Abstract
Sprinting and jumping ability are key performance measures that have been widely studied in vertebrates. The vast majority of these studies, however, use methodologies that lack an ecological context by failing to consider the complex habitats in which many animals live. Because successfully navigating obstacles within complex habitats is critical for predator escape, running, climbing, and/or jumping performance are each likely to be exposed to selection. In the present study, we quantify how behavioural strategies and locomotor performance change with increasing obstacle height. Obstacle size had a significant influence on behaviour (e.g. obstacle crossing strategy, intermittent locomotion) and performance (e.g. sprint speed, jump distance). Jump frequency and distance increased with obstacle size, suggesting that it likely evolved because it is more efficient (i.e. it reduces the time and distance required to reach a target position). Jump angle, jump velocity, and approach velocity accounted for 58% of the variation in jump distance on the large obstacle, and 33% on the small obstacle. Although these variables have been shown to significantly influence jump distance in static jumps, they do not appear to be influential in running (dynamic) jumps onto a small obstacle. Because selection operates in simple and complex habitats, future studies should consider quantifying additional measures such as jumping or climbing with respect to the evolution of locomotion performance.
Introduction
Sprint performance has been extensively studied in vertebrates as a result of its ecological relevance for gathering food and avoiding predators (Huey & Stevenson, 1979; Arnold, 1983). However, most studies have been conducted on flat, uniform trackways (Goodman, 2009; Husak, Fox & Van Den Bussche, 2008). In nature, terrestrial vertebrates navigate through complex habitats that contain highly variable terrain (e.g. rocky outcrops, woody debris, shrubs with many branches, etc.). In complex environments, animals must avoid or overcome obstacles and/or move intermittently to effectively escape predators or capture prey (Kohlsdorf & Biewener, 2006; Olberding, McBrayer & Higham, 2012). The ability for small vertebrates such as lizards to quickly overcome obstacles by jumping or other means likely influences fitness as a result of its involvement in foraging, territory defence, and predator escape (Pounds, 1988; Garland & Losos, 1994; Irschick & Losos, 1999). Thus, these complex environments can lead to differential selection on locomotor ability and potentially to habitat occupancy. Understanding how animals perform ecologically relevant tasks can expose how selection has shaped the evolution of behaviour and performance (Olberding et al., 2012). Unfortunately knowledge of how (and when) animals modulate their behaviour and performance to negotiate obstacles in complex habitats is lacking.
Animals possess a range of behaviours (i.e. a behavioural repertoire) to negotiate obstacles and move about their environment (Garber & Pruetz, 1995; Pace & Gibb, 2011). Depending on the organism and the environment, this repertoire could consist of (but is not limited to) walking, sprinting, pausing, hopping, jumping, flying, quadrupedal running, and/or bipedal running. Many non-avian terrestrial vertebrates are quadrupedal and use sprawling gaits; thus, they walk and run with their body parallel to the substrate (Reilly & Delancey, 1997). As a result of this posture, even relatively small obstacles can be visually and physically obtrusive. Lizards have served as a model organism for the study of locomotion for decades (Huey & Hertz, 1984; Garland & Losos, 1994; Vanhooydonck & Van Damme, 2001; Husak, Fox & Van Den Bussche, 2008). In particular, lizards have radiated in many complex habitats (deserts, rainforests, rock outcrops, etc.) and have demonstrated abilities to climb, run bipedally or jump over obstacles (Kohlsdorf & Navas, 2007; Schuett, Reiserer & Earley, 2009; Higham, Korchari & McBrayer, 2011). Running (quadrupedally or bipedally), climbing, and jumping over obstacles are likely most relevant for small quadrupeds trying to escape predators, and have been observed in previous studies of obstacle negotiation for lizards (Kohlsdorf & Biewener, 2006). However, very little is known regarding the frequency of each of these behaviours and how they might change as lizards approach obstacles of varying heights, especially large obstacles that reduce their visual field.
Bipedal locomotion is one particular strategy that may enhance the visual field of small quadrupeds as they negotiate obstacles (Kohlsdorf & Biewener, 2006). It has been hypothesized that bipedal locomotion (including obligate and facultative) has evolved at least six times within vertebrates (Snyder, 1962). In each case, there is either an advantage over quadrupedal locomotion, or the front limbs are co-opted for some other function (e.g. flight in birds, tool use in humans, etc.; Howell, 1944; Bennett, 1985). Because forelimbs in lizards are adapted for quadrupedal locomotion, it is not clearly understood why facultative bipedalism has evolved in multiple lizard clades (Clemente et al., 2008).
Numerous animals use jumping to overcome obstacles. Jumping performance has been widely studied in an array of vertebrates, including primates (Peters & Preuschoft, 1984; Demes, 1995), squirrels (Scheibe & Essner, 2000; Essner Jr, 2002, 2007), cats (Harris & Steudel, 2002), frogs (Emerson, 1978; Lutz & Rome, 1994, 1996; Marsh & Johnalder, 1994; Wilson, Franklin & James, 2000; Wilson, 2001; Gomes et al., 2009; Essner et al., 2010; Reilly & Jorgensen, 2011), and lizards (Toro, Herrel & Irschick, 2004; Kohlsdorf & Navas, 2007). In most studies, subjects are induced to jump from a motionless state. High-speed cameras or force platforms are utilized to quantify important jump variables (e.g. take-off angle, acceleration, etc.) as the animal leaps off of a take-off platform. In nature, animals also jump or hurdle obstacles as they encounter them during a run. Hurdling, or jumping over obstacles when running, has received little attention in the literature, although see Daley & Biewener (2011). Kohlsdorf & Biewener (2006) showed that lizards altered limb kinematics (e.g. angle, motion) and behavioural strategies when crossing obstacles of varying heights, although they did not measure sprinting and jumping ability preceding the obstacle.
Although the relevance of climbing over obstacles has received little attention, Kohlsdorf & Biewener (2006) found that Sceloporus malachiticus used climbing more than jumping or bipedal locomotion to negotiate relatively small obstacles (e.g. 0.8 cm, 1.8 cm, and 3.8 cm). On larger obstacles, lizards should favour bipedal locomotion or jumping because climbing is presumably slower. Climbing requires an animal to travel greater distances than jumping and likely requires more deceleration than negotiating an obstacle by stepping onto or over it. Both jumping and bipedal locomotion elevate the centre of mass, which is critically important for rapidly getting over the obstacle (Olberding et al., 2012).
In addition to obstacle-crossing strategies, intermittent locomotion is an important component of the behavioural repertoire of an animal. It is likely important for chasing or stalking prey, as well as predator avoidance (Vasquez, Ebensperger & Bozinovic, 2002). However, intermittent locomotion may increase energy expenditure as a result of repeated bouts of acceleration/deceleration, while at the same time aiding in fatigue recovery (Kramer & McLaughlin, 2001). Obstacle crossing likely has time and energetic demands that may cause animals to pause and evaluate other travel routes. Because obstacles are common in complex habitats, it is possible that the size of obstacles may influence an animal's decision to move intermittently. Understanding the frequencies at which animals alter behaviour on obstacles of various sizes can provide insight into how habitat composition influences behavioural decisions. In turn, these behavioural strategies can increase understanding of the conditions under which animals alter their sprinting and/or jumping performance as a result of obstacles.
In the present study, we investigated the effect of obstacle size on locomotor performance. An obstacle was defined as any physical obstruction (e.g. rock, log, leaf litter, etc.) that hinders locomotion. We quantify both sprinting and jumping performance of the Florida scrub lizard (Sceloporus woodi Stejneger 1918) as they run towards obstacles of varying heights. Although sprinting and jumping ability have been extensively studied, scant information exists on the relationship between them or relative to negotiating obstacles, although see Stefanyshyn & Nigg (1998). We test the following hypotheses: (1) as obstacle height increases, obstacle-crossing strategies will favour jumping and intermittent locomotion; (2) as obstacle height increases, lizards will increase jump distance but decrease sprint performance; and (3) if running jumps are similar to stationary jumps, then jump angle and velocity should accurately predict jump distance in running lizards.
Material and Methods
Study animals
Sceloporus woodi was chosen as the study species because this species uses flat, sandy areas in which they commonly sprint to flee from predators. Their habitat preferences range from relatively open sand pine-scrub where they are highly terrestrial, to longleaf pine where they are semi-arboreal. In both habitats, lizards are frequently observed jumping onto (and over) obstacles such as downed wood or coarse woody debris, during feeding and when escaping predators (Williams, 2010).
Fifty adult, male lizards [50.6 ± 0.55 mm; range = 45–57 mm snout–vent length (SVL)] were captured via noose from six sites (three sand pine-scrub, three longleaf pine) in the Ocala National Forest (ONF), FL, from April to June 2009. Williams (2010) showed that males from scrub sites and longleaf sites did not differ morphologically; thus, we consider the sample of males included in the present study to represent the range of genetic variation available for this species. Lizards were taken to Georgia Southern University and housed in 10-gallon glass aquaria with a loose sandy substrate. Heat lamps created a gradient of temperatures from 32–41 °C and ultraviolet lighting provided a 12 : 12 light/dark cycle. Lizards were fed vitamin-dusted crickets three times weekly and sprayed with water daily.
Obstacle performance trials
Performance trials began on the day after arriving at the facility. A jump arena (length 90 cm, width 20 cm, height 61 cm; acrylic side walls) was constructed to film locomotion trials. To mimic natural conditions, we used a packed sandy substrate. Although minimal slippage was apparent in a few trials, lizards were able to sprint and jump with ease. Logs with diameters of 5.70 and 9.55 cm were cut to the width of the arena to serve as obstacles. A third obstacle (diameter 15.90 cm) was also used initially but, in trials, 17 out of 20 lizards attempted to hide under or run around it, and thus it was discarded. Logs with diameters of 5.70 and 9.55 cm were chosen because they are common throughout our sites in the ONF, and S. woodi have been observed negotiating obstacles of this size. Prior to the trials, lizards were warmed to their field active body temperature (35 °C) for a minimum of 30 min. Upon removal from the incubator, warmed lizards were placed immediately in the jump arena, 38 cm from the obstacle, and chased toward the obstacle by tail tapping or hand waving once the lizards had initiated locomotion (Fig. 1). Although the environment and jump arena were slightly cooler than 35 °C, each trial lasted < 5 s; thus, lizards could not have cooled to the point that their locomotor performance was affected. A distance of 38 cm was chosen because other studies have shown that lizards can reach near maximum velocity (Huey & Hertz, 1984), and acceleration (McElroy & McBrayer, 2010) within 30–40 cm.
Illustration of the test arena for performance trials (not shown to scale). A full trial description is provided within the Material and Methods.
Illustration of the test arena for performance trials (not shown to scale). A full trial description is provided within the Material and Methods.
Trials were filmed at 300 frames s−1 using two Casio EXILIM EX-F1 cameras. One camera was placed above the jump chamber (dorsal view), whereas the other was placed in lateral view. Lizards were run five to ten times on each obstacle size over a 5-day period with a minimum of 2 h of rest between trials. Individuals were not tested more than twice on each sized obstacle per day. All trials were classified as either ‘successful’ or ‘unsuccessful’. ‘Unsuccessful’ trials (e.g. lizard attempted to hide under the obstacle) were only used in analysis of intermittent locomotion. ‘Successful’ trials were those in which the lizard ended the trial at any location on or beyond the obstacle. Upon review of the video (see below), successful trials were further separated into three obstacle-crossing strategies: climbing, jumping or bipedal locomotion. Jumping required that all limbs were airborne during the transition between the substrate and the obstacle, and that the airborne phase exceeded the individual's SVL. Bipedal locomotion required that the lizard take a minimum of three steps in which the front limbs were not touching the substrate immediately preceding the obstacle. The number of pauses (i.e. intermittent locomotion) occurring when the lizard approached the obstacle was also recorded. We defined a pause as an event in which the lizard decelerated to a point of zero velocity in all directions.
Video analysis
Only successful trials in which lizards jumped onto the obstacle, never paused or ran into the sides of the jump arena were used in subsequent analyses of performance. Dorsal and lateral trimmed videos were imported into DLTDATAVIEWER3 software (Hedrick, 2008). A landmark painted on the lizard's snout was used to manually digitize the positional data from each frame and thus generate three-dimensional coordinate data from the video. A quintic spline function (GCVSPL software; Woltring, 1986) was used to smooth to the output coordinate data and calculate the instantaneous velocities for each frame. Because minimal movement occurred in the y- and z-planes during the lizard's approach, mean velocity, maximum velocity, and maximum acceleration were calculated using x-values only.
Jump distance was quantified as the distance between the lizard's snout and the face of the obstacle at toe-off (i.e. the last frame where a toe could be visualized touching the substrate) during take-off (Fig. 2A). Mean sprint velocity was calculated as the mean of all smoothed instantaneous velocities during the approach to the obstacle. Maximum sprint velocity and acceleration were calculated as the peak instantaneous values reached during the approach obtained from smoothed data coordinates. Jump velocity was calculated by averaging instantaneous velocities over the eight frames (26.66 ms) prior to toe-off. This time frame was chosen because, for all trials, eight frames were most representative of the entire take-off phase (Bels et al., 1992; Toro et al., 2004). To calculate jump angle, three markers were digitized in each camera view to represent the three vertices of a right triangle (Fig. 2B) (Lutz & Rome, 1996). Steps were numbered sequentially as one hind foot contacted the substrate until the opposite hind foot made contact. Although only minimal slippage was apparent on the video, force and power calculations were not made; any slippage would bias those estimates.
A, jump distance was measured as the distance between the lizard's snout and the face of the obstacle at toe-off during take-off. B, a point was digitized on the lizard's snout (a), another at the substrate directly below the lizard's snout (b), and a third at the substrate behind the lizard directly in line with the angle of the body (c). Jump angle was calculated by dividing the arcsine of the line segment ab by segment ac.
A, jump distance was measured as the distance between the lizard's snout and the face of the obstacle at toe-off during take-off. B, a point was digitized on the lizard's snout (a), another at the substrate directly below the lizard's snout (b), and a third at the substrate behind the lizard directly in line with the angle of the body (c). Jump angle was calculated by dividing the arcsine of the line segment ab by segment ac.
Statistical analysis
We quantified differences in obstacle-crossing strategy (climb, jump, bipedal) and intermittent locomotion between obstacles. All successful trials, including multiple runs from each individual, were used to define the behavioural repertoire. We used contingency analysis to test for the effect of obstacle size on the frequency of behavioural strategies and to compare the frequency of intermittent locomotion between obstacles (both successful and unsuccessful trials). To quantify locomotor performance, only trials in which the lizard jumped onto the obstacle, and did not pause or run into the sides of the arena, were used. If lizards had multiple trials that fit these criteria, only the trial with the longest jump distance was retained. Student's t-tests were used to analyze step frequency, jump distance, jump velocity, jump angle, mean velocity, and maximum velocity between obstacles. A Mann–Whitney U-test was used to test for differences in maximum acceleration. Mean sprint velocity, jump velocity, and jump angle were placed in a multiple regression analysis to predict jump distance (square-root transformed). Multiple linear regressions showed that lizard body size (SVL) did not have a significant influence on measures of sprint and jump performance. Lizards with broken tails were not used in any analyses. Analyses were conducted using JMP, version 8 (SAS Institute) and values are presented as the mean ± SEM.
Results
Behaviourial repertoire
Lizards successfully negotiated the small obstacle in 88% of trials compared to only 52% for the large obstacle (χ2 = 92.09, P < 0.01, N = 610). The obstacle-crossing strategy used differed significantly by obstacle size (χ2 = 17.79, P < 0.01, N = 419). Lizards jumped more often onto the large obstacle but climbed and used bipedal locomotion more often on the small obstacle (Fig. 3). When jumping trials were removed from the analysis, there was no significant effect of obstacle size on the frequency of climbing versus bipedal locomotion (χ2 < 0.01, P = 0.98, N = 170). Intermittent locomotion increased with obstacle size (χ2 = 33.93, P < 0.01, N = 611; Table 1).
Frequencies of obstacle-crossing strategies in Sceloporus woodi. Behaviour was influenced by obstacle size (χ2 = 17.79, P = 0.001, N = 419), principally as a result of the increase in jumping frequency on the large obstacle.
Frequencies of obstacle-crossing strategies in Sceloporus woodi. Behaviour was influenced by obstacle size (χ2 = 17.79, P = 0.001, N = 419), principally as a result of the increase in jumping frequency on the large obstacle.
The degree of intermittent locomotion (number of times a lizard paused) was counted for each trial and found to be significantly different between obstacles (χ2 = 33.93, P < 0.0001, N = 611)
| Obstacle size | Number of pauses on approach to obstacle | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Trials | |
| Small | 101 | 113 | 49 | 18 | 5 | 0 | 1 | 1 | 288 |
| Large | 60 | 122 | 86 | 37 | 10 | 3 | 5 | 0 | 323 |
| Obstacle size | Number of pauses on approach to obstacle | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Trials | |
| Small | 101 | 113 | 49 | 18 | 5 | 0 | 1 | 1 | 288 |
| Large | 60 | 122 | 86 | 37 | 10 | 3 | 5 | 0 | 323 |
The number of trials for which lizards paused between zero and seven times is shown.
The degree of intermittent locomotion (number of times a lizard paused) was counted for each trial and found to be significantly different between obstacles (χ2 = 33.93, P < 0.0001, N = 611)
| Obstacle size | Number of pauses on approach to obstacle | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Trials | |
| Small | 101 | 113 | 49 | 18 | 5 | 0 | 1 | 1 | 288 |
| Large | 60 | 122 | 86 | 37 | 10 | 3 | 5 | 0 | 323 |
| Obstacle size | Number of pauses on approach to obstacle | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Trials | |
| Small | 101 | 113 | 49 | 18 | 5 | 0 | 1 | 1 | 288 |
| Large | 60 | 122 | 86 | 37 | 10 | 3 | 5 | 0 | 323 |
The number of trials for which lizards paused between zero and seven times is shown.
Sprint and jump performance
Lizards ran faster towards small obstacles (Fig. 4). Sprint velocities were slower for the large obstacle (0.95 ± 0.05 m s−1) than for the small obstacle (1.11 ± 0.04 m s−1; t = 2.68, P = 0.01, N = 34). Maximum sprint velocities averaged 1.45 ± 0.06 m s−1 for the large obstacle and 1.59 ± 0.05 m s−1 for the small obstacle (t = 1.70, P = 0.09, N = 34). Maximum acceleration was greater for the small obstacle (77.00 ± 5.64 m s–2) than the large obstacle (54.50 ± 6.34 m s−2; U = 215, P = 0.01, N = 34). Lizards jumped significantly farther onto the large obstacle (7.44 ± 0.65 cm) than the small obstacle (4.25 ± 0.58 cm; t = −3.42, P < 0.01, N = 34; Fig. 4). Jump velocity did not significantly differ between obstacles (t = 1.17, P = 0.25, N = 34). Jump angle increased for the large obstacle (49.9 ± 2.9°) compared to the small obstacle (37.4 ± 2.6°; t = −3.23, P < 0.01, N = 34).
Box plots comparing sprint and jump performance on large and small obstacles. All performance variables measured were significantly different (P ≤ 0.05) between obstacles except for maximum velocity and jump velocity. Although not significantly different, these two variables followed the pattern of higher velocity on the small obstacle. The box margins indicate the 25th and 75th percentiles. The median (solid) and mean (dashed) are represented with each. Whiskers indicate the 90th and 10th percentiles. Outliers are indicated individually by dots.
Box plots comparing sprint and jump performance on large and small obstacles. All performance variables measured were significantly different (P ≤ 0.05) between obstacles except for maximum velocity and jump velocity. Although not significantly different, these two variables followed the pattern of higher velocity on the small obstacle. The box margins indicate the 25th and 75th percentiles. The median (solid) and mean (dashed) are represented with each. Whiskers indicate the 90th and 10th percentiles. Outliers are indicated individually by dots.
The multiple regression analysis indicated that jump angle, jump velocity, and approach velocity, differed in importance between obstacles. The model explained 58.3% of the variation in jump distance onto the large obstacle (Table 2). Lower jump angle had the greatest effect on increased jump distance, with jump velocity and mean sprint velocity having similar effects. For the small obstacle, however, the model only explained 32.6% of the variation in jump distance. Mean velocity was most predictive, followed by jump velocity and jump angle.
Results of a multiple regression of locomotor variables as predictors of jump distance
| Variable | N | β | t | P |
|---|---|---|---|---|
| Large obstacle | ||||
| Angle | 15 | −0.767 | −3.94 | 0.001* |
| Jump velocity | 15 | 0.141 | 0.65 | 0.531 |
| Approach velocity | 15 | −0.101 | −0.51 | 0.618 |
| Small obstacle | ||||
| Angle | 19 | −0.090 | −0.46 | 0.650 |
| Jump velocity | 19 | −0.579 | −1.96 | 0.069 |
| Approach velocity | 19 | 0.961 | 3.24 | 0.006* |
| Variable | N | β | t | P |
|---|---|---|---|---|
| Large obstacle | ||||
| Angle | 15 | −0.767 | −3.94 | 0.001* |
| Jump velocity | 15 | 0.141 | 0.65 | 0.531 |
| Approach velocity | 15 | −0.101 | −0.51 | 0.618 |
| Small obstacle | ||||
| Angle | 19 | −0.090 | −0.46 | 0.650 |
| Jump velocity | 19 | −0.579 | −1.96 | 0.069 |
| Approach velocity | 19 | 0.961 | 3.24 | 0.006* |
The adjusted R2 values were 0.583 (large obstacle) and 0.326 (small obstacle).
Statistically significant (P ≤ 0.05).
Results of a multiple regression of locomotor variables as predictors of jump distance
| Variable | N | β | t | P |
|---|---|---|---|---|
| Large obstacle | ||||
| Angle | 15 | −0.767 | −3.94 | 0.001* |
| Jump velocity | 15 | 0.141 | 0.65 | 0.531 |
| Approach velocity | 15 | −0.101 | −0.51 | 0.618 |
| Small obstacle | ||||
| Angle | 19 | −0.090 | −0.46 | 0.650 |
| Jump velocity | 19 | −0.579 | −1.96 | 0.069 |
| Approach velocity | 19 | 0.961 | 3.24 | 0.006* |
| Variable | N | β | t | P |
|---|---|---|---|---|
| Large obstacle | ||||
| Angle | 15 | −0.767 | −3.94 | 0.001* |
| Jump velocity | 15 | 0.141 | 0.65 | 0.531 |
| Approach velocity | 15 | −0.101 | −0.51 | 0.618 |
| Small obstacle | ||||
| Angle | 19 | −0.090 | −0.46 | 0.650 |
| Jump velocity | 19 | −0.579 | −1.96 | 0.069 |
| Approach velocity | 19 | 0.961 | 3.24 | 0.006* |
The adjusted R2 values were 0.583 (large obstacle) and 0.326 (small obstacle).
Statistically significant (P ≤ 0.05).
For jumping trials, obstacle size had no effect on the number of steps taken to reach the obstacle (large obstacle: 7.40 ± 0.31; small obstacle: 7.68 ± 0.36; t = 0.58, P = 0.56, N = 34). The step at which maximum sprint velocity was reached was also not significantly different between the large and small obstacles (large obstacle: 5.13 ± 0.42; small obstacle: 5.95 ± 0.52; t = 1.18, P = 0.25, N = 34). However, a comparison between total number of steps until toe-off and the step at maximum velocity demonstrates that maximum velocity is reached approximately two steps prior to take-off (small obstacle: t = 2.76, P = 0.01, N = 38; large obstacle: t = 4.34, P < 0.01, N = 30). Hence, lizards accelerate to reach their maximal velocity two steps prior to their anticipated take-off position when jumping onto an obstacle.
Discussion
Although sprint and jump performance have been widely investigated, in the present study, we quantify how obstacle negotiation might influence these abilities. We add insight to previous studies by quantifying the behavioural repertoire used in obstacle crossing, by examining the effect of obstacle size on locomotor performance, and by quantifying intermittent locomotion. By using relatively large obstacles (i.e. equivalent or greater than body length), we were able to examine the potential significance of bipedal locomotion to negotiate obstacles. Here, we show that obstacle size has substantial impacts on behaviour and performance; bipedal locomotion is potentially useful for increasing the visual field, and running jumps are not easily characterized by variables important for static jumping performance.
Behavioural repertoire
Similar to previous studies, three obstacle-crossing strategies were used to negotiate obstacles: climb, jump or bipedal locomotion (Kohlsdorf & Biewener, 2006). The results obtained also show that obstacle-crossing strategy is highly dependent upon obstacle height and that jumping frequency increases with obstacle size. We hypothesize that increased jump frequency on larger obstacles is beneficial because it reduces the amount of time to reach the target position (Higham, Davenport & Jayne, 2001). Assuming lizards jump at 45° and initiate take-off at a distance equal to the obstacle's height, then, to climb over a 10-cm obstacle, a lizard would travel a total distance of 20 cm to complete this task (10 cm horizontally, 10 cm vertically). If the lizard instead jumps in a straight line from a distance of 10 cm, it will only travel 14.1 cm to reach the top of the obstacle, reducing the distance travelled by almost 6 cm. The distance (and/or time) saved by jumping instead of climbing increases linearly with obstacle size (as long as the animal can jump to a height equal to the linear distance away from the obstacle). Even on small obstacles, it is plausible that jumping is beneficial because jump frequency (51%) is much greater than climbing frequency (20%; Fig. 3). Climbing an obstacle (principally a large obstacle) has an additional disadvantage because it requires a high degree of deceleration to transition from horizontal to vertical running. Although we have identified some deceleration associated with jumping as well (see below), it is likely less impactful than the deceleration caused by climbing. Reducing the distance needed to overcome the obstacle and, in turn, the amount of time, would have the benefit of a more rapid escape from a predator, which would directly increase survival. Furthermore, climbing locomotion is associated with increased intermittent locomotion (Higham et al., 2011), which again, would increase the time to cross the obstacle and allow for closer approach of a predator. To verify these predictions, future work should quantify whether climbing and jumping do indeed differ in velocity and time to cross obstacles of varying heights.
The evolutionary cause (or ecological advantage) of facultative bipedalism is presently debated. Hypotheses suggested include: (1) bipedal running provides an energetic advantage (Snyder, 1952); (2) bipedal running enables lizards to reach higher speeds over quadrupedal locomotion (Snyder, 1962); (3) high forward accelerations cause the front of the body to pitch upward resulting in bipedal locomotion (Aerts et al., 2003; Clemente et al., 2008); and (4) bipedal locomotion is beneficial for improving environmental perception and raising the centre of mass in preparation for encountering an obstacle (Kohlsdorf & Biewener, 2006; Olberding et al., 2012). The present study shows that bipedal locomotion was used more frequently than climbing on both obstacle sizes, indicating it is an important behavioural strategy in crossing obstacles. Although it is unlikely that any one hypothesis explains bipedalism in all lizards, our experimental design suggests that hypothesis (4) has merit. If so, then employing a bipedal running posture may be under selection for animals living in complex environments.
If bipedal locomotion has evolved in part to enable lizards to increase their visual field, then this would only be advantageous if the height of the obstacle is less than that of the lizard. In the present study, maximum lizard height (i.e. length; SVL + femur + tibia/fibia + metatarsus) was in the range 6.87–9.02 cm (7.83 ± 0.77 cm). This range suggests that it would be possible for all lizards in the present study to see over the small obstacle (5.70 cm) when running bipedal (i.e. limbs adducted to raise the front of the body and the pelvis). However, none of the lizards in our sample would be able to see over the large obstacle (9.55 cm). This may explain why S. woodi uses bipedal locomotion more on the small obstacle (30.6%) than the large obstacle (16.8%). We suggest that facultative bipedalism could have arisen in species inhabiting complex environments via exaptation or co-opting a pre-existing trait for a new function (Gould & Lewontin, 1979). Even if bipedal posture arose as a result of large accelerations that cause the body to pitch upward, bipedal locomotion still is likely to enhance environmental perception over obstacles. Bipedal postures may allow lizards to see refugia or what lies beyond the obstacle. A bipedal posture also raises the centre of mass and hips such that animals can prepare for stepping onto or over the obstacle. This would be especially helpful when used at low speeds where lizards would have to actively select this gait, rather than it existing as a byproduct of high acceleration capacity (Clemente et al., 2008). Regardless of speed over the obstacle, quickly getting on or over obstacles functions to directly affect individual fitness because it plays a vital role in predator evasion in complex habitats. Those species that can employ bipedal running may have higher survivorship or may be able to persist in (or invade) complex (or cluttered) habitats.
Habitat complexity may also contribute to the prevalence of intermittent locomotion (Higham et al., 2011). Although many potential benefits of intermittent locomotion (e.g. fatigue recovery, improved detection of prey, etc.) have been proposed (Avery et al., 1987; Higham et al., 2001; Kramer & McLaughlin, 2001), an additional hypothesis is that moving intermittently contributes to increased time to search out additional travel routes. As shown in the present study, lizards are less likely to cross obstacles of increasing size, although we did not give them an alternative route to choose to navigate the obstacle. Yet, our design is biologically relevant; often, large downed branches or trees are encountered and lizards must climb, jump, hide or seek another route around such high or long obstacles. Every lizard in our sample successfully negotiated the large obstacle at least once; thereby demonstrating that unsuccessful trials were not the result of an inability to climb or jump onto it but, rather, a ‘preference’ not to do so. Olberding et al. (2012) showed that, in 87% of trials using bipedal locomotion to cross an obstacle, lizards did not maintain their bipedal gait after crossing an obstacle. Lizards stumble, fall or return to a quadrupedal gait, each of which disrupts locomotion. We speculate that intermittent locomotion provides time to look for alternative routes when encountering obstacles because animals seek to avoid a hazard that is likely to cause a fall. Future choice experiments should be conducted to examine the frequency of intermittent locomotion when alternative pathways are present.
Sprint and jump performance
In combination with increased intermittent locomotion, reduced sprint performance for the large obstacle reveals that S. woodi is hesitant about negotiating larger obstacles. Lizards reached significantly higher mean velocities and maximum accelerations when approaching a smaller obstacle, and maximum velocity trended towards the same result (P = 0.09). In all but two trials, maximum acceleration was reached in the first two steps of the trial or the final two steps before jumping. For the former case, this high initial acceleration likely coincides with escape from the researcher (predator), whereas the latter instance provides the burst of speed necessary to jump onto the obstacle.
Although little is known regarding the similarities and/or differences between stationary and running jumps, variables that have been shown to be predictive of jump performance are jump angle, velocity, acceleration, force, and power (Emerson, 1978; Wilson, 2001; Toro et al., 2004; Toro, Herrel & Irschick, 2006). Certain variables (e.g. jump acceleration) become increasingly difficult to quantify during running jumps as a result of the lack of a comparative starting point to stationary jumps. We focused on take-off angle and velocity (two common and important predictors of jump distance; Emerson, 1985; Marsh & Johnalder, 1994) in the multiple regression analysis to predict jump distance. Furthermore, mean velocity was added to investigate whether approach velocity preceding the take-off contributes to jump distance.
In the present study, it is evident that for a large obstacle the principle predictor of jump distance is jump angle (Table 2). Ballistic motion predicts that, if force and acceleration are constant during take-off, the optimal jump angle for achieving maximum distance is 45° (Emerson, 1985). Hence, a trade-off exists. Greater take-off angles lead to greater jump height and flight duration, whereas lower take-off angles lead to lower jump height and shorter flight duration. Anolis lizards jump at less than 45°, presumably to reduce flight time and height (Toro et al., 2004). It is interesting that S. woodi jumped at 49.9° onto a large obstacle, which is slightly higher than optimal. However, in the present study, lizards were gaining elevation following their jump [i.e. increasing the jump angle is required when the landing position (obstacle) is at a higher elevation than the take-off location]. The majority of studies investigating jumping ability have investigated animals as they jump from a platform to an object at the same or lower height (Toro et al., 2004; Burrows, 2006; James & Wilson, 2008). When jumping to a lower or higher position, which would be common in complex habitats, obstacle height has a significant effect on the angle and distance from which the subject should commence take-off (Toro et al., 2006). Our results on the large obstacle support studies of static jumping showing that jump angle is important for long jump distances.
Studies of human athletes have shown that joint movements and power patterns do not differ between stationary and running jumps (for both vertical and horizontal jumps; Stefanyshyn & Nigg, 1998). Overall, our multiple regression analysis failed to explain much the of variation in jump distance. We conclude that the variables shown to influence jump distance for static jumps are functionally different from those for running jumps. Running jumps are inherently more complex as a result of the shifting centre of mass, the dynamic motion of the limbs, and the compliant nature of most substrates (i.e. sand in the present study). Furthermore, take-off velocity changes with each footfall prior to a running jump, and often, the animal decelerates in preparation for the jump (Higham et al., 2001). We were unable to measure whole animal force and power during take-off as a result of substrate compliance, although these variables are known to influence jump performance (Marsh & Johnalder, 1994; Wilson et al., 2000). We recommend future work using a force platform and noncompliant surface to investigate these differences.
Most vertebrates live in complex habitats with an infinite array of obstacles to negotiate. We draw attention to the relevance of crossing obstacles in studies of locomotion and provide insight into how obstacle size influences animal behaviour and performance. Because prey capture, predator escape, and territory defense are crucial for survival, locomotor performance likely contributes to fitness (Garland & Losos, 1994). If performance during obstacle negotiation does indeed influence fitness, then selection should favour the evolution of behavioural strategies such as jumping and bipedal locomotion for lizards occupying complex habitats.
Acknowledgements
We would like to acknowledge the Georgia Southern University College of Graduate Studies and a Georgia Southern Phase 1 Catalyst grant to LDM for funding that supported the present study. Lizards were collected under permits from Ocala National Forest (# SEM451) and Florida Wildlife Conservation Commission (# WX07348B) to LDM. We thank N. Nasseri, R. Stiller, R. Tucker, J. O'Connor, S. Williams, and C. Collins for help with capturing lizards. We greatly appreciate feedback on the manuscript from several reviewers, and thank members of the primary author's graduate committee for help on the project: Drs J. S. Harrison and D. K. McLain. We thank Dr E. McElroy for assistance with the software used in data analysis and advice on data smoothing.
