3826 The Journal of Experimental Biology 211, 3826-3835 Published by The Company of Biologists 2008 doi:10.1242/jeb.014464
Feeding biomechanics of juvenile red snapper (Lutjanus campechanus) from the northwestern Gulf of Mexico Janelle E. Case1, Mark W. Westneat2 and Christopher D. Marshall1,* 1
Texas A&M University at Galveston, Departments of Wildlife and Fisheries Science and Marine Biology, 5007 Avenue U, Galveston, TX 77551, USA and 2Field Museum of Natural History 1400, S Lakeshore Dr., Chicago, IL 60605, USA *Author for correspondence (e-mail:
[email protected])
Accepted 6 September 2008
SUMMARY Juvenile red snapper settle across several complex habitats, which function as nurseries for young fish. Little is known about their life history or feeding biomechanics during this time. However, recent studies have shown higher growth rates for juveniles located on mud habitats adjacent to low profile reefs, perhaps because of varied prey availability and abundance. To further investigate the habitat needs of juvenile red snapper and test hypotheses of feeding development, individuals were collected from a low profile shell ridge and adjacent mud areas on Freeport Rocks, TX, USA, and divided into three size classes (≤3.9, 4.0–5.9, ≥6.0 cm SL). Output from a dynamic lever model suggested an ontogenetic shift in feeding morphology. Biomechanical modeling also predicted that off-ridge juveniles would have slower, stronger jaws compared with on-ridge juveniles. Kinematic profiles obtained from actual feeding events validated the modelsʼ predictive ability. Analysis of prey capture events demonstrated that on-ridge juveniles exhibited larger jaw displacements than off-ridge juveniles. Shape analysis was used to further investigate habitat effects on morphology. Off-ridge juveniles differed from on-ridge juveniles in possessing a deeper head and body. Results from model simulations, kinematic profiles, behavioral observations and shape analysis all compliment the conclusion that onridge juveniles exhibited more suction feeding behavior, whereas off-ridge juveniles used more biting behavior. Habitat disparity and possibly available prey composition generated variations in juvenile feeding biomechanics and behavior that may affect recruitment. Key words: biomechanics, kinematics, feeding, Lutjanus campechanus, red snapper.
INTRODUCTION
Ecomorphological studies are predicated on identifying patterns among morphology, behavioral performance and ecology (Wainwright, 1994), and have been utilized to test a variety of hypotheses concerning the relationships between feeding performance and foraging ecology among teleosts (e.g. Clifton and Motta, 1988; Wainwright, 1996). Ecomorphological studies are also useful in examining the functional consequences of ontogenetic changes on morphology and diet shifts in teleosts (e.g. Osenberg et al., 1988; Hyndes et al., 1997; Hunt von Herbing, 2001; Graeb et al., 2005; Monteiro et al., 2005). Ontogenetic shifts reduce competition through intraspecific (Hernandez and Motta, 1997; Hyndes et al., 1997; Soto et al., 1998) or interspecific (Mittelbach et al., 1992; Huskey and Turingan, 2001) resource partitioning. Furthermore, such shifts can reduce predation (Werner and Gilliam, 1984) and maximize growth rates (Olson, 1996; Post, 2003) of teleosts during early life development. Fast growth is most advantageous during larval and juvenile stages when individuals are most vulnerable to predation (Werner and Gilliam, 1984; Post, 2003). Therefore, improving a juvenile’s ability to take advantage of the most abundant or high energy food source over ontogeny may increase individual fitness and enhance recruitment potential (Olson, 1996; Persson and Brönmark, 2002; Post, 2003). Early life history studies that focus on the interaction between skull development, feeding mechanics, and their ecological consequences, are an important way to address critical questions in the ecomorphology of fishes. This study used juvenile red snapper
(Lutjanus campechanus Poey 1860), to investigate changes in skull development and feeding biomechanics to provide an ecomorphological explanation of divergent early life history patterns. Larval red snapper settle out of the water column at approximately 16 mm (Rooker et al., 2004) and are attracted to complex habitats, which serve as essential nursery grounds for juveniles (Szedlmayer and Howe, 1997). The settlement patterns within these habitats remain unclear. Significantly higher recruitment occurs on shell ridges (on-ridge) in the northeastern Gulf of Mexico (Szedlmayer and Conti, 1999) and on adjacent mud habitats (off-ridge) in the northwestern Gulf of Mexico (Rooker et al., 2004). Juvenile growth rates are significantly higher in off-ridge areas around Freeport Rocks (Rooker et al., 2004; Geary et al., 2007), suggesting that available prey resources may differ between off-ridge mud bottoms and on-ridge shell ridges. Therefore we asked, ‘Do juveniles respond to prey availability by altering feeding morphology or modulating feeding behavior?’ Although red snapper larval development (Collins et al., 1980; Pothoff et al., 1988; Drass et al., 2000) and diet of both adults and juveniles have been examined (Bradley and Bryan, 1976; Moran, 1988; Ouzts and Szedlmayer, 2003; Szedlmayer and Lee, 2004), their feeding mechanics and behavior have not been investigated. Therefore, this research explored the relationships between morphology and feeding kinematics within the context of trophic ecology of juvenile red snapper using biomechanical modeling, kinematic behavioral performance tests and shape analysis. We hypothesized that juvenile red snapper settling onto different habitats
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Juvenile red snapper feeding biomechanics
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would exhibit a divergence in skull morphology and/or feeding biomechanics that may be correlated to reported juvenile diet patterns (Szedlmayer and Lee, 2004). To test these hypotheses, we performed experiments involving juvenile red snapper collected from different habitats and carried out biomechanical modeling of their jaws. This allowed us to determine how interactions between feeding ecology and functional morphology may influence growth and settlement patterns by testing for significant differences in jaw morphology, lever mechanics, kinematics and phenotypic plasticity among juvenile red snapper across three size classes (≤3.9, 4.0–5.9, ≥6.0 cm SL) and between two nursery habitats (on-ridge and offridge). MATERIALS AND METHODS Animal collection and analyses
Juvenile red snapper were collected between June and September 2004, and in August 2005, on and off the Freeport rocks shell ridge (Freeport, TX, USA). On-ridge areas were characterized by abundant relic oyster shell; off-ridge sites were characterized by silt and mud. Juvenile red snapper (N=530) were collected using a 6-m otter trawl with 2 cm mesh, 1.25 cm inner mesh, 0.6 cm link tickler chain, and 0.457⫻0.914 m doors. Trawls were made in 5-min increments at 2.5 knots. Juveniles for kinematics studies (N=17) were sorted by habitat (on-ridge N=8 and off-ridge N=9) and kept in separate ‘live’ wells onboard the research vessel. Additional subjects were anesthetized then frozen and kept for jaw lever analyses (N=230), and shape analyses (N=111). Mass (g) and standard length (SL; cm) were recorded for all juveniles and assigned to the following size classes, small (1.8–3.9 cm SL), medium (4.0–5.9 cm SL) or large (6.0–10.88 cm SL). Collections were made under TAMU IACUC Animal Use Protocol no. 2003-84 and Texas Park and Wildlife Permit no. SPR 0902-243. Prior to conducting parametric statistical tests, normality of all data was tested using a Kolmogorov–Smirnov test. If normality was not met, data were transformed. Levene’s test was used to test the assumption of homogeneity of variances. Bonferroni post-hoc tests were used when the assumption of equal variance was met; Dunnett’s t3 post-hoc tests were used in cases where variances were heteroscedastic. All statistical tests were conducted using SPSS 11 (SPSS, Chicago, IL, USA) for a Mac and JMP 6 (SAS, Cary, NC, USA). More specific statistical analyses are listed under each methodological subheading (model of lower jaw lever mechanics, feeding kinematics, and phenotypic variation). Model of lower jaw lever mechanics
Lever mechanics were used to calculate the trade off between velocity and force (Wainwright and Richard, 1995; Westneat, 1994; Westneat, 2003), and make predictions about the feeding mode of juvenile red snapper. The biomechanics of juvenile red snapper feeding were modeled by investigating the anatomical arrangement of the lower jaw as a third order lever using the program MandibLever 3.2 (Westneat, 2003). This model incorporates the influence of closing muscles on lever ratio calculations and creates a set of dynamic output variables over the entire jaw closing. The use of a dynamic model is advantageous since static measurements usually overestimate mechanical advantage because the influence of changing muscle insertion angles is not accounted for (Westneat, 2003). The model, therefore, calculates an effective mechanical advantage (EMA), which is a more accurate measurement of force transmission from muscle to the lower jaw. The model also calculates a variety of other dynamic variables, such as bite force, angular velocity and percent muscle contraction, and these
Fig. 1. Morphometric measurements used as inputs in the jaw lever model, MandibLever 3.2.
parameters can be used to make predictions regarding fish feeding kinematics. Morphometric measurements of the lower jaw and associated jaw closing muscles (the A2 and A3 subdivisions of the adductor mandibulae; Fig. 1, Table 1) were taken to the nearest 0.01 cm using either a calibrated eye reticule on a Nikon SMZ1500 stereoscope, or with digital vernier calipers. The following 12 measurements were collected: (1) in-lever A2, from quadrate-articular joint to A2 insertion point on ascending process of articular; (2) in-lever A3, from quadrate-articular joint to A3 insertion point on medial face of lower jaw; (3) in-lever Open, from quadrate-articular joint to insertion of interoperculomandibular ligament on posteroventral margin of articular; (4) out-lever, from quadrate-articular joint to anterior most tip of dentary; (5) A2 length, from origin on ventral margin on preopercle to insertion on ascending process of articular; (6) A3 total length, from origin on preopercle and hyomandibula to insertion on medial face of lower jaw; (7) A3 tendon length, from origin on tapering end of A3 muscle to insertion on the medial face of the lower jaw; (8) A2–joint distance, distance from A2 origin to quadrate-articular joint; (9) A3–joint distance, distance from A3 origin to quadrate-articular joint; (10) A2–A3 ins, distance from A2 insertion to A3 insertion; (11) LJtop length, from the tip of the coronoid process to the anterior jaw tip; and (12) LJBot length, from the posteroventral margin of the articular to the anterior jaw tip. Mass of the A2 and A3 muscles were recorded to the nearest 0.01 g. Assumptions regarding jaw muscle contractile physiology were made following Westneat (Westneat, 2003): maximum shortening velocity, or Vmax (10 L s–1), maximum isometric stress of muscle contraction, or Pmax (200 kPa), dynamic contraction velocity of muscle (0.05–0.8 of Vmax), isometric force per unit area of muscle (0.05–0.79 of Pmax); and a peak jaw opening rotation value based on juvenile red snapper kinematic data (57°). Jaw muscle contraction percentage was calculated as the percent change in length from the open (stretched) position. Morphometric measurements and muscular assumptions were used as inputs in the biomechanical lever model, available free on the web from the second author. A total of 230 simulations of lower jaw closing were run to predict feeding
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3828 J. E. Case, M. W. Westneat and C. D. Marshall Table 1. Morphometric data used as input into the lever model, MandibLever 3.2, for juvenile red snapper from three size classes and two habitats
1. In-lever A2 (cm) 2. In-lever A3 (cm) 3. In-lever open (cm) 4. Out-lever (cm) 5. A2 length (cm) 6. A3 total length (cm) 7. A3 tendon length (cm) 8. A2-joint distance (cm) 9. A3-joint distance (cm) 10. A2-A3Ins (cm) 11. LJtop length (cm) 12. LJBot length (cm) 13. A2 mass (g) 14. A3 mass (g)
Small (N=74)
Medium (N=82)
Large (N=74)
On-ridge (N=113)
Off-ridge (N=117)
0.13±0.01 0.19±0.01 0.08±0.003 0.59±0.01 0.34±0.01 0.57±0.01 0.12±0.004 0.32±0.01 0.55±0.01 0.12±0.004 0.51±0.01 0.65±0.01 0.001±0.0001 0.001±0.0001
0.21±0.01 0.31±0.01 0.12±0.003 0.87±0.01 0.52±0.01 0.94±0.02 0.69±0.33 0.49±0.01 0.85±0.01 0.21±0.004 0.73±0.01 0.96±0.01 0.003±0.0002 0.004±0.0002
0.29±0.01 0.42±0.01 0.18±0.004 1.21±0.01 0.75±0.01 1.38±0.02 0.35±0.01 0.70±0.01 1.24±0.02 0.29±0.01 1.02±0.01 1.33±0.02 0.01±0.001 0.02±0.003
0.20±0.01 0.32±0.01 0.13±0.005 0.95±0.02 0.58±0.02 1.03±0.03 0.58±0.24 0.54±0.02 0.93±0.03 0.21±0.01 0.82±0.02 1.04±0.03 0.005±0.0004 0.01±0.002
0.22±0.01 0.29±0.01 0.12±0.004 0.83±0.03 0.49±0.02 0.90±0.03 0.22±0.01 0.46±0.02 0.83±0.03 0.20±0.01 0.69±0.02 0.92±0.03 0.003±0.0004 0.01±0.001
Values are means ± s.e.m.
behavior of juvenile red snapper from three size classes and two habitats. To test the hypothesis that there was no significant difference in the morphology of the feeding apparatus of juvenile red snapper across ontogeny, output parameters were analyzed using multivariate analyses of variance (MANOVA) with size class as a fixed factor, and model output parameters as dependent variables. Significant differences among size classes were determined by post-hoc tests. To test for significant differences between habitats, output parameters were analyzed using multivariate analyses of covariance (MANCOVA) with habitat as a fixed factor, model output parameters as dependent variables and standard length as a covariate. Feeding kinematics
Feeding kinematic trials were used to validate the predictive biomechanical model output, and compare the feeding biomechanics of juvenile red snapper across size classes and between habitats. Juvenile red snapper were transported to the laboratory and housed in habitat-specific 38–189 l saltwater tanks and maintained at 26°C, 32 p.p.t. salinity, and pH 8.2. Fish were allowed to acclimatize, and then trained to feed from a stationary tube under 500 W of light. During the first collection season, a mass mortality event occurred because of an Amyloodinium ocellateum outbreak during a hurricane evacuation. Not enough individuals were available to investigate ontogenetic changes; therefore, only a habitat treatment was included in the kinematic analysis. Juveniles used in feeding kinematic trials (on-ridge N=8, off-ridge N=9) all fell within the medium size class (4.0–5.9 cm SL). Juveniles were positioned laterally in front of the camera using a piece of Plexiglas with a 1 cm2 grid as a reference and fed pieces of squid, sized to 50% of the individual’s oral diameter, until satiated. Feeding events were recorded using a Redlake PCI Motion Scope high-speed camera at 250 frames s–1. Three representative feeding events for each juvenile were selected for analysis. Juveniles were then sacrificed with an overdose of methane tricaine sulphonate (MS222). Feeding events were digitized frame by frame, starting with the onset of strike until mouthparts returned to their starting position, using Motus 8.2 (Vicon, Denver, CO, USA). Digitized points (Fig. 2A) included: (A) the anterior tip of the premaxilla, (B) the anterior tip of the dentary, (C) the dorsal most visible point of the maxilla, (D) the maxilla–premaxilla articulation, (E) the mandible–quadrate articulation, (F) the ventral floor of mouth, (G)
Fig. 2. (A) Points used for digitizing juvenile red snapper cranial kinematics from feeding trials. (B) Landmark configuration on juvenile red snapper used in geometric morphometric analyses.
the posterior-most point of the orbit of the eye, (H) the first dorsal spine origin, (I) the anterodorsal tip of the opercle at the junction with the preopercle and the hyomandibula, (J) the posterodorsal tip of the opercle, (K) the origin of the first pectoral fin ray. These 11 anatomical landmarks were used to calculate the following 14 kinematic variables: (1) maximum gape (cm), (2) time to maximum gape (ms), (3) maximum gape angle (degrees), (4) time to maximum gape angle (ms), (5) maximum lower jaw rotation (degrees), (6) time to maximum lower jaw rotation (ms), (7) maximum upper jaw protrusion (cm), (8) time to maximum upper jaw protrusion (ms), (9) maximum cranial rotation (degrees), (10) time to maximum cranial rotation (ms), (11) maximum depression of the hyoid (cm), (12) time to maximum hyoid depression (ms), (13) maximum maxillary rotation (degrees), and (14) time to maximum maxillary rotation (ms). Angular velocities and phase timings were also calculated. Scatter plots of gape distance and gape angle versus closing duration were used to determine the predictive ability of the lever
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Juvenile red snapper feeding biomechanics model by comparing data from the lever model and live kinematics. To statistically test the model as an accurate predictor of feeding behavior, we log-transformed the gape, gape angle, and time axes to linearize the curvilinear relationships between time and kinematics, and performed analysis of covariance (ANCOVA) to test whether slopes and/or y-intercepts of the model and video data were significantly different. Kinematic variables were also used to characterize and quantify the feeding behavior of juvenile red snapper between habitats. To test the hypothesis that there was no significant difference in feeding behavior of juvenile red snapper between habitats (P≤0.05), kinematic variables were analyzed using multivariate analysis of variance (MANOVA) with habitat as a fixed factor and kinematic variables as dependent variables. Kinematic profiles were generated for each variable to examine their relationship to one another and identify different phases over a complete feeding event. Phenotypic variation
Shape variables were collected to investigate differences in body shape of juvenile red snapper from the on-ridge and off-ridge habitats. Lateral images of juvenile red snapper (on-ridge N=56, off-ridge N=55; small N=50, medium N=33, large N=28) were captured using a digital camera. Two-dimensional coordinates were recorded from the following 19 landmarks (Fig. 2B) digitized around the juvenile body perimeter using the program tpsDig (v. 2) (Rohlf, 2005a): (1) anterior tip of the dentary, (2) anterior tip of the premaxilla, (3) anterior-most point of the eye orbit, (4) center of the eye, (5) posterior-most point of the eye orbit, (6) anterior-most point of the frontal bone, (7, 8) anterior and posterior insertions of the dorsal fin, respectively, (9) dorsal origin of the caudal fin, (10) middle of caudal fin insertion where the lateral line terminates, (11) ventral origin of the caudal fin, (12, 13) posterior and anterior insertions of the anal fin, respectively, (14) anterior-most insertion of the pelvic fin, (15) first branchiostegal ray at the body outline, (16) quadrate-articular joint, (17) origin of the first pectoral fin ray, (18) posterodorsal tip of the opercle, (19) anterior-most point of the lateral line. TpsRelw software (v. 1.42) (Rohlf, 2005b) was used to align shape data by rotating, translating and scaling the landmark coordinates, using least squares superimposition. Aligned data were used to calculate shape variables. Significant variations in shape were tested using MANOVA with shape variables as dependent variables, and habitat and size as fixed variables. An eigendecomposition of the effect sum of squares and cross-products (SSCP) matrix was performed and used to calculate the shape variance explained by habitat and allometry. In addition, associated eigenvectors were multiplied by shape variables to yield linear axis scores. TpsRegr software (v. 1.31) (Rohlf, 2003) produced thin-plate spline transformation grids (Fig. 6), which provided a visualization of shape variation. RESULTS Lower jaw lever model Ontogeny
Model simulations demonstrated that for the A3 muscle effective mechanical advantage increased 3% (A2 P=0.28, A3 P=0.02, MANOVA) and velocity ratio decreased 6.7% (A2 P=0.22, A3 P
