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Principal components plotted into the ternary diagrams appear as curves as a result of the log-ratio transformation used in their computation. For the large acanthomorph dataset, we calculated Pearson's correlation coefficients using the cor. For the ram—suction species-pairs dataset, we were primarily interested in determining how different components of prey-capture strategy varied between the species in each pair. We used a nested mixed model ANOVA with species as the fixed independent effect and individual as the random independent factor, as has been done in previous studies Norton and Brainerd, Nested mixed models were carried out using the lmer function in the lme4 package in R, and numerator degrees of freedom, denominator degrees of freedom, F -statistics and P -values were calculated with the anova function in the lmerTest package.

We were unable to incorporate phylogenetic information in this analysis because of the lack of published trees including all the species in our dataset. However, we do not find reason to believe that evolutionary history has strongly biased our analysis as closely related species are not necessarily near one another in the ternary plots. We investigated the sensitivity of our PCA on representative strikes to variation in the choice of a typical strike using a resampling method and the species-pairs dataset for which we had multiple strikes per species 10—15 sequences per species, 70 sequences total.

A single video was randomly selected from each of the six species to simulate choosing a representative strike for a species. This was repeated 10, times and we performed PCA as described above to determine the loadings of the jaw ram, body ram and suction proportions on PC1 for each replicate. The resulting distributions of loadings were then compared with PC1 loadings based on species means to judge whether our results are rigorous to variation in representative strike choice. Body ram proportion ranged from 0. Thus, when considered as a proportion of the total strike distance, body ram and jaw ram had similar, large ranges 0.

The 40 species measured fill a large proportion of prey-capture space, as visualized using a ternary plot Fig. Strikes in which more than half of the strike distance was covered by suction were very rare. Prey capture diversity in suction-feeding acanthomorphs. Ternary plot showing the diversity of strike behaviors as determined by the suction proportion S , jaw ram proportion JR and body ram proportion BR that contributed to prey capture.

Suction distances are constrained across acanthomorphs, and prey-capture diversity does not follow a strict ram—suction trade-off. The first principal component represents a strong trade-off between body ram and the combined contributions of jaw ram and suction and is shown by the black curve. The second principal component is largely a trade-off in jaw ram and suction and is shown by the gray curve. The distribution of acanthomorphs yields new insights into how behavioral and morphological convergence shapes prey-capture diversity, and we have highlighted some of the examples mentioned in the Results colored circles.

Species are numbered as follows: For suction-feeding spiny-rayed fishes, principal component 1 PC1 explained PC1 therefore largely reflects the amount of body ram compared with the other strike components. Principal component 2 PC2 represents the remaining Species with smaller values on PC1 lower body ram proportions and higher combined suction and jaw ram proportions tend to have quicker strikes overall. Species are numbered as in Fig. There was variation within individuals, between individuals, and between species.

Comparison of prey capture from species pairs used as exemplars of extremes of the ram—suction continuum in previous studies. A Centrachids, Lepomis macrochirus and Micropterus salmoides ; B cichlids, Heros severus and Cichla ocellaris ; and C serranids, Serranocirrhitus latus and Epinephelus ongus.

Within each pair, circles represent the suction-dominated species and squares represent the ram-dominated species.

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Black coloration designates species means. Black curves represent the first principal component for each dataset. D Mean prey-capture proportions for each species, plotted for comparison. Nested mixed models for the centrarchid pair found that only body ram proportion was significantly different between L. PC1 for the centrarchid data explained Nest mixed models showed that there was a significant difference between L.

Cichla ocellaris and H. In the serranid pair, only body ram proportion was significantly different between the high-ram E. PC1 explained the majority of variation in the data Scores along PC1 were only marginally different between S. A PCA on the means for the six species represented in the ram—suction pairs revealed a major axis of variation for the six species that closely mirrored the results for the 40 species dataset Fig.

PC1 explained almost all variation in the dataset We compared these loadings based on species means with the distribution of loadings on PC1 from 10, resampled datasets consisting of a single representative strike for each of the six species. Although the resulting distributions see Fig. S1 are skewed and therefore not amenable to parametric significance testing, the density curves show that the majority of replicates are quantitatively similar to the loadings calculated from species means.

PC1 explained the vast majority of variation in replicates mean PC loadings are subject to qualitative interpretation, and the distributions indicate that most analyses would support a trade-off between body ram versus the combination of jaw ram and suction.

For instance, jaw ram and suction only load in opposite directions in out of 10, replicates There is some tendency for the representative datasets to underestimate the importance of jaw ram; the jaw ram peak is displaced towards zero relative to the species-mean loading Fig. S1 , green line , and there is a relatively high frequency with loadings near zero. Accordingly, the loading of suction on PC1 tends to be overestimated in the resampled data compared with the value obtained using species means Fig.

S1 , pink line. If these tendencies are true of our method in general, we would expect to be biased towards finding a strict body ram—suction trade-off when using representative strikes instead of species means. However, this is not what we found for our acanthomorph dataset. It should be noted that the variation in the distributions for jaw ram and suction is based on six species, but we would expect variation to be less if the same analysis was performed on the 40 species in our acanthomorph dataset, as a larger sample size will decrease the ability of one arbitrarily chosen strike to significantly influence the PC loadings.

Not knowing of any bias in our selection of typical strikes and based on the findings of our resampling method, we conclude that our results regarding the major axis of diversity in acanthomorphs are robust to variations in representative strike choice. The contribution of suction distance to prey capture is greatly limited compared with ram in acanthomorph fishes.

Introduction

The high-suction area of prey-capture space is unoccupied, and the highest contribution of suction to prey-capture distance exhibited by any fish in our dataset was only about half Fig. In contrast, there were strikes occupying the full range of jaw and body ram proportions. This is the largest published kinematic study to date for suction-feeding fishes in terms of family representation and number of species, and we purposefully included fishes from a range of trophic niches e.

Amongst this diversity, we found scant evidence that evolutionary innovation has surmounted the hydrodynamic constraints imposed on suction distance to bring any species into the extreme suction area of prey-capture space. Does the absence of suction-dominated strikes in our analysis reflect a constraint on suction feeding or did this feeding mode elude our investigation because it is relatively rare?

We suggest that a combination of these factors is responsible. Because suction distances are limited in this way, any forward movement of the mouth aperture during the strike by swimming or rotation of cranial linkages is likely to make a significant contribution to prey-capture distance. Suction-dominated strikes require that the body and mouth do not advance toward the prey during the strike.

One might expect to see this feeding mode in sit-and-wait predators that strike from a position resting on the substratum. However, the representatives of this feeding mode that we studied all used considerable jaw protrusion to close in on their prey see below. Because our study was limited to acanthomorphs feeding on mobile prey, it is possible that there are other taxa or prey types that could exhibit feeding strikes with high suction proportions. Jaw protrusion, while a synapomorphy of spiny-rayed fishes, is not a universal trait of suction feeders Wainwright et al.

Perhaps there are non-acanthomorph fishes or other aquatic vertebrates lacking jaw protrusion that have evolved strategies to feed on evasive prey using high proportions of suction. However, even these taxa may generate ram by sucking themselves toward the prey Summers et al. Furthermore, some of these lineages have independently evolved jaw protrusion Wilga et al. We also note that our study focused on strikes at mobile prey. When approaching prey that cannot escape, fishes can move to within less than a mouth diameter before initiating the strike, because there is no risk of disturbing the prey into an escape response.

Such a strike could potentially reach the suction-dominated region of the continuum. Our findings challenge the traditional view that a fundamental trade-off between ram and suction underlies the diversity of prey-capture behaviors in suction-feeding fishes. Across spiny-rayed fishes, PC1 represented a strong trade-off between body ram and the combined contribution of suction and jaw ram; suction and jaw ram load in the same direction and with near-equal magnitudes, such that the major axis of variation is not simply a ram—suction continuum.

Instead, variation is better described by the relative amount of body ram involved in the strike, or a continuum between low and high body ram, as confirmed by the strong correlation between PC1 and body ram proportion. Combined with the apparent lack of suction-specialized strikes, our results corroborate previous studies that questioned the role of suction in generating diversity in prey-capture distance Wainwright et al.

Simultaneously comparing the contributions of jaw ram, body ram and suction clarifies the importance of jaw ram in the diversification of prey-capture strategies among acanthomorph fishes. Body ram and jaw ram are often combined into a measurement of total ram, which implies that they function similarly and trade-off with suction in a comparable manner. However, PC1 reveals that jaw ram and suction combined trade-off with the relative amount of body ram in a strike.

This sets jaw ram apart from body ram and illustrates that jaw ram provides a separate axis along which to generate variation in prey capture. The interaction between suction and jaw ram appears to be particularly important in strikes with low contributions of body ram: We expect the synergistic effect of jaw protrusion on suction forces Holzman et al.

Indeed, many high jaw ram strikes in our dataset are from zooplanktivores and sit-and-wait predators that are known to only strike at close range. The close relationship between PC1 and time to prey capture also suggests that strikes dominated by short-range suction and jaw ram components are quicker than strikes relying more on body ram Fig. We found that some species with reputations as suction specialists due to their rapid and powerful strikes are actually relying on jaw ram more than suction or body ram to decrease the distance between their mouth and prey.

Pivot-feeding seahorses and pipefish were identified as high jaw ram feeders previously Flammang et al. In fact, trumpetfish A. In fact, all the benthic sit-and-wait predators included in our study grouped closely together in prey-capture space Fig. Although these fish are generally cryptic and may have large upturned mouths, they are morphologically and taxonomically diverse, in our dataset representing five families Antennariidae, Batrachoididae, Centrogenyidae, Scorpaenidae, Synanceiidae that have converged in kinematics. Predators like frogfish and pipefish may seem like evolutionary oddballs, but this study suggests that these are the type of fish that we should be studying to learn more about the interaction between jaw ram and the ability to produce fast, powerful suction Van Wassenbergh et al.

In contrast to suction, a combination of morphological and behavioral adaptations have allowed fish to invade the extreme jaw ram area of morphospace.

These include the slingjaw wrasse, E. At least some syngnathiforms power-amplify this pivoting motion using tendon elastic recoil Van Wassenbergh et al. However, novelty in one trait does not guarantee that a species will have extreme strikes as morphology and behavior interact to produce kinematics. This is demonstrated by the cichlid C. Therefore, adaptations for high jaw protrusion alone do not make a strike extreme.

In contrast, some benthic sit-and-wait predators and water-column zooplanktivores, such as I. Therefore, while a combination of behavior and unusual morphology are necessary for acanthomorphs to become extreme jaw ram specialists, many acanthomorph clades have achieved relatively high jaw ram prey-capture behaviors despite potential biomechanical and kinematic constraints on jaw function and strike distance. Specific pairs of closely related species were used to illustrate a trade-off in ram and suction contributions to prey capture. Even with jaw ram as a separate source of variation, we found strong evidence that species within the centrarchid and cichlid pairs fell out along a ram—suction continuum.

This is at odds with our findings from the larger sample of acanthomorph diversity where we did not recover a simple continuum between body ram and suction. We caution that focusing only on ram—suction pairs gives a skewed interpretation of the diversity of prey-capture strategies in acanthomorph fishes. By looking at a larger taxonomic and ecomorphological sample of acanthomorph suction feeders and incorporating another source of variation in prey-capture behavior, we show that the apparent ram—suction trade off in closely related pairs of fishes does not govern feeding diversity at broader evolutionary scales.

In agreement with this conclusion, PC1 for the six species averages converges on the same axis found in the large-scale acanthomorph study Fig. This suggests that as you add diversity, a strict body-ram versus suction continuum breaks down, and jaw ram and suction contributions combined trade-off with changes in body ram.

RAM Random Articles and Manuscripts - 9781589095540

Our findings highlight the importance of considering ram, especially body ram, when studying how suction-feeding fishes diversify across feeding niches on evolutionary time scales. It is worth pointing out that laboratory studies that record feeding events may greatly underestimate the maximum body ram that some species can exhibit, because laboratory feeding arenas are quite cramped compared with most natural settings. Also, methods that select for highly motivated strikes based on time to prey capture may also underestimate ram, because strikes with greater ram distances tend to increase prey-capture times despite high ram speeds Fig.

Further studies on locomotion during predator—prey interactions, and how different ram strategies affect feeding accuracy and suction performance, will be important in developing a better understanding of the diversity of prey-capture strategies Kane and Higham, , ; Rice et al. Get fast, free shipping with Amazon Prime.

Ram : Random Articles and Manuscripts by Jay Dubya (2012, Hardcover)

Your recently viewed items and featured recommendations. View or edit your browsing history. Get to Know Us. English Choose a language for shopping. Amazon Music Stream millions of songs. Amazon Drive Cloud storage from Amazon. Alexa Actionable Analytics for the Web. AmazonGlobal Ship Orders Internationally. Amazon Inspire Digital Educational Resources. In the present study we visualized the flows generated by suction-feeding bluegill sunfish using digital particle image velocimetry DPIV; Fig.

Drucker and Lauder, , , and we measured the effect of bluegill swimming speed on aspects of the induced suction flows. Depending on the question, we measured fluid speed FS in either the earth-bound, or absolute, frame of reference AFS or the fish's frame of reference FFS. We focused on the following three questions: First, does ram speed affect the maximum fluid speed entering the mouth during suction feeding, as measured in the absolute frame of reference?

We hypothesize that, if the fish is stationary, fluid speed in the absolute frame of reference AFS stationary will result exclusively from buccal cavity expansion. However, if the fish is swimming at a ram speed RS , then fluid speed at the mouth aperture in the absolute frame of reference AFS swimming will equal the predicted fluid speed if the fish were not moving AFS stationary minus the magnitude of RS.

This is because when the buccal cavity expands, water will enter the mouth passively at a speed equal to the swimming speed of the fish. We therefore expected that increases in ram speed would result in decreasing fluid speed as long as buccal expansion rate is identical. The degree of focusing Fig.

A low degree of focusing indicates water is being drawn from every direction, whereas a high degree of focusing indicates water is being drawn predominantly from in front of the mouth. We expected that, with increasing ram, the degree of focusing would increase Drost et al. The experimental setup used in this study. In order to elicit varying ram speeds at the time of capture the prey was introduced at one of three distances from the sunfish: Note that mirrors were positioned below and above the tank to reflect the laser sheet up and then down in order to illuminate both above and below the head of the fish during feeding.

Lastly, does ram speed affect the shape of the ingested volume of water, as measured in the absolute frame of reference? If water flow into the mouth becomes more focused with increasing ram speed, this should influence the dimensions of the parcel of water that is captured during a suction feeding event.

Modeling studies Drost et al. We studied the bluegill sunfish Lepomis macrochirus Rafinesque, a member of the freshwater family Centrarchidae. Bluegill have been the focus of considerable work on the functional morphology and biomechanics of suction feeding for example Lauder, ; Lauder and Clark, ; Ferry-Graham et al.

Fish were fed daily with cut squid Loligo sp. All maintenance and experimental procedures used in this research followed a protocol that was reviewed by the University of California, Davis Institutional Animal Care and Use Committee. We analyzed data from three fish with standard lengths of Note that the streamlines do not indicate the area of water ingested, but rather the instantaneous direction of movement of water at each location in space. Each bluegill was placed in the experimental tank and trained to feed in the laser sheet see below. At the onset of experiments, the individual was kept at one end of the tank and restrained behind a door Fig.

Varying locomotor speeds were elicited by introducing the prey items at one of three distances from the fish Fig. Previous work indicates that bluegill will capture prey with relatively high ram speeds when traversing distances within the range used in this set-up T. Lauder, manuscript submitted for publication. Each individual was fed at every location and the order of locations for each fish was arbitrarily chosen.

We used DPIV to quantify a number of parameters describing the flow of water into the mouth during suction feeding. Willert and Gharib provide a detailed description of this technique for measuring fluid flow. An Innova 5 W argonion continuous wave laser Coherent, Inc.

Mirrors above and below the tank were used to illuminate both above and below the head of the fish during feeding Fig. Additionally, a Sony CCD camcorder Tokyo, Japan , operating at 30 images s —1 , was used to capture anterior view images for each sequence in order to determine the orientation and position of the fish relative to the laser sheet.

While we only analyzed sequences recorded in lateral view in this study, we have found that the flow pattern generated by bluegill is radially symmetrical about the long axis of the fish Day et al. An adaptive mesh cross correlation algorithm created by Scarano and Riethmuller was used to calculate velocities from image pairs.

The distance that particles traveled between image pairs 2 ms interval was determined within interrogation windows with dimensions of 0. The algorithm then returned a two-dimensional grid of two components of measured velocity for each image pair that was processed. Two-dimensional x and y velocity vector profiles were visualized using Tecplot version 10 Amtec Engineering, Inc. In order to determine the validity of the vector measurements, a two-step validation scheme was implemented.

Only vectors with a signal-to-noise ratio SNR of 2 or greater were included in the analyses, and no smoothing was applied to the final velocity field. Some spurious measurements passed the SNR validation criterion, and the second part of the validation scheme accounted for these measurements. Measurements located two grid points away from the primary measurement location were used, because these do not overlap the primary measurement region.

If at least two of the three measurements considered had not been removed, based on the SNR criterion step one of the validation scheme , then the mean of the remaining measurements was used as the value of speed for that position along the transect. Finally, for several sequences we confirmed that measurements with an SNR of 2 were accurate by tracking particles manually for several sequences using IMAGE J version 1.

A transect extending forward from the center of the fish's mouth was studied to measure the speed of the fluid as a function of distance from the mouth. The accuracy at this position was validated in every trial.

The statistical analyses were performed only on those feedings that met the following criteria: The last point is important because the prey item can interfere with the DPIV measurements, which were made at maximum gape. Using IMAGE J, the x and y coordinates of the tip of the upper and lower jaw were digitized for each image 2 msintervals starting before the onset of mouth opening and ending after the mouth was closed. These points were used to quantify changes in gape and to calculate maximum gape for every feeding sequence. This method for measuring TTPG reduced errors that are related to a variable rate of early mouth opening and the difficulty in clearly identifying the point where the peak value is achieved in an asymptotic relationship.

TTPG was measured as an indication of the rate of buccal expansion that is used by the fish to generate suction Sanford and Wainwright, The x and y coordinates of the anterior margin of the eye were digitized and used to quantify ram speed throughout the strikes.

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The fish in A was moving at 0 cm s —1 and the fish in B was moving at Depending on the question being addressed, we either measured variables in the absolute frame of reference AF; maximum suction speed and the shape of the ingested volume of water or in the fish's frame of reference FF; the degree of focusing. For the latter, we subtracted the ram speed of the fish from each speed vector in order to visualize the flow relative to the fish's mouth and body Fig.

To determine the degree of focusing DF of water flow that was directed towards the mouth, the streamlines in the fish's frame of reference were visualized using Tecplot, and we determined the most dorsal and ventral streamlines that entered the fish's mouth. At a distance anterior to the fish equal to the fish's maximum gape, we measured the maximum vertical distance between these outermost streamlines Fig. The reciprocal of this value is defined as DF such that larger values of DF indicate a smaller vertical distance between streamlines and a flow pattern that is more focused in front of the fish.

To determine the shape of the ingested volume of water, we visually tracked particles going into the mouth using IMAGE J and drew a boundary around the outer limit of particles that entered the mouth Fig. We measured the maximum height and the length of this boundary and converted the measurements to a ratio that described the aspect ratio of the ingested volume in lateral view. All variables were first log 10 transformed to normalize variances, and in each case this allowed the variables to meet the assumptions of the parametric procedures.

We performed mixed-model multiple regressions with individual categorical, random , TTPG continuous , and ram speed continuous as the independent variables and all two-way and the three-way interaction terms, with the following dependent variables: TTPG was included as a variable in the analyses because it strongly affects the suction speed in bluegill sunfish Day et al. All P values from this second analysis are presented in Table 1.

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