB, Layman CA, Langerhans AK, Dewitt TJ. Habitat-associated morphological divergence in two Neotropical fish species. Biol J Linnean Soc. 2003;80(4):689–98. WOS:000187247200010.
- 32. Langerhans RB, Chapman LJ, Dewitt TJ. Complex phenotype-environment associations revealed in an East African cyprinid. J Evol Biol. 2007;20(3):1171–81. WOS:000245989600033. pmid:17465926
- 33. McLaughlin RL, Grant JWA. Morphological and behavioural differences among recently-emerged brook charr, Salvelinus fontinalis, foraging in slow- vs. fast-running water. Environmental Biology of Fishes. 1994;39(3):289–300. WOS:A1994NA68400007.
- 34. Strelin MM, Cosacov A, Chalcoff VR, Maubecin CC, Sérsic AN, Benitez-Vieyra SM. The role of ontogenetic allometry and nonallometric flower shape variation in species-level adaptive diversification–Calceolaria polyrhiza (Calceolariaceae) as a case study. Evol Dev. 2020;n/a(n/a):e12363. pmid:33372721
- 35. López-Romero FA, Klimpfinger C, Tanaka S, Kriwet J. Growth trajectories of prenatal embryos of the deep-sea shark Chlamydoselachus anguineus (Chondrichthyes). Journal of Fish Biology. 2020;97(1):212–24. pmid:32307702
- 36.
Thompson DW. On growth and form: Cambridge Univ. Press; 1942. 116 pp. p.
- 37. Ocampo EH, Spivak ED, Baeza JA, Luppi TA. Ontogenetic changes in the external anatomy of the parasitic castrator crab Calyptraeotheres garthi: implications for the timing of host colonization and sexual behaviour. Biol J Linnean Soc. 2017;120(1):54–74. WOS:000400943400004.
- 38. Gottardo M, Vallotto D, Beutel RG. Giant stick insects reveal unique ontogenetic changes in biological attachment devices. Arthropod Structure & Development. 2015;44(2):195–9. pmid:25601633
- 39. Monteiro LR, Cavalcanti MJ, Sommer HJS III. Comparative ontogenetic shape changes in the skull of Caiman species (Crocodylia, Alligatoridae). Journal of Morphology. 1997;231(1):53–62. https://doi.org/10.1002/(SICI)1097-4687(199701)231:1<53::AID-JMOR5>3.0.CO;2-P. pmid:29852629
- 40. de la Hera I, Pulido F, Visser ME. Longitudinal data reveal ontogenetic changes in the wing morphology of a long-distance migratory bird. Ibis. 2014;156(1):209–14. https://doi.org/10.1111/ibi.12112.
- 41. Hernandez G, Garcia S, Vilela JF, de la Sancha NU. Ontogenetic variation of an omnivorous generalist rodent: the case of the montane akodont (Akodon montensis). J Mammal. 2017;98(6):1741–52. WOS:000417241500023.
- 42. Claessen D, Dieckmann U. Ontogenetic niche shifts and evolutionary branching in size-structured populations. Evolutionary Ecology Research. 2002;4:189–217.
- 43. Lima-Junior SE, Goitein R. Ontogenetic diet shifts of a Neotropical catfish, Pimelodus maculatus (Siluriformes, Pimelodidae): An ecomorphological approach. Environmental Biology of Fishes. 2003;68(1):73–9. WOS:000185646800009.
- 44. Rodriguez-Mendoza R, Munoz M, Saborido-Rey F. Ontogenetic allometry of the bluemouth, Helicolenus dactylopterus dactylopterus (Teleostei: Scorpaenidae), in the Northeast Atlantic and Mediterranean based on geometric morphometrics. Hydrobiologia. 2011;670(1):5–22. WOS:000291222700002.
- 45. Baliga VB, Mehta RS. Ontogenetic allometry in shape and flexibility underlies life history patterns of labrid cleaning behavior. Integrative and Comparative Biology. 2016;56(3):416–27. WOS:000381708600005. pmid:27252204
- 46. Gould SJ. Allometry and size in ontogeny and phylogeny. Biol Rev. 1966;41(4):587–638. pmid:5342162
- 47. Ahnelt H, Sauberer M, Ramler D, Koch L, Pogoreutz C. Negative allometric growth during ontogeny in the large pelagic filter-feeding basking shark. Zoomorphology. 2020;139(1):71–83. WOS:000514996200006.
- 48. Merigoux S, Ponton D. Body shape, diet and ontogenetic diet shifts in young fish of the Sinnamary River, French Guiana, South America. Journal of Fish Biology. 1998;52(3):556–69. WOS:000072711500009.
- 49. Shea BT. Ontogenetic scaling of skeletal proportions in the talapoin monkey. J Hum Evol. 1992;23(3):283–307. https://doi.org/10.1016/S0047-2484(05)80004-1.
- 50. Grünbaum T, Cloutier R, Mabee PM, Le François NR. Early developmental plasticity and integrative responses in arctic charr (Salvelinus alpinus): effects of water velocity on body size and shape. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution. 2007;308B(4):396–408. pmid:17358017
- 51. Hassell EMA, Meyers PJ, Billman EJ, Rasmussen JE, Belk MC. Ontogeny and sex alter the effect of predation on body shape in a livebearing fish: Sexual dimorphism, parallelism, and costs of reproduction. Ecology and Evolution. 2012;2(7):1738–46. pmid:22957177
- 52. Pistore AE, Barry TN, Vanderzwan SL, Schutz H, Rogers SM, Jamniczky HA. The role of genetic and environmental background driving ontogenetic trajectories of skeletal variation in the threespine stickleback (Gasterosteus aculeatus L.). Evolutionary Ecology Research. 2019;20(1):27–50.
- 53. Parsons KJ, Sheets HD, Skulason S, Ferguson MM. Phenotypic plasticity, heterochrony and ontogenetic repatterning during juvenile development of divergent Arctic charr (Salvelinus alpinus). J Evol Biol. 2011;24(8):1640–52. WOS:000292699200002. pmid:21599773
- 54. Svanbäck R, Eklöv P. Effects of habitat and food resources on morphology and ontogenetic growth trajectories in perch. Oecologia. 2002;131(1):61–70. pmid:28547511
- 55. Landaeta MF, Bernal-Duran V, Castillo MI, Diaz-Astudillo M, Fernandez-General B, Nunez-Acuna P. Nearshore environmental conditions influence larval growth and shape changes for a temperate rocky reef fish. Hydrobiologia. 2019;839(1):159–76. WOS:000476499300011.
- 56. Arnqvist G, Johansson F. Ontogenetic reaction norms of predator-induced defensive morphology in dragonfly larvae. Ecology. 1998;79(6):1847–58. WOS:000075752700001.
- 57. Hjelm J, Svanbäck R, Byström P, Persson L, Wahlström E. Diet-dependent body morphology and ontogenetic reaction norms in Eurasian perch. Oikos. 2001;95(2):311–23.
- 58. Dunn NR, O’Brien LK, Closs GP. Phenotypically induced intraspecific variation in the morphological development of wetland and stream Galaxias gollumoides McDowall and Chadderton. Diversity. 2020;12(6):19. WOS:000551688400001.
- 59. Chara JD, Baird DJ, Telfer TC, Rubio EA. Feeding ecology and habitat preferences of the catfish genus Trichomycterus in low-order streams of the Colombian Andes. Journal of Fish Biology. 2006;68(4):1026–40. WOS:000236718200004.
- 60. Scott S, Pardo R, Vila I. Trophic niche overlap between two Chilean endemic species of Trichomycterus (Teleostei: Siluriformes). Revista Chilena De Historia Natural. 2007;80(4):431–7. WOS:000252317900004.
- 61. Habit E, Belk MC, Tuckfield RC, Parra O. Response of the fish community to human-induced changes in the Biobio River in Chile. Freshwater Biology. 2006;51(1):1–11. WOS:000233834400001.
- 62. Rohlf JF, Marcus LF. A revolution in morphometrics. Trends in Ecology & Evolution. 1993;8(4):129–32.
- 63. Kern EMA, Langerhans RB. Urbanization drives contemporary evolution in stream fish. Global Change Biology. 2018;24(8):3791–803. pmid:29700897
- 64. Johnson JB, Belk MC. Predation environment predicts divergent life-history phenotypes among populations of the livebearing fish Brachyrhaphis rhabdophora. Oecologia. 2001;126(1):142–9. WOS:000166243500016. pmid:28547433
- 65. Nickum JG. Guidelines for Use of Fishes in Field Research. Fisheries. 1988;13(2):1–62.
- 66. Manriquez A, Huaquin L, Arellano M, Arratia G. Reproductive aspects of Trichomycerus areolatus Valenciennes, 1846 (Pisces, Teleostei, Siluriformies) in Angostura River, Chile. Stud Neotrop Fauna Environ. 1988;23(2):89–102. WOS:A1988Q403800004.
- 67.
Bookstein FL. Morphometric tools for landmark data: Geometry and biology: Cambridge University Press; 1991.
- 68.
Rohlf FJ. tpsDig: Digitize landmarks & outlines from image files, scanner, or video. Stony Brook, NY: Department of Ecology and Evolution, State University of New York at Stony Brook; 2003.
- 69. Rohlf FJ, Loy A, Corti M. Morphometric Analysis of Old World Talpidae (Mammalia, Insectivora) Using Partial-Warp Scores. Syst Biol. 1996;45(3):344–62.
- 70.
Rohlf FJ. tpsRelw32: Relative warps analysis. Stony Brook, NY: Department of Ecology and Evolution, State University of New York at Stony Brook; 2003.
- 71. Rohlf FJ, Slice D. Extension of the procrustes method for the optimal superimposition of landmarks. Systematic Zoology. 1990;39(1):40–59. WOS:A1990DP85800004.
- 72. Rohlf FJ. The tps series of software. Hystrix, the Italian Journal of Mammalogy. 2015;26(1):9–12.
- 73. Bookstein FL. Principal warps—Thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Mach Intell. 1989;11(6):567–85. WOS:A1989U674900003.
- 74. Roth-Monzón AJ, Belk MC, Zuniga-Vega JJ, Johnson JB. Beyond pairwise interactions: Multispecies character displacement in Mexican freshwater fish communities. Am Nat. 2020;195(6):983–96. WOS:000537567400006. pmid:32469659
- 75. Ingley SJ, Billman EJ, Belk MC, Johnson JB. Morphological divergence driven by predation environment within and between species of Brachyrhaphis fishes. PLoS ONE. 2014;9(2):11. WOS:000332389000147. pmid:24587309
- 76. Heins DC, Baker JA. Stream-flow environment predicts divergent life history phenotypes among populations of the Blacktail Shiner Cyprinella venusta: Temporal stability of a large-scale pattern. Ecology of Freshwater Fish. 2018;27(1):453–9. WOS:000417191100040.
- 77. Wesner JS, Billman EJ, Meier A, Belk MC. Morphological convergence during pregnancy among predator and nonpredator populations of the livebearing fish Brachyrhaphis rhabdophora (Teleostei: Poeciliidae). Biol J Linnean Soc. 2011;104(2):386–92.
- 78. Kenward MG, Roger JH. Small sample inference for fixed effects from restricted maximum likelihood. Biometrics. 1997;53(3):983–97. pmid:9333350
- 79. Adams DC, Collyer ML. Analysis of character divergence along environmental gradients and other covariates. Evolution. 2007;61(3):510–5. pmid:17348916
- 80. Collyer ML, Adams DC. Analysis of Two-State Multivariate Phenotypic Change in Ecological Studies. Ecology. 2007;88(3):683–92. pmid:17503596
- 81. Adams DC. Character displacement via aggressive interference in Appalachian Salamanders. Ecology. 2004;85(10):2664–70. https://doi.org/10.1890/04-0648.
- 82.
Butler DG, Cullis BR, Gilmour AR, Gogel BJ, R. T. ASReml-R Reference Manual Version 4. Hemel Hempstead, United Kingdom: VSN International Ltd; 2018.
- 83.
R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020.
- 84. Billman EJ, Rasmussen JE, Creighton JC, Johnson JB, Belk MC. A multivariate approach to the analysis of within lifetime variation in life history. Methods Ecol Evol. 2014;5(8):797–805. https://doi.org/10.1111/2041-210X.12211.
- 85. Langerhans RB. Trade-off between steady and unsteady swimming underlies predator-driven divergence in Gambusia affinis. J Evol Biol. 2009;22(5):1057–75. pmid:21462405
- 86. Langerhans RB, Makowicz AM. Shared and unique features of morphological differentiation between predator regimes in Gambusia caymanensis. J Evol Biol. 2009;22(11):2231–42. pmid:20069725
- 87.
Rohlf FJ. tpsRegr: Multivariate regression of shape onto one or more independent variables. Stony Brook, NY: Department of Ecology and Evolution, State University of New York at Stony Brook; 2003.
- 88. Wimberger PH. Plasticity of fish body shape. The effects of diet, development, family and age in two species of Geophagus (Pisces: Cichlidae). Biol J Linnean Soc. 1992;45(3):197–218.
- 89. Belk MC, Benson LJ, Rasmussen J, Peck SL. Hatchery-induced morphological variation in an endangered fish: a challenge for hatchery-based recovery efforts. Can J Fish Aquat Sci. 2008;65(3):401–8.
- 90.
Helfman G, Collette BB, Facey DE, Bowen BW. Special habitats and special adaptations. The diversity of fishes: Biology, evolution, and ecology: John Wiley & Sons; 2009.
- 91.
Langerhans RB, Reznick DN. Ecology and evolution of swimming performance in fishes: Predicting evolution with biomechanics. In: Domenici P, Kapoor BG, editors. Fish Locomotion: An Eco Ethological Perspective. Enfield: Science Publisher; 2009. p. 200–48.
- 92. Bravi R, Ruffini M, Scalici M. Morphological variation in riverine cyprinids: a geometric morphometric contribution. Ital J Zoolog. 2013;80(4):536–46. WOS:000327469300010.
- 93. Bernal-Duran V, Landaeta MF. Feeding variations and shape changes of a temperate reef clingfish during its early ontogeny. Sci Mar. 2017;81(2):205–15. WOS:000403554400007.
- 94. Villares GA, Goitein R. Morphological aspects in the ontogeny of Salminus hilarii Valenciennes, 1850 (Ostaryophysi: Characidae). Braz J Biol. 2016;76(4):905–11. WOS:000387656700013. pmid:27143050
- 95. Reis RE, Zelditch ML, Fink WL. Ontogenetic allometry of body shape in the Neotropical catfish Callichthys (Teleostei: Siluriformes). Copeia. 1998;(1):177–82. WOS:000071900500020.
- 96. Rader RB, Belk MC, Shiozawa DK, Crandall KA. Empirical tests for ecological exchangeability. Animal Conservation. 2005;8(3):239–47. Epub 2005/08/26.