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Biomechanics of predator–prey arms race in lion, zebra, cheetah and impala

Nature volume 554, pages 183–188 (2018)Cite this article

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Abstract

The fastest and most manoeuvrable terrestrial animals are found in savannah habitats, where predators chase and capture running prey. Hunt outcome and success rate are critical to survival, so both predator and prey should evolve to be faster and/or more manoeuvrable. Here we compare locomotor characteristics in two pursuit predator–prey pairs, lion–zebra and cheetah–impala, in their natural savannah habitat in Botswana. We show that although cheetahs and impalas were universally more athletic than lions and zebras in terms of speed, acceleration and turning, within each predator–prey pair, the predators had 20% higher muscle fibre power than prey, 37% greater acceleration and 72% greater deceleration capacity than their prey. We simulated hunt dynamics with these data and showed that hunts at lower speeds enable prey to use their maximum manoeuvring capacity and favour prey survival, and that the predator needs to be more athletic than its prey to sustain a viable success rate.

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Figure 1: Overview
Figure 2: Muscle contraction mechanics
Figure 3: Locomotor performance based on stride parameters.
Figure 4: Output of the model of predator–prey interaction.
Figure 5: Orientation of direction of acceleration for each stride grouped by species.

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References

  1. Howland, H. C. Optimal strategies for predator avoidance: the relative importance of speed and manoeuvrability. J. Theor. Biol. 47, 333–350 (1974)

    Article  CAS  PubMed  Google Scholar 

  2. Moore, T. Y. & Biewener, A. A. Outrun or outmaneuver: Predator–prey interactions as a model system for integrating biomechanical studies in a broader ecological and evolutionary context. Integr. Comp. Biol. 55, 1188–1197 (2015)

    PubMed  Google Scholar 

  3. Combes, S. A., Salcedo, M. K., Pandit, M. M. & Iwasaki, J. M. Capture success and efficiency of dragonflies pursuing different types of prey. Integr. Comp. Biol. 53, 787–798 (2013)

    Article  CAS  PubMed  Google Scholar 

  4. Domenici, P., Booth, D., Blagburn, J. M. & Bacon, J. P. Cockroaches keep predators guessing by using preferred escape trajectories. Curr. Biol. 18, 1792–1796 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Domenici, P., Blagburn, J. M. & Bacon, J. P. Animal escapology II: escape trajectory case studies. J. Exp. Biol. 214, 2474–2494 (2011)

    Article  PubMed  PubMed Central  Google Scholar 

  6. Van Valen, L. A new evolutionary law. Evol. Theory 1, 1–30 (1973)

    Google Scholar 

  7. Benton, M. J. The Red Queen and the Court Jester: species diversity and the role of biotic and abiotic factors through time. Science 323, 728–732 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  8. Bro-Jørgensen, J. Evolution of sprint speed in African savannah herbivores in relation to predation. Evolution 67, 3371–3376 (2013)

    Article  PubMed  Google Scholar 

  9. Wilson, A. M. et al. Locomotion dynamics of hunting in wild cheetahs. Nature 498, 185–189 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Irschick, D. J. & Higham, T. E. Animal Athletes: an Ecological and Evolutionary Approach (Oxford Univ. Press, 2015).

    Book  Google Scholar 

  11. Broekhuis, F., Cozzi, G., Valeix, M., McNutt, J. W. & Macdonald, D. W. Risk avoidance in sympatric large carnivores: reactive or predictive? J. Anim. Ecol. 82, 1098–1105 (2013)

    Article  PubMed  Google Scholar 

  12. Schaller, G. B. The Serengeti Lion: A Study of Predator–Prey Relations (Univ. Chicago Press, 1972)

  13. Curtin, N. A ., Woledge, R. C. & Aerts, P. Muscle directly meets the vast power demands in agile lizards. Proc. R. Soc. Lond. B 272, 581–584 (2005)

    Article  Google Scholar 

  14. Kohn, T. A. & Noakes, T. D. Lion (Panthera leo) and caracal (Caracal caracal) type IIx single muscle fibre force and power exceed that of trained humans. J. Exp. Biol. 216, 960–969 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Williams, S. B., Tan, H., Usherwood, J. R. & Wilson, A. M. Pitch then power: limitations to acceleration in quadrupeds. Biol. Lett. 5, 610–613 (2009)

    Article  PubMed  PubMed Central  Google Scholar 

  16. Carrier, D. R., Gregersen, C. S. & Silverton, N. A. Dynamic gearing in running dogs. J. Exp. Biol. 201, 3185–3195 (1998)

    CAS  PubMed  Google Scholar 

  17. Tan, H. & Wilson, A. M. Grip and limb force limits to turning performance in competition horses. Proc. R. Soc. Lond. B 278, 2105–2111 (2011)

    Article  Google Scholar 

  18. Usherwood, J. R. & Wilson, A. M. Biomechanics: no force limit on greyhound sprint speed. Nature 438, 753–754 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  19. Daley, M. A. in Understanding Mammalian Locomotion: Concepts and Applications Ch. 11 (ed. Bertram, J. E. A. ) 277–306 (Wiley & Sons, 2016)

  20. Wilson, J. W. et al. Cheetahs, Acinonyx jubatus, balance turn capacity with pace when chasing prey. Biol. Lett. 9, 20130620 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  21. Jindrich, D. L., Smith, N. C., Jespers, K. & Wilson, A. M. Mechanics of cutting maneuvers by ostriches (Struthio camelus). J. Exp. Biol. 210, 1378–1390 (2007)

    Article  PubMed  Google Scholar 

  22. Curtin, N. A., Diack, R. A., West, T. G., Wilson, A. M. & Woledge, R. C. Skinned fibres produce the same power and force as intact fibre bundles from muscle of wild rabbits. J. Exp. Biol. 218, 2856–2863 (2015)

    Article  PubMed  Google Scholar 

  23. Rome, L. C., Sosnicki, A. A. & Goble, D. O. Maximum velocity of shortening of three fibre types from horse soleus muscle: implications for scaling with body size. J. Physiol. (Lond.) 431, 173–185 (1990)

    Article  CAS  Google Scholar 

  24. Seow, C. Y. & Ford, L. E. Shortening velocity and power output of skinned muscle fibers from mammals having a 25,000-fold range of body mass. J. Gen. Physiol. 97, 541–560 (1991)

    Article  CAS  PubMed  Google Scholar 

  25. Hill, A. V. The dimensions of animals and their muscular dynamics. Science Progress 38, 209–230 (1950)

    Google Scholar 

  26. West, T. G. et al. Power output of skinned skeletal muscle fibres from the cheetah (Acinonyx jubatus). J. Exp. Biol. 216, 2974–2982 (2013)

    Article  PubMed  Google Scholar 

  27. Crow, M. T. & Kushmerick, M. J. Chemical energetics of slow- and fast-twitch muscles of the mouse. J. Gen. Physiol. 79, 147–166 (1982)

    Article  CAS  PubMed  Google Scholar 

  28. Bartlam-Brooks, H. L., Bonyongo, M. C. & Harris, S. How landscape scale changes affect ecological processes in conservation areas: external factors influence land use by zebra (Equus burchelli) in the Okavango Delta. Ecol. Evol. 3, 2795–2805 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  29. Schmidt-Nielsen, K. Desert Animals. Physiological Problems of Heat and Water (Clarendon, 1965).

    Google Scholar 

  30. Wilson, A. M., McGuigan, M. P., Su, A. & van Den Bogert, A. J. Horses damp the spring in their step. Nature 414, 895–899 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  31. McGuigan, M. P. & Wilson, A. M. The effect of gait and digital flexor muscle activation on limb compliance in the forelimb of the horse Equus caballus. J. Exp. Biol. 206, 1325–1336 (2003)

    Article  PubMed  Google Scholar 

  32. Pasi, B. M. & Carrier, D. R. Functional trade-offs in the limb muscles of dogs selected for running vs. fighting. J. Evol. Biol. 16, 324–332 (2003)

    Article  CAS  PubMed  Google Scholar 

  33. Carrier, D. R., Anders, C. & Schilling, N. The musculoskeletal system of humans is not tuned to maximize the economy of locomotion. Proc. Natl Acad. Sci. USA 108, 18631–18636 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wynn, M. L., Clemente, C., Nasir, A. F. A. A. & Wilson, R. S. Running faster causes disaster: trade-offs between speed, manoeuvrability and motor control when running around corners in northern quolls (Dasyurus hallucatus). J. Exp. Biol. 218, 433–439 (2015)

    Article  PubMed  Google Scholar 

  35. Merz, A. The homicidal chauffeur. AIAA J. 12, 259–260 (1974). https://doi.org/10.2514/3.49215

    Article  ADS  Google Scholar 

  36. Getz, W. & Pachter, M. Two-target pursuit–evasion differential games in the plane. J. Optim. Theory Appl. 34, 383–403 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  37. Hubel, T. Y. et al. Energy cost and return for hunting in African wild dogs and cheetahs. Nat. Commun. 7, 11034 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  38. Méndez, J. & Keys, A. Density and composition of mammalian muscle. Metabolism 9, 184–188 (1960)

    Google Scholar 

  39. Pinheiro, J. & Bates, D. Mixed-Effects Models in S and S-PLUS (Springer, 2000)

  40. Ranatunga, K. W. Temperature dependence of mechanical power output in mammalian (rat) skeletal muscle. Exp. Physiol. 83, 371–376 (1998)

    Article  CAS  PubMed  Google Scholar 

  41. Barclay, C. J., Woledge, R. C. & Curtin, N. A. Is the efficiency of mammalian (mouse) skeletal muscle temperature dependent? J. Physiol. (Lond.) 588, 3819–3831 (2010)

    Article  CAS  Google Scholar 

  42. Sikes, R. S. et al. 2016 Guidelines of the American Society of Mammalogists for the use of wild mammals in research and education. J. Mamm. 97, 663–688 (2016)

    Article  Google Scholar 

  43. Kalman, R. E. A new approach to linear filtering and prediction problems. J. Basic Eng. 82, 35–45 (1960)

    Article  MathSciNet  Google Scholar 

  44. Titterton, D. & Weston, J. L. Strapdown Inertial Navigation Technology. 2 edn, Vol. 207 (AIAA, 2004)

  45. Rauch, H. E., Striebel, C. & Tung, F. Maximum likelihood estimates of linear dynamic systems. AIAA J. 3, 1445–1450 (1965)

    Article  ADS  MathSciNet  Google Scholar 

  46. Dewhirst, O. P. et al. An exploratory clustering approach for extracting stride parameters from tracking collars on free ranging wild animals. J. Exp. Biol. 220, 341–346 (2017)

    Article  PubMed  Google Scholar 

  47. Davies, D. L. & Bouldin, D. W. A cluster separation measure. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-1, 224–227 (1979)

    Article  Google Scholar 

  48. Hubel, T. Y. et al. Additive opportunistic capture explains group hunting benefits in African wild dogs. Nat. Commun. 7, 11033 (2016)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  49. Estes, R. D. The Behaviour Guide to African Mammals: including hoofed Mammals, Carnivores, Primates (Russell Friedman Books, 1991)

  50. Nowak, R. M. Walker’s Mammals of the World Vol. 1 (JHU, 1999)

  51. Williams, S. B., Wilson, A. M., Rhodes, L., Andrews, J. & Payne, R. C. Functional anatomy and muscle moment arms of the pelvic limb of an elite sprinting athlete: the racing greyhound (Canis familiaris). J. Anat. 213, 361–372 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Williams, S. B., Wilson, A. M., Daynes, J., Peckham, K. & Payne, R. C. Functional anatomy and muscle moment arms of the thoracic limb of an elite sprinting athlete: the racing greyhound (Canis familiaris). J. Anat. 213, 373–382 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Webster, E. L., Hudson, P. E. & Channon, S. B. Comparative functional anatomy of the epaxial musculature of dogs (Canis familiaris) bred for sprinting vs. fighting. J. Anat. 225, 317–327 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  54. Hudson, P. E. et al. Functional anatomy of the cheetah (Acinonyx jubatus) forelimb. J. Anat. 218, 375–385 (2011)

    Article  PubMed  PubMed Central  Google Scholar 

  55. Hudson, P. E. et al. Functional anatomy of the cheetah (Acinonyx jubatus) hindlimb. J. Anat. 218, 363–374 (2011)

    Article  PubMed  Google Scholar 

  56. Payne, R. C., Hutchinson, J. R., Robilliard, J. J., Smith, N. C. & Wilson, A. M. Functional specialisation of pelvic limb anatomy in horses (Equus caballus). J. Anat. 206, 557–574 (2005)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Payne, R. C., Veenman, P. & Wilson, A. M. The role of the extrinsic thoracic limb muscles in equine locomotion. J. Anat. 205, 479–490 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Crook, T. C. et al. Comparative anatomy and muscle architecture of selected hind limb muscles in the quarter horse and Arab. J. Anat. 212, 144–152 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Williams, S. B., Payne, R. C. & Wilson, A. M. Functional specialisation of the pelvic limb of the hare (Lepus europeus). J. Anat. 210, 472–490 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Williams, S. B., Wilson, A. M. & Payne, R. C. Functional specialisation of the thoracic limb of the hare (Lepus europeus). J. Anat. 210, 491–505 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Smith, N. C., Wilson, A. M., Jespers, K. J. & Payne, R. C. Muscle architecture and functional anatomy of the pelvic limb of the ostrich (Struthio camelus). J. Anat. 209, 765–779 (2006)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Schaller, N. U. Structural Attributes contributing to Locomotor Performance in the Ostrich. PhD thesis, Univ. Heidelberg (2008)

  63. Cuff, A. R. et al. The scaling of postcranial muscles in cats (Felidae) II: hindlimb and lumbosacral muscles. J. Anat. 229, 142–152 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  64. Cuff, A. R. et al. The scaling of postcranial muscles in cats (Felidae) I: forelimb, cervical, and thoracic muscles. J. Anat. 229, 128–141 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  65. Holland, R ., Loveday, D. & Ferguson, K. How much meat to expect from a beef carcass. http://extension.tennessee.edu/publications/Documents/PB1822.pdf (Univ. Tennessee, Institute of Agriculture, 2014)

  66. Sacks, R. D. & Roy, R. R. Architecture of the hind limb muscles of cats: functional significance. J. Morphol. 173, 185–195 (1982)

    Article  CAS  PubMed  Google Scholar 

  67. Shahar, R. & Milgram, J. Morphometric and anatomic study of the hind limb of a dog. Am. J. Vet. Res. 62, 928–933 (2001)

    Article  CAS  PubMed  Google Scholar 

  68. Gunn, H. M. Muscle, bone and fat proportions and muscle distribution of thoroughbreds and other horses. In Proc. 2nd ICEEP Equine Exercise Physiology (Gillespie, J. R. & Robinson, N. E.) 253–264 (ICEEP, 1988)

    Google Scholar 

  69. Alexander, R. M. Principles of Animal Locomotion (Princeton Univ. Press, 2003)

  70. Lindstedt, S. L., LaStayo, P. C. & Reich, T. E. When active muscles lengthen: properties and consequences of eccentric contractions. News Physiol. Sci. 16, 256–261 (2001)

    CAS  PubMed  Google Scholar 

  71. Roberts, T. J. & Azizi, E. The series-elastic shock absorber: tendons attenuate muscle power during eccentric actions. J. Appl. Physiol. 109, 396–404 (2010)

    Article  PubMed  PubMed Central  Google Scholar 

  72. Abbott, B. C., Bigland, B. & Ritchie, J. M. The physiological cost of negative work. J. Physiol. (Lond.) 117, 380–390 (1952)

    Article  CAS  Google Scholar 

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Acknowledgements

We thank S. Amos for fabricating collars, N. Jordan and G. Gilfillan, M. Claase and N. Terry and BPCT research assistants for working with us in the study area and M. Flyman (DWNP) for his support and enthusiasm; J. Usherwood, R. Bomphrey and A. R. Wilson for comments on the manuscript; EPSRC (EP/H013016/1), BBSRC (BB/J018007/1) and ERC (323041) for funding. The Botswana Predator Conservation Trust was supported by private donors, Tusk Trust and the Cincinnati Zoo. Work was approved by RVC Ethics & Welfare Committee (RVC 2013 1233) and Botswana Department of Wildlife and National Parks Research Permits were held by J.W.M. and A.M.W. (EWT 8/36/4 plus additions) and a Botswana Veterinary Registration held by A.M.W. Tissue shipping was covered by CITES, Botswana export, Botswana National Veterinary Laboratory approval, South African transit and UK DEFRA import permits.

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Author notes

  1. Roger C. Woledge: Deceased.

Authors and Affiliations

  1. Structure & Motion Lab, Royal Veterinary College, University of London, Hatfield, AL9 7TA, UK

    Alan M. Wilson, Tatjana Y. Hubel, Simon D. Wilshin, John C. Lowe, Maja Lorenc, Oliver P. Dewhirst, Hattie L. A. Bartlam-Brooks, Rebecca Diack, Roger C. Woledge, Nancy A. Curtin & Timothy G. West

  2. Okavango Research Institute, University of Botswana, Maun, Botswana

    Emily Bennitt

  3. Botswana Predator Conservation Trust, Private Bag 13, Maun, Botswana

    Krystyna A. Golabek & J. Weldon McNutt

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  1. Alan M. Wilson
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Contributions

A.M.W., T.Y.H. N.A.C., R.C.W. and T.G.W. conceived, designed and led the study. K.A.G., J.W.M., H.L.A.B.-B. and E.B. organized field work, monitored animals and downloaded data. A.M.W. performed veterinary procedures, J.C.L. and A.M.W. designed and built collars. R.D., M.L., N.A.C. and T.W. carried out muscle experiments and interpreted the muscle data. T.Y.H., O.P.D., T.G.W. and A.M.W. analysed data. S.W. created the model and carried out statistical analysis. A.M.W. wrote the paper with input from all authors.

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Correspondence to Alan M. Wilson.

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Extended data figures and tables

Extended Data Figure 1 GPS data summary.

a, Example manoeuvring sequence for a cheetah showing position based on fused GPS-IMU data (250 Hz) colour-coded according to speed and segmented for clarity (1–5, duplicated in b–e). b, Speed based on fused GPS-IMU data (250 Hz). c–e, Stride-wise values for speed (averaged over stride), tangential (fore–aft) acceleration (change in stride speed/stride durations) and centripetal (lateral) acceleration ((change in heading/stride duration) × stride speed). f, Details on the animals used and datasets collected. Reduced dataset of non-steady state stride used for analysis of maximum performance. Note, the number of strides and distance per run was based on all strides (steady-state included).

Extended Data Figure 2 Muscle data summary.

a–c, Time course of stress (force) development in a single skinned impala fibre, showing transition of the fibre through pre-activation, activation and relaxation solutions, and stress development after temperature jump (T-jump) from 1 to 25 °C. The sample rate was 5 kHz. The grey noisy parts of the stress trace denote periods of solution change. The four downward ‘spikes’ in the stress record (at 9, 10, 11 and 12 s) are distinct periods of force control, where the fibre length was first rapidly reduced from Lo and then reduced at an appropriate rate to maintain force at pre-defined sub-maximal levels. The broken-line box in a surrounds the first episode of force control and is presented in b and c on an expanded time scale. b Relative force (F/Fisom) was reduced to 40% of the maximum for 20 ms, where F indicates force during shortening, Fisom indicates isometric force. Isometric force (Fisom) and the force during force clamp (F) were recorded as average values for the central 10-ms intervals (vertical lines). A force measurement, Fisom, was recorded just before each of the four force-control events and used in the calculation of F/Fisom. c, Shortening speed (in Lo s−1) was derived from the rate of change in fibre length during each force clamp. At the end of the force clamp, fibre length was ‘quick-released’ to a slack length (70% of Lo), where force was reduced to the zero baseline. After 10 ms at slack length, the motor lengthened the fibre back to the starting length (Lo), isometric stress was re-established (as shown in a) and another force control event was initiated. d, Twelve points on a power–force relationship could be obtained from three temperature jump activations of a single fibre. The curves were fitted (see Methods) to give relative power (power/FisomLo (in s−1)) as a function of relative force (F/Fisom). Expressing both variables in relative units is important for the curve-fitting process, mainly because the measurements of Fisom often vary between and within activations; in the example shown in a there was a small reduction in Fisom through the activation at 25°C. e, Peak isometric force relative to fibre cross-sectional area (CSA) for fibres from the four species. f, Power output relative to fibre volume. There was a distinct subpopulation of low-performance fibres (mostly from lion and zebra) that displayed lower power at a given fibre volume. Fibres with a shortening velocity at peak power of <1.35 Lo s−1 (see also Fig. 2c) were classified as low performance. g, Peak power relative to stress at peak power. The low performing fibres also had stress at peak power values that were relatively low—the data points below the thin dashed black line have velocities of shortening <1.35 Lo s−1. h, The variability in stress at peak power was similar across the species tested. i, Details about the muscle fibres. Mean (±s.e.m.) mechanical features for single skinned skeletal muscle fibres from biceps femoris of cheetah, lion, impala and zebra. Mean values are also categorized for the predator and prey groups, and further as the high-performing sub-groups of fibres (high-performing fibres had optimal shortening speeds >1.35 Lo s−1, see main text and Extended Data Fig. 2f, g, i).

Extended Data Figure 3 Predator–prey run comparisons.

a, b, Histograms of all strides (a) and extracted non-steady state strides (b), for which the cut-off was species-specific based on their kurtosis. The x axis is the normalized and squared horizontal acceleration in arbitrary units (that is, combined tangential and centripetal). In b, on the x axis, the cut-off is zero and the 98th percentile is one. Cheetah, blue; impala, red; lion, purple; zebra, yellow. Removing steady-state strides delivers a similar distribution tail for all four species. This is critical for deriving an appropriate 98th percentile, as this should be equally representative in all four species. c, Histogram of maximum stride parameters recorded in each run (speed, centripetal and tangential acceleration) for each species. Colour-coded by individuals, n is the number of runs used for data extraction. One concern of the comparison between predator and prey species is the potential lack of high-performance runs in prey species due to the low number of actual one-on-one chases. However, the distribution of the performance data shows that the cheetah and impala data include a considerably higher proportion of high-performance runs, whereas the lion and zebra dataset includes a large percentage of slower runs. Recognizing that the species differ in run characteristics (motivation, proportion of steady-state versus non-steady-state strides), we removed steady-state strides, based on the species-specific kurtosis, resulting in a comparable distribution in all four species (see Methods).

Extended Data Figure 4 Performance metrics separated by individual and species plotted against run distance and against run tortuosity.

Maximum accelerations and speeds were extracted from each run and displayed versus distance covered during the run and versus tortuosity of the run. Tortuosity is the ratio of distance covered in a run to net displacement (distance between start and end of the run). Markers are colour-coded per individual, dashed black line maximum values are based on 98th percentile. Number of runs (data points) are given in Extended Data Fig. 1f. Cheetah, 520 runs; impala, 515 runs; lion, 2,726 runs; zebra, 1,801 runs.

Extended Data Figure 5 Work and power analysed for each species.

a, Cheetah. b, Impala. d, Lion. e, Zebra. a, b, d, e, Dots indicate the data points and the line marks the 98th percentile for data in speed bins as shown in Fig. 3a, b, d, e. Markers are colour-coded by individual, the solid black line is the 98th percentile. c, f, Comparison of the predator–prey pairs. c, Cheetah–impala. f, Lion–zebra. g, Comparison of the predator species (lion–cheetah). h, Comparison of the herbivore species (impala–zebra). i, The 98th percentile for all four species. c, f–i, Data are colour-coded by species (key is shown in i). In all four species maximum negative power was similar to maximum positive power. Muscle stress can be considerably higher when performing negative work than positive work70,71 and a 60% higher fascicle power in lengthening (rather than shortening) has been reported71, so mass-specific muscle power can be much higher in deceleration72. Body geometry relative to the ground reaction force vector or grip may limit the attainable horizontal ground reaction force15 and the muscles need to be arranged to lengthen while experiencing the large horizontal forces. Many of the propulsive muscles are hip retractors (Extended Data Table 1), which are not configured to resist forward motion.

Extended Data Figure 6 Tangential and centripetal acceleration analysed for each species.

a, Cheetah. b, Impala. d, Lion. e, Zebra. Dots indicate the data points and the line marks the 98th percentile for data in speed bins as shown in Fig. 3a, b, d, e. Markers are colour-coded by individual, the solid black line is the 98th percentile. c, f, Comparison of the predator–prey pairs. c, Cheetah–impala. f, Lion–zebra. g, Comparison of the predator species (lion–cheetah). h, Comparison of the herbivore species (impala–zebra). i, The 98th percentile for all four species. c, f–i, Data are colour-coded by species (key is shown in i).

Extended Data Figure 7 Locomotor performance based on stride parameters.

This is the same as Fig. 3, but the ratios compare the two predators and the two prey species. All values are averaged per stride or represent the change over a stride. a–e, Acceleration. a, Positive net work performed in each stride. b, Stride frequency. c, Stride power. d, Increase in speed per stride. e, Forward acceleration with the curved lines representing a mean power of 30, 60, 90, 120 and 150 W. f–j, Deceleration. f–j, As a–e but for decelerating strides. k–n, Turning. k, Centripetal acceleration. l, The relationship between speed and turn radius with limit lines for a coefficient of friction (μ) of 0.6 and 1.3. m, Change in heading versus speed. n, Lateral versus tangential acceleration with limits as for μ. In n, F represents pure forward acceleration; B, deceleration; and C, acceleration to the side. In each panel, there is one line per species that represents the 98th percentile for data in speed bins (bins always include 400 data points, therefore bin width varies). Cheetah, blue; impala, red; lion, purple; zebra, yellow. Bottom, the ratio of that parameter for cheetah to lion (green circle) and impala to zebra (magenta circle) is given for each speed bin.

Extended Data Figure 8 Output of model of predator–prey interaction and impact of performance differential on hunt outcome.

See also Fig. 4. a, b, Plot showing output of simulation. a and b are equivalent to Fig. 4d with more subplots for cheetah–impala and lion–zebra, respectively. At the start of simulation, both have initial velocity towards the top of the page and initial separation. After one stride the prey can move to anywhere in the red or yellow ellipse by acceleration in the appropriate direction. Predator velocity remains unchanged, as there is no prey acceleration in the previous stride to react to. Initial positions are shown. Larger red or yellow ellipse perimeter is the area prey can reach after two strides of the chosen maximum acceleration. The blue or purple filled ellipse represents the locations the predator can occupy after its second stride (responding to the prey acceleration observed in first stride). The area of the prey ellipse that is covered by the predator ellipse line is defined as probability of capture. Predator is given a starting speed for each combination of prey speed and initial spacing that maximizes the capture probability. Rows are different initial prey speeds, values in red to the left of each row. Columns are different initial predator–prey separations at the start of the simulation with values given in red below each column. Scale for all instances is given in the bottom left plot in metres (in black). The inset black numbers in each sub-panel are the initial (optimized for maximum success) predator speeds in m s−1. c, The optimum lion speed to maximize overlap (hotter colours indicate faster speed, key on the right) as a function of zebra speed (x axis) and starting separation (y axis). The histogram above the main plot shows the distribution of actual zebra speed at first turn of 10 degrees or more for each run (same x axis as the main plot) and the vertical histogram shows distribution of actual lion speed at first turn (scale as for heat bar). d, The proportional overlap (capture probability), as a function of zebra initial speed and starting separation. e, Modelled capacity for forward acceleration (speed increase per stride) as a function of speed (Extended Data Table 2b). Cheetah, blue; impala, red; lion, purple; zebra, yellow.

Extended Data Table 1 Proportion of animal that is locomotor muscle
Full size table
Extended Data Table 2 Performance parameters
Full size table

Supplementary information

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This file contains a description about collar design, collar data recording and collar performance with references. (PDF 146 kb)

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Wilson, A., Hubel, T., Wilshin, S. et al. Biomechanics of predator–prey arms race in lion, zebra, cheetah and impala. Nature 554, 183–188 (2018). https://doi.org/10.1038/nature25479

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