DOI: 10.5061/dryad.hdr7sqvqd
title: Distinct morphological drivers of jumping and maneuvering performance in gerbils

description: Theoretically, animals with longer hindlimbs are better jumpers, while
 those with shorter hindlimbs are better maneuverers. Yet experimental
 evidence of this intuitive relationship is lacking. We experimentally
 compared jump force and maneuverability in a lab colony of Mongolian
 gerbils (Meriones unguiculatus). We hypothesized that gerbils with long
 legs (ankle to knee) and thighs (knee to hip) would produce the greatest
 jump forces, while gerbils with short legs and thighs would be able to run
 most rapidly around turns. Consistent with these hypotheses, gerbils with
 longer legs produced greater jump forces after accounting for sex and body
 mass: a 1-mm greater leg length provided 1 body-weight-unit greater jump
 force on average. Furthermore, gerbils with shorter thighs were more
 maneuverable: each 1-mm greater thigh length reduced turn speed by 5%.
 Rather than a trade-off, however, there was no significant correlation
 between jump force and turn speed. The experiments revealed how distinct
 hindlimb segments contributed in different ways to each performance
 measure: legs to jumping and thighs to maneuvering. If variation in
 jumping and maneuvering influences survival during predator encounters,
 then hindlimb segment lengths may be subject to strong natural selection.
description: <em>Jumping data</em> To test jump
 gerbil performance, we built a vertical tunnel (10x10x47-cm) using clear
 1/16-mm polycarbonate sheets, including a ~0.5-cm gap at the bottom, and
 designed to not exert weight on the ATI mini40 force plate. We placed
 gerbils in the tunnel to acclimate for 30 seconds and set the force plate
 to record data at 1,000 samples per second using Igor (v7, Wavemetrics,
 Lake Oswego, OR, USA). Each trial began when gerbils stood on four feet
 and were sprayed with compressed air to simulate surprise by ambush
 predators. We recorded videos at 700 fps using two Phantom MIRO cameras
 and Phantom Camera Control software. To increase chances of measuring
 maximum jump force, we completed 2-4 trials for 20 gerbils (N = 12 males,
 8 females); we stopped after 1 trial for 8 gerbils that exhibited stress
 (N = 2 males, 6 females). We scored each of 57 trials involving 28
 individuals as a: (<em>i</em>) ‘jump’ in which the gerbil
 pushed off the ground vertically using its hindfeet,
 (<em>ii</em>) ‘hop’ on all four feet, or
 (<em>iii</em>) any ‘other’ response. We obtained time-matched
 morphological measurements for 15/17 of the gerbils who jumped (N = 11
 males, 4 females), and the trials for which we recorded jumps are included
 in the attached dataset. We calculated maximum resultant force from the
 vector sum of forces in the x, y, and z directions and expressed this
 value in proportion to the gerbil’s mass. We low-pass filtered force plate
 data at 70 Hz to account for vibrations. Resultant force outputs were
 given in body weight units (BWU); a BWU of one is equivalent to a jump
 force of 1x body weight. We used the maximum force recorded for each
 gerbil for analysis. <em>Maneuverability
 data</em> To quantify gerbil maneuverability, we
 conducted corner-turning trials. We built polycarbonate corridors of
 increasingly difficult turn angles (135°, 90°, 45°) with a 120-cm runway
 into the turn and 80-grip black traction tape to line floors and visually
 indicate turns. Gerbils acclimated by exploring the corner and back at
 least three times before we sprayed them with compressed air to begin the
 trial. We recorded runs at 240 fps using GoPro Hero 10 Black cameras (one
 above the arena; one lengthwise along the runway). We ended up using the
 top camera view for analysis, and the tracking data from that camera are
 included in these datasets. We tested each gerbil up to three times on the
 three angles, allowing &gt;48 hours between tests and randomizing the
 order of angles. We categorized each of 226 trials across 29 individuals
 (14 male; 15 female) as a: (<em>i</em>) ‘turn’ if the gerbil’s
 body was perpendicular to the lane after the turn (47.8%)
 (<em>ii</em>) ‘no turn’ if it stopped before its body was
 perpendicular (50.9%) or (<em>iii</em>) ‘fail’ if the gerbil
 ran into a wall (1.3%). We excluded failed trials from analyses, along
 with 15 trials for which a camera malfunctioned and 3 for which we did not
 have timely trait measurements. The final dataset included 192 trials
 across 28 individuals (N = 63 for 135°, 65 for 90°, 64 for 45°).
 To calculate turn speed for each maneuverability trial, we
 tracked the tip of each gerbil’s nose through the trial using DLTdv8 in
 MATLAB R2022a to calculate instantaneous velocity using
 <em>trajr</em> and used filter order 3 with a filter length of
 21 to smooth the trajectory. We calculated the average speed around the
 corner over 0.1-s intervals. The fastest turn speed was selected for each
 gerbil and angle, yielding 52 top-performance trials across 24 individuals
 (11 males, 13 females).
description: # Distinct morphological drivers of jumping and maneuvering performance in
 gerbils
 [https://doi.org/10.5061/dryad.hdr7sqvqd](https://doi.org/10.5061/dryad.hdr7sqvqd) **Jump Force Data and Code** Dataset: jumpdata.csv Script: Jumping_Code.Rmd This dataset and script allow you to test for correlations between gerbil traits and jump performance. The columns contain identifying information on each trial -- "Trial.ID", "Date" -- identitiy and trait information for each gerbil during that trial -- "Gerbil.ID", "Sex", "Mass.g", "Hindfoot.mm", "Leg.mm", "Thigh.mm", "Forefoot.mm", "Arm.mm", "Tail.mm". For each trial, "Time.ms" represents the timepoint in the trial in ms. "Input0" to "Input5" give the raw output from the force plate for the 6 inputs. "Vx", "Vy", and "Vz" give instantaneous velocity in the X, Y, and Z directions. "Vxfilt", "Vyfilt", and "Vzfilt" give instantenous velocity in each direction after running the filter. "Ax"..... and "Fx"...... give instantaneous acceleration and force, respectively, in each direction with and wihtout the filter. "AbsFx" to "AbsFz" takes the absolute value of filtered force for use in calculations. **Maneuverability (Corner-Turning) Data and Code** 1\. Determining corner-turning speed from video tracking data. Dataset 1: maneuverability_tracing_data.csv Dataset 2: pixel_scaling.xlsx Script: Manueverability_Tracking_Code.Rmd This dataset contains the movement-tracking datapoints for every video for which a gerbil turned the corner. The "Trial.ID" column contains the unique identifier for each trial (e.g., G2_T1_135d_03Jul2022), including the gerbil ID, trial #, turn angle, and date. There are also unique columns for "Date", "Turn.Angle", "Gerbil.ID", and "Sex". The columns "Coord.X" and "Coord.Y" represent the position of the gerbil's nose in the camera view based on tracking in DLTdv8. Run the script "Manueverability_Tracking_Code.Rmd" to visualize the gerbil's trajectory and calculate speed around the turn for each trial in the dataset. Use the dataset pixel_scaling.xlsx to determine the number of pixels per centimeter for each date and turn angle, which is needed for the maneuverability tracking script. 2\. Testing impacts of sex and turn angle on probability of turning a corner. Dataset: binomial_turn_data.csv Script: Corner_Turning_Probability_Code.Rmd This dataset and script allow you to run a bionomial regression to test whether sex and turn angle are significantly associated with the probability of turning the corner at least once at a given angle. This script also contains code to plot the results. 3\. Testing impacts of traits, sex, and turn angle on corner-turning speed. Dataset: ManeuverabilityData.csv Script: CornerTurningAnalysis.Rmd This dataset and script allow you to run generalized linear mixed models to test for significant impacts of traits, turn angle, and sex on corner-turning speed. The columns contain basic information about each trial -- "Date", "Trial.ID", "Turn.Angle" -- and identify and trait information about each geribl -- "Gerbil.ID", "Sex", "Mass.g", "Hindfoot.mm", "Leg.mm", "Thigh.mm", "Forefoot.mm", "Arm.mm", "Tail.mm". The last three columns describe the results of the trial. "Turn.Speed.mps" gives the speed around the turn in meters per second. "Top.Turn.Speed" indicates whether the trial is the best performance at that angle for that gerbil. "Notes" describe the gerbils behavior during the trial. This script also contains code to plot the results. **Testing for a trade-off in jumping and maneuvering performance** Dataset 1: jumpdata.csv Dataset 2: ManeuverabilityData.csv Script: Performance_Correlation_Code.Rmd This script tests for a correlation between jumping and maneuvering performance using the jumping and maneuvering datasets described previously. **Videos** Video_S1.mp4 -- Example of a strong jump. Video shows male gerbil’s feet being sprayed with compressed air. He responds by hopping on all four feet, resetting on his hindfeet, and performing a jump. This was the strongest jump in the dataset, producing a force of 10.8 body weight units. Video_S2.mp4 -- Side view of male gerbil maneuvering around 135° turn. Gerbil approaches the end of the corridor, receives the compressed air spray, turns around, and sprints down the corridor and around the corner. He completes the turn and continues with his body parallel to the slow-down corridor. Video_S3.mp4 -- Top view of female gerbil maneuvering around 90° turn. Gerbil sprints down the corridor and around the corner. She completes the turn and then stops with her body parallel to the slow-down corridor. Video_S4.mp4 -- Top view of male gerbil maneuvering around 45° turn. Gerbil sprints down the corridor and around the corner, slowing down as he turns. He completes the turn and then pauses with his body parallel to the slow-down corridor before continuing to run to the end. Video_S5.mp4 -- Top view of female gerbil on 90° turning assay. Gerbil sprints down the corridor and stops in the corner without rounding it. She explores and tries to climb over the wall.