To Run Or to Carry: Derived Traits in Early Members of the Genus Homo

To Run or to Carry: Derived Traits in Early Members of the Genus Homo

Item Type text; Electronic Dissertation

Authors Webber, James Thomas

Publisher The University of Arizona.

Rights Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

Download date 26/09/2021 13:13:55

Link to Item http://hdl.handle.net/10150/642005 TO RUN OR TO CARRY: DERIVED TRAITS IN EARLY MEMBERS OF THE GENUS

HOMO

James T. Webber

A Dissertation Submitted to the Faculty of the

SCHOOL OF ANTHROPOLOGY

In Partial Fulfillment of the Requirements

For the Degree of

DOCTOR OF PHILOSOPHY

In the Graduate College

THE UNIVERSITY OF ARIZONA

2020

ACKNOWLEDGEMENTS

First and foremost, I would like to thank the College of School of Behavioral and Social Sciences for the Dissertation Research Grant (award number: 18DRF0885), and the University of Arizona School of Anthropology for the Haury Dissertation Fellowship for supporting this dissertation research. I am thankful for my committee members, Dr. David Raichlen, Dr. Ivy Pike, Dr. Stacey Tecot, and Dr. Steven Kuhn who helped shape and inspire this research through their mentorship, conversations, personal research, and classes taught. I am especially grateful to my chair, Dr. David Raichlen who took a shot on a small-town undergrad interested in barefoot running, for his support, belief, mentorship, and positive outlook on the totality of the grad school experience. Additionally, I would like to thank Dr. Ivy Pike who was willing to take over as my committee chair allowing me to finish my degree at the University of Arizona. I would also like to thank Catherine Lehman for being patient with me as I stumbled through the requirements of graduate school, and Veronica Peralta for buffering the enormous stress of the grant application process with warmth and kindness. My dissertation would not have been possible without the numerous study volunteers, many of which who came from the School of Anthropology to support one of their own. Specifically, I would like to thank all the parents who brought their precious children into our back-alley laboratory and allowed me to apply reflective ping-pong balls and film them at 400 frames a second. Finally, I would like to thank my friends and partner who supported me throughout this campaign. I would like to specifically thank my partner Emily for following me down into the desert from the beautiful Pacific northwest for 5 long years of stress and hardship. This dissertation is also seeing the light of day thanks to the endless support of my fellow BioAnth cohort. Thank you all for walking me through every step of the way.

DEDICATION

I dedicate this dissertation to my uncle, Richard Shell, for inspiring me to be curious about the stars above my head and the bones beneath my feet.

TABLE OF CONTENTS ABSTRACT ...... 6 CHAPTER 1: INTRODUCTION ...... 7 1.1 Research question ...... 7 1.2 Aims ...... 8 1.3 Methods overview ...... 9 1.4 Participants ...... 10 1.5 Data ...... 12 1.6 Limitations ...... 13 1.7 Dissertation organization ...... 13 CHAPTER 2: LITERATURE REVIEW ...... 17 2.1 Early hominin evolution of bipedal locomotion ...... 17 2.2 Biomechanical differences between walking and running ...... 22 2.3 Derived structures and alternative behaviors...... 25 2.4 Hominin skeletal morphology ...... 31 2.5 An argument for carrying and high-speed walking ...... 34 2.6 Evidence of carrying behaviors in primates ...... 37 2.7 Carrying in small scale societies ...... 41 2.8 Conclusion ...... 43 CHAPTER 3: CONCLUSION ...... 44 3.1 Implications ...... 44 3.2 Future studies ...... 46 3.3 Conclusions ...... 48 REFERENCES ...... 50 APPENDIX A: MANUSCRIPT 1 ...... 67 Abstract ...... 68 Introduction ...... 69 Materials and methods ...... 72 Results ...... 78 Discussion ...... 79 Acknowledgements ...... 82 References ...... 83 Supporting information ...... 87 APPENDIX B: MANUSCRIPT 2 ...... 90 Abstract ...... 91 Introduction ...... 92 Methods ...... 95 Results ...... 100 Discussion ...... 102 Conclusions ...... 105 Acknowledgments ...... 105 References ...... 106 APPENDIX C: MANUSCRIPT 3 ...... 112 Abstract ...... 113 Introduction ...... 114 Methods ...... 115 Results ...... 120 Discussion ...... 124 Conclusions ...... 125 Acknowledgements ...... 126 References ...... 127 APPENDIX D: HOMININ SKELETAL MORPHOLOGY SUPPLEMENT ...... 130 6

ABSTRACT

The purpose of this dissertation is to expand upon hypothesized selective pressures for three body acceleration and impact-resisting derived skeletal features seen in early members of the genus Homo. Historically, many of these skeletal structures (including enlarged lower limb joint surface areas, large anterior semicircular canal diameters, increased gluteal attachment sites, and robust heel bones) have been interpreted in the context of long-distance running and persistence hunting (typically adult male activities in modern hunting and gathering societies). However, many human locomotor activities can produce elevated impact forces, including high-speed walking and load carrying. For example, carrying infants during extended juvenile periods is a derived trait within primates and represents a significant energetic challenge, a large portion of which is the byproduct of transporting additional weight in the form of the dependent offspring. Furthermore, activities practiced in early life have significant impacts on adult skeletal morphology especially related to locomotion. Therefore, this dissertation seeks to explore loaded walking behaviors in humans in relation to running to determine if there is overlap in locomotor challenges between these two activities. To accomplish this goal, three studies were conducted to examine locomotor impact forces in children, head perturbations during load carrying, and gluteal muscle activation between load carrying and running. The results of this dissertation suggest that children deal with high impact forces early in the development of walking but can use non-heel-strike foot postures to reduce these impacts, that load carrying significantly increases head motion when compared to running, and that high gluteal excitation is specific to running. These data suggest that the human endurance running capacity may be the product of coopting many early adaptations related to non- running behaviors.

CHAPTER 1: INTRODUCTION

1.1 Research question

The primary focus of this dissertation is to address gaps in the literature regarding the evolution of human long distance running and explore possible locomotor behaviors that could have acted as exaptations for our current high-speed locomotor capabilities. Historically, research focused on endurance running has been conducted by a very homogeneous group of individuals which may have directed the focus of evolutionary locomotor research on high-speed, typically male oriented hunting activities. Of the top ten most cited research articles on the evolution of endurance running in humans (found by searching Web of Science; "evolution*" AND "endurance running*" and "human"), eight are first authored by self-proclaimed runners who have participated in competitive organized road races (Bramble and Lieberman, 2004; Hatala et al., 2013; Le

Galliard et al., 2004; Liebenberg, 2006; Lieberman et al., 2010; Millet, 2011; Raichlen and Polk,

2013; Rolian et al., 2009). Thus, the focus on this relatively rare activity in extant small-scale societies (Hill et al., 1987; Hilton and Greaves, 2004; Lee, 2003; Marlowe, 2010), may be unwarranted, and our modern conceptions of what constitutes endurance running may be locally, temporally, and historically biased.

Therefore, this dissertation seeks to reexamine common but under-researched locomotor behaviors which may have played a role in the generation of derived skeletal traits in early Homo.

This dissertation explores naturally occurring locomotor modes including high-speed walking and load carrying in relation to running to capture a fuller range of transportation challenges.

Additionally, this dissertation lays the groundwork for pursuing ethnographic research on carrying traditions and child allomaternal care activities beyond of western contexts. This dissertation adds 8 quantitative evidence of the role of carrying, and locomotor development in the acquisition of adult skeletal morphologies thought to be linked to endurance running.

1.2 Aims

This dissertation addresses three related aims. Aim 1: to determine whether children encounter landing forces similar to running during immature gaits (walking gaits used by children under 3.5 years of age). Previous research has shown that walking produces significantly lower impact forces than running (Lieberman et al., 2010; Webber and Raichlen, 2016), yet children often tolerate significantly high forces compared to adults when using immature gaits (Zeininger et al., 2018). However, the kinematic differences between instances of high and low landing forces are not well understood and immature gaits resemble adult barefoot running gaits which reduce impact forces (Altman and Davis, 2012; Divert et al., 2005; Lieberman et al., 2010). Locomotor differences between the two may help explain adult skeletal lower limb morphology thought to be linked to endurance running.

Aim 2: to assess whether loaded walking behaviors can generate locomotor challenges which overlap with running and are linked to derived skeletal morphologies in early Homo. Many derived skeletal traits related to endurance running are attributed to impact resisting structures

(Bramble and Lieberman, 2004). Yet, many locomotor modes can increase impact forces including high-speed walking and loaded walking (Birrell et al., 2007; Webber and Raichlen, 2016), behaviors which are common in extant small scale populations (Bentley, 1985; Grove, 2009; Hill et al., 1987; Hurtado et al., 1985; Marlowe, 2010; Pontzer et al., 2015).

Aim 3: to test whether increased gluteus maximus excitation is specific to running behaviors or if loaded walking can generate equivalent electromyography (EMG) amplitudes. The human gluteus maximus is conspicuous due to its derived size. The muscles main action is 9 extension of the lower limb and stabilization of the torso (Stern, 1972). Previous research has shown that the gluteus maximus is especially electrically excited during running when compared to walking (Lieberman et al., 2006). However, comparisons with loaded or higher speed walking modes have not been analyzed previously.

To address these aims three hypotheses were tested. These hypotheses were designed to test a range of endurance running-related evolutionary hypotheses pertaining to derived features of modern humans. Hypothesis 1: Children using foot strike patterns similar to adult barefoot runners will have lower impact forces than children using heel-strike gaits. Hypothesis 2: Walking while carrying weight will increase head motion to rates seen recorded during running due to increased ground reaction forces at landing and differences in lower limb orientation. Hypothesis

3: Walking while carrying a load in a frontal position will increase maximal gluteus maximus

EMG amplitudes within the range found during low-speed running.

1.3 Methods overview

To address the aims of this dissertation a range of experimental methods were used (which are explained in more detail in the methods section of each manuscript). In order to explore how the development of heel-strike altered impact forces during the ontogeny of walking (Aim 1), twenty-five children between the ages of 1.1 and 8.5 years and ten adults aged 18 to 33 years were recruited in Tucson Arizona to walk in the Evolutionary Biomechanics Laboratory. Kinematic data were collected using a six-camera, high-speed motion capture system (Vicon T160 cameras and

Vicon Nexus v1.6.1. Oxford, UK). Kinetic data were collected using an embedded AMTI force plate (AMTI OR6-6, Watertown, MA). Subjects walked across a 4-meter trackway while being filmed to capture foot posture and impact forces at a range of speeds. 10

To explore how loaded walking impacts head pitch with relation to running (Aim 2), eighteen subjects (nine female and nine male) between the ages of 21 and 48 were recruited to walk on a treadmill (SOLE F63, Salt Lake, UT) while wearing a set of 3D accelerometers (Delsys,

SP-W06 sensors and SP-W02 base station, Natick, MA) on their head, torso, and right lower limb.

Subjects walked or ran for twenty unique trials consisting of different combinations of speed and carried load.

Finally, to address the final aim of this dissertation (Aim 3), twenty subjects (aged 21-48, ten male and ten female) wore six wireless EMG sensors (Delsys, SP-W06 sensors and SP-W02 base station, Natick, MA) on the torso and right lower limb to capture muscle activity across a range of locomotor behaviors. Subjects walked while carrying loads in a frontal position, and torso pitch rates were measured to determine whether gluteus maximus excitation was specific to running behaviors.

Laboratory locomotor analysis of extant populations has often been used to help elucidate behaviors that could have impacted musculoskeletal morphology in our evolutionary past (Key,

2016; Lieberman et al., 2006; Wall-Scheffler and Myers, 2013; Zeininger et al., 2018). Here I have been careful to recruit a wide array of subjects, including children, adults, and a mix of sexes and fitness levels to better represent the transition period between walking and running rather than focus on experienced runners who represent the extremes of human locomotor abilities.

1.4 Participants

Young children go through a number of key developmental windows important for bone growth and development during the ontogeny of gait (Beck et al., 1981; Berger et al., 1983; Burnett and Johnson, 1971; Cowgill et al., 2010; Raichlen et al., 2015; Ruff, 2003b; Sutherland, 1997).

Additionally, previous research has suggested that children deal with large impact forces early in 11 gait development (Zeininger et al., 2018), and high ground reaction forces are critically linked to many running related derived skeletal morphologies (Bramble and Lieberman, 2004; Carrier,

1984). Thus, exploring the range of locomotor challenges faced across the development of gait will help quantify overlaps in ground reaction forces as they relate to long distance running.

Children under the age of nine were recruited to capture lower limb mechanics before the development of “adult-like” gait (Sutherland et al., 1980). Subjects were excluded from this study if they were unable to walk on their own or if they were atypical in development. Over forty children were recruited for the study. However, due to the challenges of capturing consistent locomotor data from children, data collected from twenty-five children were used in the final analysis. Further data on sex, age, and morphological characteristics can be found in Appendix A.

Normally active and healthy individuals from the University of Arizona were recruited for the two adult studies rather than targeting specifically athletes or runners. Significant changes in skeletal morphology are used to demark shifts in locomotor habits, notably an initial shift toward bipedality (Carvalho et al., 2012; Preuschoft, 2004; Rodman and Mchenry, 1980), and then later as members of the genus Homo likely increased daily ranges at potentially higher speeds or intensities (Aiello and Wells, 2002; Kuhn et al., 2016; Lieberman et al., 2009; Malina and Little,

2008; Pontzer et al., 2012; Pontzer et al., 2015; Raichlen et al., 2011). Bipedalism is a defining human feature, separating humans from the rest of the extant great apes. While the reason for the appearance of this behavior has been discussed thoroughly (Cunningham et al., 2010; Pontzer et al., 2014; Sockol et al., 2007; Webber and Raichlen, 2016), how early the hominin skeletal system adapted during the first shifts from simply bipedal walkers toward longer day ranges or endurance running is not well understood. Twenty subjects participated in the two adult experiments (ten men and ten women). Subjects were only excluded if they had an active lower limb injury. 12

Demographic data (from subjects including: 20 adults, [10 women; 10 men] and 25 children) can be found in Appendix B & C.

1.5 Data

I collected data using three distinct methodologies, each specific to the aims of the individual study. To capture kinetic (force) and kinematic (movement) data during the ontogeny of walking, I measured impact and ground reaction forces along with the location and position of foot postures and lower limb joint angles during natural walking gaits in children using motion capture. These data allowed for comparisons of immature and mature gait mechanics and for analysis of the relation between high impact forces and foot postures.

To study derived inner ear morphologies linked to endurance running, I investigated head and trunk rotation (pitch) accelerations (in rates of gravitational units) along with locomotor speed.

Here, I analyzed the relationships between locomotor speeds, carried loads, gait type (walking or running) and head and trunk pitch rates to determine whether running or load carrying played a more significant role in upper body locomotor perturbations.

I also used electromyography (EMG) to study muscle activity. EMG data can be contentious because it only measures muscle excitability (in electrical voltage) and not force production of specific muscle groups (Vigotsky et al., 2018), therefore I specifically compared muscle activity within muscle groups, but between activities. Since I am relating muscle excitation to expected muscle force production it was important to acknowledge that EMG data does not directly measure force production. However, previous research has suggested that EMG amplitude data is linearly related to muscle force, but only during the stance phase of human gait (Roberts and Gabaldón, 2008). Therefore, I only analyzed stance phase muscle amplitudes. Additionally, I 13 used the linear envelope of the muscle activity data to avoid artifactual spikes in the EMG signals

(Roberts and Gabaldón, 2008).

I recorded metrics such as age, stature, hip height, weight, and sex to address how differences in bodies can impact locomotor biomechanics for all three studies. When studying muscle excitation, which is affected by fatigue, trial order was added to predictive models to account for the degradation in muscle voltage that comes with fatigue (Rahnama et al., 2006).

1.6 Limitations

This dissertation seeks to address gaps in the locomotor evolutionary literature but is in no way exhaustive of the range of transportation behaviors used by contemporary and past humans.

Future studies across cultures and across a broader range of ages and fitness levels are required to paint a true picture of the spectrum of possible challenges we face during locomotion. I seek to link locomotor behaviors in the present with skeletal morphologies in the past, but we cannot that assume the way humans move in the present exactly matches how our ancestors moved.

Furthermore, study participants were sampled from a broad, but Western context, and many aspects of walking dynamics shift due to context, location, culture, and age (Wagnild and Wall-

Scheffler, 2013; Wirtz and Ries, 1992). Additionally, the adult studies of this dissertation did not make use of a force plate to allow for estimation of impact forces or muscle force production.

Future studies employing a force treadmill would help elucidate how load carrying affects locomotor impact forces, a key component of many of the derived skeletal traits important to the endurance running hypothesis.

1.7 Dissertation organization

The remainder of this dissertation is organized into five section as follows. First, I will provide a literature review of the anatomical indicators suggesting early members of the genus 14

Homo but not australopithecines were adapted to long distance running, how these indicators may overlap with carrying behaviors, the frequency of long distance running in modern small-scale societies, and of behaviors most likely produce locomotor challenges similar to running (Chapter

2). Within the literature review I will examine previous research to link the three aims of this dissertation.

Next, I provide the major findings of this dissertation in three separate manuscripts. The first manuscript (under review in PLOS One) examined how immature gaits (and foot postures at ground contact) specifically create different (higher) impact forces during walking relative to adult gaits (Appendix A). In this article, titled Initial ground contact location, impact forces, and the development of heel-strike walking in children, I used high-speed motion capture camera and force plate analysis to show to the distance of the ground reaction force from the ankle joint is important when accounting for high impact forces often seen in young children. While children displayed increased impact forces during walking (p < 0.0001), the way they were walking was critically important. Using a comparison of linear mixed models, I found that including precisely where initial ground contact originated during walking in children significantly improved upon predictions of maximal impact forces from a null model without this variable (p < 0.0001). Here the main finding is that as the foot contact location moves away from the ankle joint impact forces are reduced (p < 0.0001). These findings support the hypothesis that impact resisting skeletal structures associated with endurance running may have their roots in early childhood development.

Furthermore, they suggest that immature gaits assigned to young walkers may have a protective effect against high impact forces that could prove damaging to growing bones.

The second article tackles derived skeletal inner ear morphology associated with high- speed locomotor activities, the semicircular canal. This article titled Head kinematics of load 15 carrying while walking and the evolution of the semicircular canal in early members of the genus

Homo, to be submitted for publication in the Journal of Human Evolution, uses wireless 3D accelerometers and rate gyro sensors to compare head perturbations between loaded walking and running (Appendix B). Previously, head pitch rates have been related to highly agile activities such as running and leaping, however, this research found that loaded walking significantly increases head pitch rates when compared with non-loaded conditions (p < 0.0001, X2 = 30.685).

Additionally, at high speeds, loaded walking head pitch rates were significantly higher than those seen during running (p = 0.0122). These data suggest that the derived inner ear canal diameters previously attributed to running behaviors may have initially evolved to tolerate load carrying behaviors.

The third manuscript, A comparison of running and loaded walking on human gluteus maximus activation, which will be submitted to the Journal of Experimental Biology, explores unique human gluteal musculature and its relation to endurance running (Appendix C). Here, I examine whether gluteal muscle activation is specific to endurance running locomotor modes.

Previously, trunk pitch has been related to the excitation of the gluteus maxims as it acts as a trunk stabilizer. Hypothetically, adding a carried mass may also decrease trunk stability requiring additional activation of these core stabilization muscles. However, this research found that the gluteus maximus is unique among the lower limb muscles in its activation during running when compared with loaded walking. Only the gluteus maximus activation was statically different between loaded walking and running (X2 = 48.00, p < 0.001) whereas the rectus femoris, tibialis anterior, and medial gastrocnemius were not (RF X2 = 0.13, p = 0.71, TA X2 = 0.01, p = 0.93, GA

X2 = 1.69, p = 0.20). These findings support the hypothesis that the derived musculoskeletal features of the gluteus maximus are specifically related to running due to its role in stabilizing 16 trunk pitch. This paper bolsters the position that endurance running adaptations have been acquired across a broad scope of time.

Finally, the concluding chapter ties together the major implications of this dissertation.

Here I address future studies applicable to these findings. These dissertation data suggest a mosaic acquisition of human endurance running capabilities which support a hypothesis that many of the features thought to be specialized for running may have been coopted from lower intensity activities throughout our evolution. Furthermore, a discussion of how ethnographic accounts of carrying behaviors and accounts of what running means in different cultures will help further increase the scope of research required to tackle this evolutionary question.

CHAPTER 2: LITERATURE REVIEW

2.1 Early hominin evolution of bipedal locomotion

This dissertation focuses on the evolution of human locomotion across a key transition from early hominins to the evolution of the genus Homo. The study of locomotor behavior in early hominins has focused on reconstruction the biomechanics of habitual bipedalism, which forms a foundation for understanding how locomotor behaviors shift later in human evolution. Habitual bipedalism is the defining feature of the hominin tribe (Darwin, 1871), which separates extant humans from our extant great ape relatives. Reduced locomotor energy costs are often invoked as an explanation for the adoption of this peculiar behavior (Cunningham et al., 2010; Pontzer et al.,

2014; Sockol et al., 2007; Webber and Raichlen, 2016), and are generally linked to changes in the paleoenvironment which shifted toward more open or patchy landscapes and away from more densely forested habitats (Klein, 2009). Researchers suggest that near the end of the Miocene the climate became more cool and arid, greatly reducing the vegetation available for the existing primate species (Cerling et al., 1997; Herbert et al., 2016; Micheels et al., 2009; Roters and Henrich,

2010). Around this same time-period, humans ancestors split from the rest of the hominids, sharing a last common ancestor with Pan around 6-8 million years ago (Hasegawa et al., 1993; Klein,

2009). These changes in the environment represented a new evolutionary pressure, and many have hypothesized that this initial cooling period encouraged early human ancestors to shift toward bipedalism to conserve energy (Rodman and Mchenry, 1980; Sockol et al., 2007) as they walked between more distant feeding locations in an environment of patchy resources. Whether this initial change in locomotor mode caused early bipeds to travel further than extant apes during daily foraging is unknown, but perhaps energy economy was of greater importance in light of reduced resource density (Cerling et al., 1997; Pontzer, 2017). 18

Extant chimpanzees (and all great apes) are capable of bipedal locomotion and often practice two-legged walking when carrying a load in the arms (Carvalho et al., 2012; Elftman and

Manter, 1935; Pontzer et al., 2014; Sockol et al., 2007). However, non-human ape bipedal locomotion is biomechanically different from humans largely due to significantly flexed lower limbs when compared to the extended limbs of humans and their ancestors (Sockol et al., 2007).

Using a crouched gait significantly increases locomotor costs during bipedalism as muscle activity must resist the collapse of the limbs (Foster et al., 2013; Sockol et al., 2007). Additionally, chimpanzees daily ranges are typically smaller than those of extant human populations that hunt and gather for resources (Raichlen et al., 2019), but they can still travel significant distances between food sites (Chapman, 2000). (Sockol et al., 2007). While chimpanzees travel significantly further terrestrially than arboreally (terrestrial 2.1 km ± 0.06 daily, climbing 0.113 km ± 0.057 daily) (Pontzer and Wrangham, 2004), they are energetically inefficient during these quadrupedal bouts (Steudel, 1990). Researchers have suggested that chimpanzee skeletal morphologies appear both constrained and driven by habitual arboreality (Pontzer and Wrangham, 2004) resulting in higher terrestrial locomotor energy costs especially while walking bipedally. For example, the chimpanzee ischium is long, and the posterior positioning of this skeletal feature allows for powerful hip extensor during climbing when the limb is flexed (Lewton and Scott, 2017), but significantly increases bipedal locomotor costs where limb extension is more beneficial (Foster et al., 2013). Thus, chimpanzees do not appear to have optimized musculoskeletal morphology for the bipedal or terrestrial behaviors that appear in later hominins (Pontzer and Wrangham, 2004).

Changes in skeletal morphology are used to demark shifts in locomotor habits in hominin fossil remains, such as the initial shift toward bipedality (Carvalho et al., 2012; Preuschoft, 2004;

Rodman and Mchenry, 1980), and then the later shift to larger day ranges by genus Homo (Aiello 19 and Wells, 2002; Kuhn et al., 2016; Lieberman et al., 2009; Malina and Little, 2008; Pontzer et al.,

2012; Pontzer et al., 2015; Raichlen et al., 2011). If we use chimpanzees as a model for an early primate adopter of bipedality, we may expect bipedal adaptation to occur first plastically in the australopithecines, in incremental steps, due to a need to walk on two legs for shorter bouts, such as infant or resource carrying behaviors (Wall-Scheffler et al., 2007). The mammalian skeletal system has been shown to change plastically in regards specifically to bipedalism as seen in early studies of a bipedal goat which was born without forelimbs (Slijper, 1942; West-Eberhard, 2003).

The australopithecines span a range of bipedal primate species existing between approximately 4.4 million or 1.2 million years ago. The earliest australopithecine,

Australopithecus anamensis, brings the first hints of habitual bipedalism with a flat tibial plateau, the articular surface of the tibia and femur (Ward et al., 1999), suggesting the foot was aligned directly below the knee joint. More widely known is Australopithecus afarensis of “Lucy” fame, and the likely makers of the Laetoli site G prints, a preserved set of footprints made by an early biped (Leakey and Hay, 1979; Raichlen et al., 2010). A. afarensis remains have been dated to between 3.7 and 3.2 million years ago (Klein, 2009) and appear to display a mix of primitive and modern traits, with the upper body being more chimp-like and the lower limbs being strikingly human-like (Berge, 1994; Latimer, 1991; Stern and Susman, 1983). Australopithecus africanus, a related hominin found almost 100 years ago (Dart, 1925) is similar to A. afarensis with a slightly larger braincase and has been dated to between 3.3 and 2.1 million years ago (Klein, 2009).

Finally, an interesting and recent find, Australopithecus sediba, displays a number of unique traits suggesting it walked bipedally but with different kinematics compared with modern humans and the rest of the australopithecines (Berger et al., 2010; Zipfel et al., 2011). A. sediba, a

South African biped, has foot and ankle morphology that is thought to generate footfalls similar to 20 extant apes while being contemporaneous with more active members of our own genus around 2 million years ago (Desilva et al., 2012; Dirks et al., 2010; Zipfel et al., 2011). Gracile heels, midfoot mobility, and foot inversion in A. sediba all point toward climbing and suggest there may be more than one way of being a successfully bipedal hominin (Desilva et al., 2012; Zipfel et al.,

2011).

Following the evolution of bipedal walking, skeletal anatomy shifted again just after 2 million years ago, during the evolution of our own genus (see: Table 1 in section 2.4), with significant changes appearing in the fossil remains of Homo erectus (Antón, 2003; Kennedy, 1985;

Walker and Leakey, 1993). Prior to H. erectus, the fossil remains of H. habilis, the first members of our genus, display expanded brain sizes but likely retained australopithecine-like postcranial anatomy and body sizes (McHenry and Coffing, 2000). Increased body sizes present in later members of the genus Homo have been interpreted to imply both greater mobility and larger dietary breath (Foley, 1987). If H. erectus maintained an australopithecine-like diet they would have required a drastic shift in foraging behavior (Aiello and Wells, 2002). Additionally, enlarged brains generating significant energy demands suggest that H. erectus underwent a significant change in diet, towards more calorie-dense foods sources (e.g., carnivory) (Aiello and Wheeler,

1995). Fossil remains suggest several locomotor traits shifted alongside the increased body size of

H. erectus and may be linked with a shift in foraging behavior, including enlarged lower limb joint surface areas, increased lower limb robusticity, an enlarged calcaneus tuber, and enlarged lower lumbar body sizes (Bramble and Lieberman, 2004).

To explain the combination of newly derived skeletal traits and a hypothesized need for higher quality food sources, some researchers have put forth hypotheses that suggest that endurance running was an important behavior in H. erectus (Bramble and Lieberman, 2004; 21

Carrier, 1984). In this hypothesis, a shift towards endurance running would have aided foraging success by allowing for a novel hunting technique: persistence hunting (Bramble and Lieberman,

2004; Liebenberg, 2006; Liebenberg, 2008). Persistence hunting is the following of large bodied mammals until the target prey is incapacitated due to heat exhaustion (Liebenberg, 2008;

Lieberman et al., 2009). However, this hypothesis has garnered significant debate, and it is unclear how early the transition to persistence hunting from an australopithecine-like biped would have occurred. For example, persistence hunting is difficult (Liebenberg, 2008), not limited to running alone, and anything other than successful hunts would have a major impact on energy return rates

(large amounts of energy burned with zero energy returned), especially if hunters only ran as running gaits burn more energy per distance traveled than walking (Alexander, 2002; Pontzer,

2007). Additionally, many of the ethnographic accounts of persistence hunting of large body mammals take place at low locomotor speeds or contain significant bouts of walking (Liebenberg,

2006; Lowie, 1924). Finally, fossil evidence pointing to increased carnivory (Aiello and Wheeler,

1995; Larsen, 2003), scavenging (Blumenschine, 1986; Blumenschine, 1987; Dominguez-Rodrigo,

2002), and increased mobility (Kramer and Eck, 2000; Steudel-Numbers, 2006) that do not require long distance running exist. Therefore, claims that persistence hunting represented a key evolutionary pressure for the derived skeletal traits associated with habitual bipedalism are contentious (Liebenberg, 2006; Liebenberg, 2008). Given the high risk for even exceptional endurance runners, it is difficult to argue for the appearance of these skeletal traits strictly for improved running capabilities.

Therefore, alternative explanations for derived skeletal traits related to impact resistance

(i.e. large lower limb joint surface areas, robust calcaneal tubers, increased semicircular canal diameters, and the enlarged gluteus maximus size) should be explored to test the endurance 22 running hypothesis. To do so, this dissertation seeks to reexamine walking and load carrying, behaviors that require load resistance and where small evolutionary changes in morphology could lead to reproductive advantages (Wall-Scheffler et al., 2007), especially since these are behaviors already present in extant non-human primates (Ross, 2001). Many of the derived skeletal traits seen late in the evolution of the genus Homo may be helpful for loaded walking behaviors (Birrell et al., 2007; Watson et al., 2008), and improving locomotor economy in small amounts could lead to fitness benefits without requiring novel behaviors or a suite of adaptations to appear in order to gain added reproductive success (Wall-Scheffler et al., 2007). Thus, in order to explore alternative selective pressures to high-speed locomotion, such as carrying behaviors, I will first define the specific derived traits explored in the three manuscripts, and then I will explore the skeletal and associated behavioral shifts that have been suggested for our lineage and compare these shifts between the australopithecines and the members of our own genus.

2.2 Biomechanical differences between walking and running

Bipedal walking and running are two distinctly different gaits that are defined by the number of feet in contact with the ground at any time. During walking a foot is in contact with the ground more than 50% of a gait cycle (the time period between successive gait events, typically heel-strike to heel-strike, see: Fig. 1) leading to periods of double limb support (Gatesy and

Biewener, 1991; Novacheck, 1998). During running, each foot is on the ground less than 50% of the gait cycle (also known as a duty factor), leading to an aerial phase (Reynolds, 1987). Since there are always two limbs supporting the body at foot touchdown during walking, impact forces are relatively low when compared to running (Levinger and Gilleard, 2005; Simon et al., 1981).

Figure 1. (Duty Factor Example) 23

Human bipedal walking is modeled as an inverted pendulum where body mass is represented as a point at the end of a stiff extended limb (see: Figure 2) (Lee and Farley, 1998).

Humans tend to land on the heel due to the extended limb postures used during walking (Berge,

1994; Raichlen et al., 2010; Tardieu, 2010), and then vault over the stance limb, where the center of mass follows an arc above the stance limb, and land on the opposite foot as it swings through

(Usherwood et al., 2012). This extended limb and rearfoot striking gait is energetically efficient, using gravity for energy return in the second half of the stance phase (Cunningham et al., 2010;

Webber and Raichlen, 2016), and is distinct from a running gait.

When running, humans leap from one leg to the other landing on a single leg at high speeds which generates a high-magnitude impact shortly after the foot touches the ground (Altman and

Davis, 2012; Lieberman et al., 2010). Rather than landing on a stiff limb, running is modeled as acting as a point mass at the end of a spring (see: Fig. 2), where after landing the limb compresses

(through flexion at the knee) limiting the vertical translation of the center of mass over the course 24 of the stance phase (Lee and Farley, 1998; Saibene and Minetti, 2003). Where heel-strike footfalls are a hallmark of human walking, footfalls in human running gaits are more variable, with individuals falling into one of three categories: rear-foot strikers, mid-foot strikers, or fore-foot strikers (Lieberman et al., 2010). When landing with a rear-foot strike, there is no kinematic mechanism to alter the runners momentum, resulting in a large ground impact force shortly after the collision of the heel with the substrate (Altman and Davis, 2012; Divert et al., 2005; Lieberman et al., 2010; Revill et al., 2008). However, research suggests that landing with a fore-foot strike can reduce impact forces by translating the compressive force of landing into a rotational force about the ankle (Lieberman et al., 2010). Therefore, running is significantly more variable in regards to lower limb kinematics (Altman and Davis, 2012; Divert et al., 2005; Divert et al., 2008;

Lieberman, 2012).

Figure 2. (Walking and Running Models)

2.3 Derived structures and alternative behaviors

Due to the differences in biomechanics and impact forces in walking and running, researchers have linked the evolution of impact-resistant skeletal traits to the adoption of endurance running (Bramble and Lieberman, 2004). However, as described above, there may be alternative behaviors that may have played a role in the evolution of these adaptation. For this dissertation, I focus on three key traits that have been liked with the evolution of endurance running and propose alternative hypotheses for their origins.

Heel-Strike, impact forces, and lower limb anatomy: Heel-strike walking gaits are significantly more energetically economical in adults than non-heel-striking gaits (Cunningham et al., 2010; Usherwood et al., 2012), however, they require skeletal adaptations to manage large impact forces (Zeininger et al., 2018) such as robust foot bones and enlarged joint surface areas

(Jungers, 1988). Non-heel-strike steps may still be adaptive in children who are less constrained by locomotor energetics due to being carried early in their development (Altmann and Samuels,

1992; Tracer, 2009; Wall-Scheffler et al., 2007). Since non-heel-strike steps can reduce impact forces in adults (Lieberman et al., 2010; Webber and Raichlen, 2013) they may be a useful tool for young developing skeletons which could be more susceptible to injury or deformation. For example, fracture risk in children is associated with bone mechanical properties (Bernhardt, 1988;

Kalkwarf et al., 2011), which change across development due to the forces experienced during locomotion.

Due to the transition to unassisted bipedalism at around one year (Sheridan, 1975), children undergo significant lower limb skeletal changes throughout growth and development (Barak et al.,

2011; Carlson and Judex, 2007; Cowgill et al., 2010; Pontzer et al., 2006; Raichlen et al., 2015;

Ruff and Hayes, 1982; Ruff et al., 2006; Wolff, 1892), including rapid femoral strength increases 26

(Ruff, 2003a), and changes in the orientation, thickness, and volume of trabecular bone (Gosman and Ketcham, 2008; Ryan and Krovitz, 2006). During this time, children generate higher impact forces (when scaled to body mass) during walking than adults (Hennig et al., 1994; Zeininger et al., 2018). However, children move about their environments using a range of locomotor modes including crawling and being carried, and use different forms of bipedalism, suggesting children encounter a range of locomotor forces throughout development (MacLellan et al., 2012; Tracer,

2009; Tracer, 2009; Zeininger et al., 2018).

In adults, very high impact forces (often due specifically to running) have been linked to lower limb injury (Daoud et al., 2012; Lieberman, 2012). Yet, changes in foot posture towards a fore- or mid-foot strike (often called non-heel-strikes) have been shown to have a significant effect on impact forces (Altman and Davis, 2012; Divert et al., 2005; Lieberman et al., 2010). In children, bipedal gait develops in two stages, split into immature and mature walking categories with a transition between the two at around 3 and a half years (Sutherland, 1997). Importantly, a key indicator of a mature gait is the presence of a heel-strike at foot touchdown (Sutherland, 1997;

Sutherland et al., 1980). Young children’s immature gaits often exhibit a plantarflexed foot initiating ground contact anterior to the ankle joint (see: Fig. 3) (Hallemans et al., 2003; Zeininger et al., 2018). This immaturity in gait and foot strike has historically been thought of as the product of gait maturation (Sutherland, 1997) or neurobiological development (Berger et al., 1983).

However, children may use alternative foot postures to protect developing bones, while at the same time, high impact forces during locomotor development may actually play a role in the acquisition of an adult lower limb morphology argued to be linked to endurance running (Lieberman et al.,

2009).

Figure 3. (Example Heel-Strike and Non-Heel-Strike Steps) 27

Semicircular Canal Diameter: The semicircular canal (SCC) system is a key part of the vestibular system responsible for sensing head motion. Evolutionary changes in hominin SCCs have been linked to the evolution of endurance running (Bramble and Lieberman, 2004; Spoor and

Zonneveld, 1998). The SCC system is a set of three circular bone tubes filled with endolymph, a fluid which stimulates cilia within the canals as it moves (Oman et al., 1987). The three canals

(anterior, posterior, and lateral) sit at right angles to each other such that they create an internal coordinate system (i.e. x, y, and z axes) that individually sense angular accelerations in the sagittal, coronal, and transverse planes (Malinzak et al., 2012). The SCC system functions to stabilize the gaze of an individual during locomotion (Wilson, 2013) by interpreting both head movements and visual information (Frost et al., 1994). The gaze stabilization process is called the vestibulo-ocular reflex, which combines cranial, eye muscle, and trunk activity in response to perceived head rotation (Jones and Spells, 1963). Rapid head movements, higher than those typically seen during running (Pozzo et al., 1990), can disrupt the vestubolo-ocular reflex, causing a loss of vision as the eyes are unable to track the new position of the head (Atkin and Bender, 1968). SCC diameters generally follows negative allometric scaling with body-size (Jones and Spells, 1963). However, research has suggested that canal diameter size in some organisms have adapted to locomotor factors (Cox and Jeffery, 2010; Malinzak et al., 2012; Spoor and Zonneveld, 1998; Spoor et al., 28

2007). Studies exploring slow-moving sloths (Gray, 1908), and agile birds (Hadžiselimović and

Savković, 1964) suggest that canal diameter sizes have to locomotor activity adjusted accordingly.

Studies in nonhuman primates suggest species categorized as more agile tended to have larger canal diameters (King and Taub, 1986; Spoor and Zonneveld, 1998).

These results suggest that SSC diameter is related to precise gaze stabilization during head perturbations depending on absolute maximal speed of the rotations. Therefore, the SCC system has been used to reconstruct hominin locomotor behaviors (Cox and Jeffery, 2010; Malinzak et al.,

2012; Spoor et al., 2007). Compared to australopithecines, H. erectus has significantly larger anterior SSC diameters for their body size (Bramble and Lieberman, 2004; Lieberman, 2011;

Spoor, 2003). The same is true of H. erectus and modern human anterior SCC diameters (Spoor and Zonneveld, 1998). The anterior canals are in the sagittal plane of the body and therefore relay head pitch (the yes-nodding motion of the head) information to the eyes. If SSC diameters have adapted to significantly rapid head pitch incidences, then hominin vestibulo-ocular reflex and canal diameters may be tuned to locomotor behaviors that produce significant changes in head rotational acceleration (Bramble and Lieberman, 2004; Cox and Jeffery, 2010; Lieberman, 2011; Spoor,

2003).

However, many biomechanical factors including the magnitude and rate of loading of impact forces, lower limb compliance (Gatesy and Biewener, 1991), vertical and angular displacement of the torso (Bramble and Lieberman, 2004; Hamill et al., 1995; Hirasaki et al., 1999;

Mulavara and Bloomberg, 2002), and absolute body mass (Spoor, 2003) affect head pitch rates during locomotion. Walking, especially at energetically optimal speeds, generates low impact forces (a ground reaction force peak occurring after foot touchdown) known as the impact transient

(Lieberman et al., 2010; Webber and Raichlen, 2013). These impact forces are ultimately 29 transmitted to the head, through the body, leading to low maximal pitch accelerations (Lieberman,

2011). However, walking is often modeled as using a stiff stance limb (Lee and Farley, 1998), which causes significant vertical displacement of the torso (Hirasaki et al., 1999). Impact forces, as discussed earlier, are much higher during running when compared to walking even through runners typically uses a more compliant leg (Lieberman et al., 2010). Additionally, running significantly increases trunk pitch (Lieberman et al., 2006; Thorstensson et al., 1984), which likely increase head pitch rates (Lieberman, 2011). Impact forces do increase linearly as walking speed increases, but only reach non-heel-strike running amplitudes (Lieberman et al., 2010; Webber and

Raichlen, 2013).

As discussed above, load carrying can significantly increase impact forces (Birrell et al.,

2007), and reduces trunk movement (Watson et al., 2008), which when combined may significantly increase head pitch rates. Just as stiff limbs propagate forces more readily (Larney and Larson, 2004), a stiff trunk may exacerbate the already increased impact forces generated from the added mass of the load. Therefore, walking while carrying some weight may produce greater than expected forces and head pitch rates as a product of complimentary challenges.

Gluteus Maximus Enlargement: The human gluteus maximus (GM) is large in comparison to extant ape gluteal musculature (Marzke et al., 1988). Researchers have attributed the evolutionary increase in size of this powerful muscle to a range of locomotor modes, including running and climbing (Lieberman et al., 2006; Zimmermann et al., 1994). The most popular explanations for the enlarged GM, which appears to be distinct among the genus Homo (Bramble and Lieberman, 2004), suggest it developed as a response to relatively rare activities such as endurance running, traversing hills, or sprinting (Bartlett et al., 2014; Bramble and Lieberman,

2004; Zimmermann et al., 1994). These locomotor activities stand out as they produce significant 30 trunk flexion, and the GMs primary functions are lower limb extension and trunk flexion

(Lieberman et al., 2006; Stern, 1972).

The GM originates on the superior portion of the iliac crest and inserts onto the superior gluteal ridge of the femur (Aiello and Dean, 1990; Stern, 1972). Since the muscle crosses the hip joint, gluteal contraction either acts on a free lower limb causing extension of the femur, or, if the lower limb is stable, the GM acts as an extensor of the trunk (see: Fig. 4) (Lieberman et al., 2006;

Stern, 1972). Early GM research suggests that the muscle may have initially evolved to resist trunk pitch, as the muscle can resist moments of trunk flexion and stabilize the torso by isometrically contracting (Marzke et al., 1988). In humans, running can generate high trunk pitch velocities with each step and research quantifying GM muscle excitation have found the muscle to be significantly more active during running than walking (Lieberman et al., 2006). This comparison has been used to suggest that the human GM is specifically derived to mitigate locomotor activities that significantly increase trunk pitch, and in this case, endurance running.

Figure 4. (Gluteus Maximus Function)

However, running is not the only human locomotor behavior that can increase GM excitation and trunk pitch. Load carrying has been shown to increase excitation of the posterior fibers responsible for hip extension of the gluteus medius during load carrying (Neumann and

Cook, 1985). High ground reaction forces at foot touchdown during running have also been argued to increase GM activity (Stern et al., 1980) as the rapid translation of this impact force could cause violent trunk pitch velocities. However, studies examining impact forces have found that running, walking speed, and load carrying all can increase landing ground reaction forces (GRFs) (Birrell et al., 2007; Lieberman et al., 2010; Webber and Raichlen, 2013). Finally, during pregnancy, individuals shift their altered center of mass posteriorly, so it is centered above the hips as during non-pregnancy (Fries and Hellebrandt, 1943; Opala-Berdzik et al., 2010). While walking GM activity is not well understood during pregnancy, related research has found that GM activity is elevated in obese adults when compared to nonobese (Haight et al., 2014). Therefore, it is possible that a similar center of mass shift occurs during loaded walking, where the GM would be responsible for stabilizing the weight from tipping forward during each step. These factors raise the possibility of loaded walking being a significant activator of the GM when applied in tandem.

2.4 Hominin skeletal morphology

In order to better highlight how derived skeletal traits found in members of the genus Homo have been used to outline a transition from low to high activity levels compared to the australopithecines, a short review of the evolution of skeletal morphologies related to locomotion from both genera will follow in table format (see Table 1). I will summarize the skeletal morphologies related to walking and climbing within the australopithecines and the skeletal morphologies thought to be related to endurance running in the genus Homo more thoroughly in

Appendix D. This section addresses many of the ancestral skeletal traits within the 32 australopithecine species to provide a rough outline of the traits which have been interpreted as adaptions for bipedal walking and those likely adaptive for climbing and arboreal locomotion which are often interpreted as detrimental to endurance running behaviors. The section on the genus Homo (specifically H. erectus onwards) contrasts the australopithecine features by highlighting the derived traits thought to aid specifically endurance running activities. Finally, the table highlights the features that are retained in the genus Homo from our australopithecine ancestors, and those that have shifted in favor of terrestrial adaptations.

Table 1. (Locomotor skeletal traits of the australopithecines and the genus Homo)

Locomotor Skeletal Traits of the Australopithecines Locomotor Skeletal Traits of the Genus Homo

Retained Skeletal Feature Proposed Function Arboreal / Bipedal Skeletal Feature Proposed Function Walking / Running in Homo Head Minimal Prognathism Balanced Head Running Large Semicircular Canals Vestibulo-Ocular Reflex Sensitivity Running

Upper Long Forelimbs Brachiation Arboreality Lost Short Forelimbs Economical Endurance Running Running Limbs Superior Glenoid Fossa Brachiation Arboreality Lost Low and Wide Shoulder Joints Running Head Balance Running

Torso Funnel Shaped Trunk Vertical Climbing Arboreality Lost Barrel Shaped Trunk Running Stabilization Running Stiff Trunk Vertical Climbing Arboreality Lost Narrow Disconnected Waist Running Stabilization Running Large Vertebral Bodies Impact Force Resistance Running Pelvis Large Glute Attachments Economical Bipedalism Bipedalism Kept Large Gluteus Maximus Trunk Pitch Stabilization Running

Wide Pelvis Gait Stability Bipedalism Lost Short and Narrow Pelvis Economical Bipedalism Walking / Running Longer Iliac Blades Arboreal Climbing Arboreality Lost Lower Bicondylar Angle Gait Stability Bipedalism Kept Large Joint Surface Areas Impact Force Resistance Running

Limbs Flat Tibial Plateau Gait Stability Bipedalism Kept Elongated Limbs Economical Bipedalism Walking / Running

Extended Limbs Bipedal Walking Bipedalism Kept

Large Acetabulum Support Bipedal Weight Bipedalism Kept

Feet Adducted Big Toe Economical Bipedalism Bipedalism Kept Short Toes Reduction in Foot Stress Running Robust Calcaneus Impact Force Resistance Bipedalism Kept Large Calcaneal Tuber Impact Force Resistance Walking / Running Midtarsal Break Grasping Arboreality Lost Ridged Feet Efficient Foot Push off Walking / Running Curved Phalanges Grasping Arboreality Lost Medial and Transverse Arches Efficient Foot Push off Walking / Running 34

It appears that some amount of arboreal activity was still important to the early members of our genus as it is currently defined (Homo habilis), or, that there were no strong selective pressures to remove arboreal linked traits (see: Appendix D). Yet, by the time of H. erectus, many derived traits that have been linked to impact resistance, endurance running, and decreased arboreal locomotion are present (Bramble and Lieberman, 2004; Carrier, 1984). However, it is not clear what persistence hunting actually entails (as to how much of it was walking, or how long the average bout would have been), and the benefit of incremental gains in locomotor economy would not have been limited running gaits. Other hypotheses have been posited for the use of running, such as scavenging behaviors where arriving at a scavengeable site early could have been beneficial to acquire the best remaining flesh and bones (Blumenschine, 1987; Dominguez-

Rodrigo, 2002; O’Connell et al., 1988; Pickering and Bunn, 2007). Yet, there may be other, simpler explanations for the early development of the many impact-resisting skeletal traits that have been attributed to running.

2.5 An argument for carrying and high-speed walking

Exploring the role that walking and carrying could have played in the development of specific derived skeletal traits acts as a test of the endurance running hypothesis. Walking and carrying represent behaviors that are obviously practiced by both human sexes, and by primates in general. Extant small scale societies practice central place foraging which requires extensive carrying for both males and females (Kelly, 2013). Additionally, infant carrying appears to be an important behavior to primates (Ross, 2001), which is made all the more difficult by extended dependency periods seen in later species of Homo (Klein, 2009). Thus, it is possible that behaviors like load carrying may help explain why skeletal anatomy may have shifted during the evolution of the genus Homo. 35

A key argument for attributing skeletal features to selection for endurance running is based on the ethnographic evidence of persistence hunting in small-scale societies (Bramble and

Lieberman, 2004; Carrier, 1984; Liebenberg, 2006). Yet, while walking is heavily utilized by extant subsistence foragers (Kelly, 2013), long distance running is comparatively rare (Lee, 2003;

Marlowe, 2010; O’Keefe et al., 2011). Supporters of the endurance running hypothesis suggest caution when using the modern ethnographic record as a reflection of past behaviors however

(Lieberman et al., 2007). Modern hunter-gatherers also possess projectile weapons, yet evidence of projectile weapons does not appear in the archaeological record until after the origins of modern

H. sapiens (Lieberman et al., 2007; Shea, 2006). Therefore, pursuit hunting using endurance running could have been a viable foraging strategy for early members of the genus Homo.

Therefore, many derived lower limb traits found in H. erectus have been described here through the lens of endurance running, but it is possible that the same lower limb adaptations may help both running and walking. Bramble and Lieberman (2004) acknowledge that many of these derived traits are more helpful to running but still may improve walking performance, which leaves open the possibility of finding evidence for walking-specific adaptations when studies are not comparing treadmill running and walking at energetically optimal speeds.

For example, living members of small-scale hunter-gatherer societies practice a wide range of non-endurance running locomotor behaviors that might also alter loading regimes (Hill et al.,

1987; Hurtado et al., 1985; Kelly, 2013; Lee, 2003; Marlowe, 2005; Marlowe, 2010; O’Connell et al., 1988; Pontzer et al., 2012). Specifically, both male and female foragers often walk at relatively high-speeds (Bentley, 1985; Hill et al., 1987; Pontzer et al., 2012) while carrying heavy loads (e.g., food, water, firewood, or children) (Junqueira et al., 2015; Lee, 2003; Marlowe, 2010; Wall-

Scheffler et al., 2007). Therefore, this section will review how some of the previously mentioned 36 running-related skeletal traits are impacted by more rigorous walking behaviors, especially while carrying loads.

Researchers have attributed enlarged joint surface areas and robust limbs to running due to the significant increase in impact forces of running (Bramble and Lieberman, 2004; Lieberman et al., 2010), with larger articular surfaces spreading the compressive forces of landing over a larger area, reducing the impact force per surface ratio. However, carrying loads effectively increases the carrier’s mass leading to increased ground reaction forces (Watson et al., 2008) that can have similar magnitudes compared to running (Webber and Raichlen, 2017). Additionally, increasing walking speeds increases impact forces linearly (Webber and Raichlen, 2016). Thus, while large articular surfaces appear adaptive for managing impact forces, running is not the only activity that increases impact forces. Specifically, high-speed walking with loads is another potential source of selective pressure favoring enlarged joint surfaces.

The large gluteal muscles and derived pelvis of H. erectus can be viewed in the same way.

The rapid trunk pitching accelerations of running, which activate the gluteal muscles (Lieberman et al., 2006), may also occur in loaded walking where a change in the center of mass that comes from carrying loads in the arms (Duarte et al., 2012; Opala-Berdzik et al., 2010), may also lead to trunk pitching moments. Further, the narrow waist present in later members of the genus Homo which allows for counter rotation of the upper and lower body, and is useful during the aerial phase of running (Bramble and Lieberman, 2004), could reduce the energetic costs of carrying a load.

Chimpanzees swing carried objects back and forth during bipedal gaits (Carvalho et al., 2012), which could be reduced in humans by the ability of the trunk to counter rotate in relation to the pelvis (Thompson et al., 2015). Additionally, shorter forearm lengths are thought to help reduce the costs of arm swing during running (Bramble and Lieberman, 2004), but, reducing the length 37 of the forearm also shortens the moment arm of the load during arm carrying behaviors (Huang and Kuo, 2014).

2.6 Evidence of carrying behaviors in primates

Non-human primate infants are transported by either clinging onto a caregivers fur or by riding on the mothers (or fathers in the case of some New World monkeys) back (Ross, 2001).

Neither option is available to contemporary human infants. Humans must physically carry infants in their arms unless some carrying technology has been implemented (Wall-Scheffler et al., 2007).

Humans lack the fur of most non-human primates, possibly aiding thermoregulation (Carrier,

1984), and even though a grasping response in infants still exists (Halverson, 1937), it is questionable whether human infants would possess the strength to hold on even if humans were fur covered. Moreover, committed bipedal hominins lost the ability to grasp effectively with their hind feet (Bennett et al., 2009), meaning that infants of the genus Homo could only hold on with their hands. While the australopithecines likely retained fur for infant clinging, bipedalism removes the ability of hominin infants to ride horizontally on mothers’ backs in the way other primate infants travel. In humans, carrying a load with our arms adds an additional energetic burden in the form of our arm muscles supporting the load at the same time that our legs are doing the same (Wall-Scheffler et al., 2007), suggesting adaptations to increase locomotor economy would have been a helpful way to combat this extra energetic requirement.

Metabolic demands are important selective pressure for all organisms (Fisher, 2000), and may be even more important to primates given the prolonged periods of dependency (Kaplan,

1996). While lactation is the key energetic cost for new mothers, infant carrying has been shown to be a close second (Altmann and Samuels, 1992). Some of the strepsirrhine primates avoid carrying their offspring and instead park them to avoid the extra costs of transport (Ross, 2001; 38

Tecot et al., 2012). Carrying (including riding, where the infant clings to a caregiver) is a derived trait thought to have evolved multiple times in later primates suggesting important selective pressures must have existed to support this behavior (Kappeler, 1998). Since the primary cost of locomotion is due to the weight the muscles have to support (Taylor et al., 1980), extra carried weight increases locomotor costs in a linear manner (Watson et al., 2008). Thus, infant carrying presents a direct metabolic cost to mothers which could be avoided by non-carrying behaviors.

As an example, in baboons, infants are born weighing approximately 7% of their mothers weight (Altmann and Samuels, 1992), which should lead to a significant increase in locomotor costs when carried (roughly linear). During development, baboon infants grow 4-5g a day and can be carried (which includes riding, and infant clinging both dorsally and ventrally) up to seven months by their mothers (Altmann, 1980; Altmann and Samuels, 1992). At the end of the dependency period, this load should add an even further increased energetic burden to mother’s locomotor costs while carrying the infant, and the extra cost should be proportional to the amount of weight gained. However, the amount of maternal care related to locomotion is reduced over the course of an infant’s life (DeVore, 1965), suggesting the total daily energetic burden may remain elevated but stable. Regardless, baboon mothers incur significant energetic stress throughout the dependence period during infant riding directly from the added weight of the infant.

Because metabolic energy requirements are increased during motherhood (Hinde and

Milligan, 2011; Kaplan, 1996), any behavior that influences a mothers ability to forage effectively must be under high selective pressure. Some primates whose offspring ride along on mothers have displayed reduced foraging efficiency (acquiring less food during a time period than non-mothers) during infant care (Altmann, 1980; Johnson, 1986; Mason and Mendoza). Infant carrying directly impacts locomotor speeds during daily foraging as well (Caperos et al., 2012; Pontzer and 39

Wrangham, 2006; Shimooka, 2005; Wrangham, 2000). Wild saddle-back tamarins (Saguinus fusciollis) were found to forage less overall while carrying dependent offspring (offset by paternal care), which is especially significant considering the increased costs of possibly carrying twins and providing food for them (Tardif et al., 1992). An additional burden incurred by carriers and infants being carried is an increased risk of fall (Allman et al., 1998), which could also reduce locomotor speeds to mitigate potential injury. Reduced locomotor speed means lower daily food encounter rates unless the mothers add additional foraging time to make up for the travel distances lost, both of which increase predation risk. However, some studies exploring the negative foraging impacts of infant carrying have found no increase in daily travel distances (Savage et al., 1996).

In addition to the increased metabolic costs, infant carrying (specifically in terrestrial primates) adds stress which the limb bones must habitually resist during infant dependency. Both challenges should impact adult skeletal morphology, although in different ways (Ruff et al., 2006;

Wolff, 1892). Metabolic stresses should produce adaptations in the skeleton to increase energetic economy during locomotion, whereas repeated bone stress should result in enhanced bone robusticity. We see both types of adaptations in non-human primates, although, whether they are due to carrying is currently untested. However, because habitual forces have been used to explain skeletal plasticity in primates (Burgess and Ruff, 2015; Paciulli, 1995), it is possible carrying loads may impact these skeletal morphologies.

Nonhuman primates also engage in object carrying that can induce higher loads. An example are Japanese macaques which have been recorded transporting sweet-potatoes long distances while walking bipedally (Kawai, 1965; Ward and Hopkins, 1993). Depending on the age of the monkey and the weight of the potato, this behavior could induce a significant stress on the skeleton. This feeding preference also reflects human mother-like carrying burdens, where mothers 40 with infant riders would be carrying two distinct loads. Another form of non-infant carrying in non-human primates is the tool use and transport seen in capuchin monkeys. Cebus libidinosus

(wild bearded capuchins) have been shown to transport hammer stones (mean mass ≈ 800 to 1000 g) long distances to feeding locations to process food (Visalberghi et al., 2009). These transport behaviors induce bipedalism in the monkeys (Hanna et al., 2015), which could lead to plastic adaptation similar to the lower limb development in humans (Tardieu, 2010) if practiced often enough. Chimpanzees also have been recorded transporting hammer stones, although the relative distance and load are lower (Hannah and McGrew, 1987).

With a shift to bipedality, carrying mechanics would have changed dramatically, and would have impacted skeletal loading patterns in key ways. As discussed above, the australopithecines had a more ancestral body plan, consisting of skeletal morphologies which suited them to both bipedality and arboreality (Berge, 1994; Ricklan, 1987; Schmid et al., 2013; Zipfel et al., 2011).

Adaptations for arboreality, such as a wide immobile trunk and powerful shoulders seen in the australopithecines (Aiello and Wheeler, 1995), seem to hinder chimpanzees during bipedal carrying activities (Carvalho et al., 2012) but would not have the same negative impact on terrestrial quadrupedal infant riding. During bipedal walking, chimpanzees tend to rotate around a vertical axis to maintain their center of gravity above their feet (Pontzer et al., 2014; Sockol et al.,

2007; Thompson et al., 2015), and a stiff trunk would mean that carrying objects in the upper arms would have caused large rotational torques during each step. Additionally, a vertical trunk orientation would have removed dorsal riding as an option for developing infant riders, requiring clinging which may have been aided by free hands produced by bipedality. Only later in H. erectus do we see a deviation from the ancestral broad thorax (Bramble and Lieberman, 2004; Walker and 41

Leakey, 1993) which may have been an adaptation to bipedal carrying behaviors which differed from the simple infant riding carrying techniques of the non-human primates.

2.7 Carrying in small scale societies

Bipedality has been suggested as an adaptation toward minimizing locomotor costs due to our increased mobility (Cunningham et al., 2010; Usherwood et al., 2012; Webber and Raichlen,

2016). Given the challenges presented by our lack of body hair, upright posture, reduced grasping capabilities, and increased mobility, carrying may have played a significant role in the evolution of human derived adult skeletal morphologies. Furthermore, carrying is practiced often by all members of virtually all societies.

Offspring carrying may be important, especially in small scale societies, as discussed above.

In some foraging societies, mothers often bring their offspring with them out to forage (Lee, 2003;

Marlowe, 2010), and because they are central place foragers, returning to a central location after foraging, the return trip involves a double burden of the foraged goods and their offspring (Kelly,

2013). In addition, data from societies that do not bring their children out to forage show adults still carry very heavy loads (Hilton and Greaves, 2004). As infant care seems to reduce the amount of food primates obtain during foraging bouts (Altmann, 1980; Johnson, 1986; Mason and

Mendoza), hominin foraging must have been significantly more difficult before the advent of slings or other carrying technology. To add to this perceived foraging difficulty, human juvenile periods are extremely long (Klein, 2009; Kramer, 2002), meaning that human mothers tend to carry their offspring, at least part of the time, for many years (Tracer, 2009). Humans also display large amounts of allomaternal care (care provided by individuals other than the mother), which can help reduce the total burden of infant carrying in a species that is both hairless and bipedal

(Crittenden and Marlowe, 2008; Sutou, 2012; Tecot et al., 2013). Yet, research has shown that 42 allomothers who are doing the carrying can come from a range of related community members, and that they include young related individuals (Kramer, 2005). In one study with the Hadza (a small-scale society in Tanzania), children as young as 6 years old spent time carrying infants who were up to 2.5 years old themselves (Crittenden and Marlowe, 2008). The metabolic and impact burdens of carrying in juveniles could be significantly higher due to the higher ratio of load versus carrier body mass.

In addition, hunter-gatherers must often carry large non-infant loads (Hurtado et al., 1985;

Kelly, 2013; Lee, 2003; Marlowe, 2010). These carried masses are not trivial. For example, savanna Pumé women, hunter-gatherers of Venezuela, can carry resources weighing as much as

80% of their bodyweight during foraging trips including firewood, food, and tools (Hilton and

Greaves, 2004). High rates of load carrying may not be uncommon in small scale societies

(Surovell, 2000). More generally, infant carrying represents a universal activity leading to carried loads ranging from 10% to nearly 30% of body mass (Junqueira et al., 2015; Wall-Scheffler et al.,

2007; Watson et al., 2008). Males in hunting and gathering societies also often carry heavy loads, especially when returning from a successful hunt with meat (Hill et al., 1987; Marlowe, 2010;

Pickering and Bunn, 2007).

Added masses, when carried anterior to the center of mass, can be large enough to force bipedal walkers to adjust walking posture into pelvic anteversion (Junqueira et al., 2015) which may require active stabilizing mechanisms in pelvic and trunk musculature that could lead to skeletal modification. Finally, human foragers travel great distances to acquire food when compared to other primates (Foley, 1987). Humans are highly terrestrial (Bramble and Lieberman,

2004; Lieberman et al., 2009; Pontzer, 2017), and an increase in mobility is what seems to mark the evolution of the genus Homo (Aiello and Wells, 2002; Kuhn t al., 2016; Lieberman et al., 2009; 43

Malina and Little, 2008; Pontzer et al., 2012; Pontzer et al., 2015; Raichlen et al., 2011). Increased mobility and longer dependency periods mean more carrying in early Homo compared to other non-human primates. Furthermore, the lack of fur and the transition toward bipedality both have significant consequences for carrying.

2.8 Conclusion

Humans have many locomotor modes, several of which can induce large impact forces thought to be responsible for a number of derived skeletal traits. This dissertation examines specifically the effects of changes in gait with development as well as carrying behaviors which are prevalent among non-human primates and extant humans. Thus, this dissertation follows the logic of Hempel’s raven paradox, where the hypothesis all ravens are black can be supported by both observing all ravens, or all black objects (Hempel, 1945; Watanabe, 1969). By exploring the potential influence of both endurance running and behaviors that are not endurance running on the development of these derived skeletal features we create a better picture of the whole. Carrying behaviors represent a range of activities which are practiced by all members of society and reflect a significant recorded energetic burden of primate mothers (Altmann and Samuels, 1992; Ross,

2001; Wall-Scheffler et al., 2007) as well as living and extinct humans. The aim of this dissertation is to add to the research on derived, impact-reducing skeletal structures, by reexamining carrying behaviors in relation to endurance running. If carrying activities can produce locomotor challenges similar to running, this may point to evolutionary overlap between the two activities, perhaps paving the way for high-speed locomotor activities which took root later in our evolution.

CHAPTER 3: CONCLUSION

3.1 Implications

The results of this dissertation suggest that some running related derived skeletal structures may in fact be the product of locomotor development, carrying, or high-speed walking. In young children, immature gaits lead to both higher average impact forces, but also some instances of significantly lower impact forces (Appendix A). The range of impact forces suggest that children must tolerate relatively high impact forces during important developmental windows (Gosman and

Ketcham, 2008; Ryan and Krovitz, 2006), likely due to the absolute size of their feet and variety of landing foot postures. The use of non-heel-strike foot postures which reduced maximal impact forces occurred at young ages, when carrying is still a normal mode of juvenile transport (Tracer,

2009). Furthermore, the magnitude of impact forces was reliably predicted by the distance of initial ground contact to the ankle joint. This pattern of non-heel-strike steps leading to reduced impact forces is retained in adults using experimentally similar gaits (Webber and Raichlen, 2016) suggesting this biomechanical trait is likely responsible for reduced impact forces in both adults

(experimentally-induced) and children. Since human lower limb development occurs throughout childhood (Raichlen et al., 2015; Tardieu and Trinkaus, 1994; Zeininger et al., 2018), this first study of the dissertation adds to the story of both adult and child skeletal morphologies, and also questions the role of high-speed locomotor activities in the development of adult derived traits in light of significantly high impact forces in children during walking. Finally, the significantly high impact forces tolerated during most steps of immature walkers suggests adaptations for impact resisting structures may be beneficial early in life before endurance running would become a significant behavior. 45

In adults, carrying behaviors, especially at high walking speeds, significantly increase head perturbations during walking, above and beyond those seen during running (Appendix B). Humans’ derived inner-ear skeletal morphologies, specifically enlarge anterior semicircular canal diameter sizes, have been linked to highly agile behaviors, but this research suggest less intense locomotor activities may have had a role in their development. Here, I suggest it is important to separate categories of agile and non-agile in favor of simply acknowledging that many activities can increase head movement. Previous research has suggested that arm swing is an important head stabilizer (Pontzer et al., 2009), and one that is removed when individuals have to carry loads with the arms. Importantly, enlarged, and therefore supposedly more sensitive, semicircular canal diameters appear early in the evolution of the genus Homo, hinting that carrying (perhaps due to a recent lack of body hair) may have played a more important role in the development of this gaze stabilization trait than endurance running. Other traits related to head stabilization Carrying is a behavior that all members of small-scale societies participate in, and any improvements to visual perception, especially when it means removing possible moments of loss of vision, would be an important adaptation. The benefits of an increased visual acuity may be even greater in children who are carrying siblings, who have the double burden of carrying large loads relative to body size and are more likely to be subject to predation.

Finally, this dissertation suggests that while some skeletal traits that have been attributed to endurance running may be more helpful to other behaviors, other traits are clearly derived for high-speed locomotor activities. The gluteus maximus is a large muscle in extant humans that helps both extend the lower limb and counteract trunk pitch. This final study found that running induces significantly higher trunk pitch rates than carrying behaviors, which was not surprising, yet led to significantly higher gluteus maximus excitation (Appendix C). As the GM is a trunk 46 stabilizer it was hypothesized that carrying a significantly heavy load in front of the center of mass would challenge this stabilization system. However, when compared to other lower limb muscles the gluteus maximus stood out in a comparison of running and load carrying. There are other human activities that can increase gluteal excitation including sprinting and climbing (Marzke et al., 1988), but endurance running represents many repeated high trunk pitch incidents. This study highlights the difference between some derived traits possibly being coopted for endurance running, and others that may exist specifically for endurance running.

3.2 Future studies

The results of these dissertation experiments suggest that load carrying can pose a significant locomotor challenge in adults, and that children must navigate a period of significantly high impact forces. How these two locomotor challenges interact outside of experimental settings is uncertain. Additionally, how load carrying affects foot posture in children is not well understood, and it may be that load carrying restricts the possibly protective non-heel-strike steps. In order to understand how load carrying in children can impact adult skeletal morphologies, studies need to be conducted exploring natural carrying in both small- and large-scale societies. With the advent of affordable wireless accelerometers and EMG sensors these types of studies should be possible to conduct to collect across significantly longer time spans.

For the purpose of this dissertation, I only tested a single form of carrying, holding a load in the arms in front of the body. There are many alternative carrying postures including on the shoulder, in a single hand, and all forms of carrying technology (Lee, 2003). Many of these carrying postures impose asymmetrical forces on the body that could further exacerbate some of the challenges found in this dissertation (Mbada et al., 2019). Detailed ethnographic studies of 47 carrying behaviors, frequency, and age demographics will help expand upon the predictive power of children’s role in adult skeletal morphology.

A related concern of these studies is that it was conducted using a largely WEIRD (western

/ white, educated, industrialized, rich, and democratic), population. Exposure to sibling allomaternal care is expected to be significantly different between populations and cultures.

Additionally, availability of transportation likely decreases the frequency of carrying behaviors in western contexts. Children in some small-scale societies also do some foraging for themselves

(Bird and Bliege Bird, 2000; Kramer, 2002), which adds another longer distance walking and carrying activity. Conducting these same tests in foraging populations might uncover significantly different challenges due to habituation to carrying bouts.

Finally, an important inspiration of this dissertation was the question: “What is running?”

Many of the studies that have explored the endurance running hypothesis also come from WEIRD authors, who participate in a very specific form of western competitive running that likely has its roots in English betting and entertainment culture (Gotaas, 2009). The endurance running hypothesis, with its tilt toward individual male hunting, may in fact be a reflection of this competitive and modern physical outlet in a world of limited daily physical challenges. Studies exploring what running means within the United States would likely find that trail runners, fitness enthusiasts, and competitive road racers all have significantly different perspectives.

Ethnographically, groups such as the Rarámuri of Mexico (Balke and Snow, 1965) or historically, the Aztec of the Americas (Schwaller, 2019), celebrate and ritualize running in very different ways than the commercialized fitness events that occur in the United States. Future studies exploring this concept can help solidify what long distance running may have been used for in the ancient past. 48

3.3 Conclusions

The story of human evolution contains a range of novel behaviors, which may include endurance running. However, many of the traits that have been attributed to this high-speed locomotor mode may be better explained and have their origins as adaptations for high-speed walking, or load carrying, or developmental buffers against unstable gaits, which were later coopted. This dissertation found that children experience significantly high impact forces early in their development, before acquiring a mature bipedal gait. These instances of violent ground reaction forces come during critical developmental periods when skeletal morphologies are sensitive to locomotor forces. Traits developed during these stages to resist high impact forces of immature walking gaits may be interpreted as running specific traits later in life.

Similarly, inner ear morphology has been used to inform researchers about changes in hominin locomotor behaviors. However, the appearance of this derived trait in early members of the genus Homo has been linked to high-speed locomotion, specifically running. Yet, high-speed activities do not necessarily lead to high head acceleration which is how this trait has historically been interpreted. Acceleration is a change in velocity, and while rear-foot running typically generates a significant change in velocity of the human body (especially vertical), it is unclear whether this is a running gait that reflects our evolutionary past. Instead, this research suggests that load carrying may better explain the enlargement of semicircular canal diameters. Here, head accelerations were significantly higher when load carrying than during running, likely due to habitual the use of rear-foot gaits during walking, and the added mass of load carrying. Load carrying represents a behavior more probably reflecting our evolutionary past, and is a behavior used by many members of society rather than a specialized hunting activity. 49

Finally, while many derived impact-resisting skeletal traits linked to endurance running may be better explained by high-speed walking or load carrying, there are some clear running specific adaptations. Research for this dissertation found that the enlarged gluteus maximus of H. sapiens acts to resist trunk pitch during running but is not especially active during loaded walking.

Therefore, my research appears to be support the endurance running hypothesis for this trait, suggesting adaptation to long distance running may have occurred over time, perhaps first borrowing traits useful for walking, and then later generating long distance running specific traits later in our evolution. This dissertation highlights the complexity of any evolutionary story, and enhances the evolutionary stories of human walking, load carrying, and running.

REFERENCES

Aiello, L. and Dean, C. D. (Ph (1990). An Introduction to Human Evolutionary Anatomy. Academic Press.

Aiello, L. C. and Wells, J. C. K. (2002). Energetics and the Evolution of the Genus Homo. Annual Review of Anthropology 31, 323–338.

Aiello, L. C. and Wheeler, P. (1995). The Expensive-Tissue Hypothesis: The Brain and the Digestive System in Human and Primate Evolution. Current Anthropology 36, 199–221.

Alexander, R. (2002). Energetics and optimization of human walking and running: The 2000 Raymond Pearl Memorial Lecture. Am. J. Hum. Biol. 14, 641–648.

Allman, J., Rosin, A., Kumar, R. and Hasenstaub, A. (1998). Parenting and survival in anthropoid primates: Caretakers live longer. PNAS 95, 6866–6869.

Altman, A. R. and Davis, I. S. (2012). Barefoot Running: Biomechanics and Implications for Running Injuries. Curr. Sport. Med. Rep. 11, 244–250.

Altmann, J. (1980). Baboon mothers and infants: J. Altmann.

Altmann, J. and Samuels, A. (1992). Costs of maternal care: infant-carrying in baboons. Behav Ecol Sociobiol 29, 391–398.

Amsler, S. J. (2010). Energetic costs of territorial boundary patrols by wild chimpanzees. Am. J. Primatol. 72, 93–103.

Ankel-Simons, F. (2010). Primate Anatomy: An Introduction. Academic Press.

Antón, S. C. (2003). Natural history of Homo erectus. In Yearbook of Physical Anthropology: Vol 46 (ed. Stinson, S.), pp. 126–169. New York: Wiley-Liss, Inc.

Asfaw, B., White, T., Lovejoy, O., Latimer, B., Simpson, S. and Suwa, G. (1999). Australopithecus garhi: a new species of early hominid from Ethiopia. Science 284, 629–635.

Atkin, A. and Bender, M. (1968). Ocular Stabilization During Oscillatory Head Movements - Vestibular System Dysfunction and Relation Between Head and Eye Velocities. Arch. Neurol. 19, 559-.

Balke, B. and Snow, C. (1965). Anthropological and physiological observations on Tarahumara endurance runners. American Journal of Physical Anthropology 23, 293–301.

Barak, M. M., Lieberman, D. E. and Hublin, J.-J. (2011). A Wolff in sheep’s clothing: Trabecular bone adaptation in response to changes in joint loading orientation. Bone 49, 1141–1151.

Bartlett, J. L., Sumner, B., Ellis, R. G. and Kram, R. (2014). Activity and Functions of the Human Gluteal Muscles in Walking, Running, Sprinting, and Climbing. Am. J. Phys. Anthropol. 153, 124–131.

Beck, R. J., Andriacchi, T. P., Kuo, K. N., Fermier, R. W. and Galante, J. O. (1981). Changes in the gait patterns of growing children. J Bone Joint Surg Am 63, 1452–1457. 51

Bennett, M. R., Harris, J. W. K., Richmond, B. G., Braun, D. R., Mbua, E., Kiura, P., Olago, D., Kibunjia, M., Omuombo, C., Behrensmeyer, A. K., et al. (2009). Early Hominin Foot Morphology Based on 1.5- Million-Year-Old Footprints from Ileret, Kenya. Science 323, 1197–1201.

Bentley, G. R. (1985). Hunter-gatherer energetics and fertility: A reassessment of the !Kung San. Hum Ecol 13, 79–109.

Berge, C. (1994). How did the australopithecines walk? A biomechanical study of the hip and thigh of Australopithecus afarensis. Journal of Human Evolution 26, 259–273.

Berger, W., Altenmueller, E. and Dietz, V. (1983). Normal and impaired development of children’s gait. Hum Neurobiol 3, 163–170.

Berger, L. R., de Ruiter, D. J., Churchill, S. E., Schmid, P., Carlson, K. J., Dirks, P. H. G. M. and Kibii, J. M. (2010). Australopithecus sediba: A New Species of Homo-Like Australopith from South Africa. Science 328, 195–204.

Berillon, G. (1999). Geometric pattern of the hominoid hallucal tarsometatarsal complex. Quantifying the degree of hallux abduction in early hominids. Comptes Rendus de l’Académie des Sciences-Series IIA-Earth and Planetary Science 328, 627–633.

Bernhardt, D. B. (1988). Prenatal and Postnatal Growth and Development of the Foot and Ankle. Phys Ther 68, 1831–1839.

Bird, D. W. and Bliege Bird, R. (2000). The Ethnoarchaeology of Juvenile Foragers: Shellfishing Strategies among Meriam Children. Journal of Anthropological Archaeology 19, 461–476.

Birrell, S. A., Hooper, R. H. and Haslam, R. A. (2007). The effect of military load carriage on ground reaction forces. Gait & Posture 26, 611–614.

Blumenschine, R. J. (1986). Early hominid scavenging opportunities: implications of carcass availability in the Serengeti and Ngorongoro ecosystems. B.A.R.

Blumenschine, R. (1987). Characteristics of an Early Hominid Scavenging Niche. Curr. Anthropol. 28, 383– 407.

Bramble, D. and Lieberman, D. (2004). Endurance running and the evolution of Homo. Nature 432, 345– 352.

Burgess, M. L. and Ruff, C. (2015). Ontogenetic Change in Metacarpal, Metatarsal, and Phalangeal Curvature in African Apes. FASEB J 29, 865.18.

Burnett, C. N. and Johnson, E. W. (1971). Development of gait in childhood: Part II. Developmental Medicine & Child Neurology 13, 207–215.

Caperos, J. M., Morcillo, A., Pelaez, F., Fidalgo, A. and Sanchez, S. (2012). The Effect of Infant Body Mass on Carrier Travel Speed in Cotton-top Tamarins (Saguinus oedipus). Int. J. Primatol. 33, 447–459. 52

Carlson, K. J. and Judex, S. (2007). Increased non-linear locomotion alters diaphyseal bone shape. Journal of Experimental Biology 210, 3117–3125.

Carrier, D. R. (1984). The energetic paradox of human running and hominid evolution. Curr. Anthropol. 25, 483–495.

Carvalho, S., Biro, D., Cunha, E., Hockings, K., McGrew, W. C., Richmond, B. G. and Matsuzawa, T. (2012). Chimpanzee carrying behaviour and the origins of human bipedality. Current Biology 22, R180– R181.

Cerling, T. E., Harris, J. M., MacFadden, B. J., Leakey, M. G., Quade, J., Eisenmann, V. and Ehleringer, J. R. (1997). Global vegetation change through the Miocene/Pliocene boundary. Nature 389, 153– 158.

Chapman, C. A. (2000). Determinants of group size in primates: the importance of travel costs. On the move: How and why animals travel in groups.

Churchill, S. E., Holliday, T. W., Carlson, K. J., Jashashvili, T., Macias, M. E., Mathews, S., Sparling, T. L., Schmid, P., Ruiter, D. J. de and Berger, L. R. (2013). The Upper Limb of Australopithecus sediba. Science 340, 1233477.

Cowgill, L. W., Warrener, A., Pontzer, H. and Ocobock, C. (2010). Waddling and toddling: The biomechanical effects of an immature gait. American Journal of Physical Anthropology 143, 52– 61.

Cox, P. G. and Jeffery, N. (2010). Semicircular canals and agility: the influence of size and shape measures. J Anat 216, 37–47.

Crittenden, A. N. and Marlowe, F. W. (2008). Allomaternal care among the Hadza of Tanzania. Hum. Nat.- Interdiscip. Biosoc. Perspect. 19, 249–262.

Cromwell, R. L., Newton, R. A. and Carlton, L. G. (2001). Horizontal plane head stabilization during locomotor tasks. J. Mot. Behav. 33, 49–58.

Crowe, A., Schiereck, P., Deboer, R. and Keessen, W. (1995). Characterization of Human Gait by Means of Body Center-of-Mass Oscillations Derived from Ground Reaction Forces. IEEE Trans. biomed. Eng. 42, 293–303.

Cunningham, C. B., Schilling, N., Anders, C. and Carrier, D. R. (2010). The influence of foot posture on the cost of transport in humans. Journal of Experimental Biology 213, 790–797.

Daoud, A. I., Geissler, G. J., Wang, F., Saretsky, J., Daoud, Y. A. and Lieberman, D. E. (2012). Foot strike and injury rates in endurance runners: a retrospective study. Med Sci Sports Exerc 44, 1325–1334.

Dart, R. A. (1925). Australopithecus africanus - The man-ape of South Africa. Nature 115, 195–199.

Darwin, C. (1871). Descent of Man and Selection in Relation to Sex. London, England: Murray.

DeSilva, J. M. (2010). Revisiting the “midtarsal break.” Am. J. Phys. Anthropol. 141, 245–258. 53

Desilva, J. M., Zipfel, B., Kidd, R. S., Carlson, K. J., Churchill, S. E. and Berger, L. R. (2012). The primitive aspects of the foot and ankle of Australopithecus sediba. Am. J. Phys. Anthropol. 147, 129–129.

DeVore, I. (1965). Mother-infant relations in free-ranging baboons.

Dirks, P. H. G. M., Kibii, J. M., Kuhn, B. F., Steininger, C., Churchill, S. E., Kramers, J. D., Pickering, R., Farber, D. L., Mériaux, A.-S., Herries, A. I. R., et al. (2010). Geological Setting and Age of Australopithecus sediba from Southern Africa. Science 328, 205–208.

Divert, C., Mornieux, G., Baur, H., Mayer, F. and Belli, A. (2005). Mechanical comparison of barefoot and shod running. International Journal of Sports Medicine 26, 593–598.

Divert, C., Mornieux, G., Freychat, P., Baly, L., Mayer, F. and Belli, A. (2008). Barefoot-shod running differences: Shoe or mass effect? Int. J. Sports Med. 29, 512–518.

Dominguez-Rodrigo, M. (2002). Hunting and scavenging by early humans: The state of the debate. J. World Prehist. 16, 1–54.

Duarte, M., Hanna, J., Sanches, E., Liu, Q. and Fragaszy, D. (2012). Kinematics of bipedal locomotion while carrying a load in the arms in bearded capuchin monkeys (Sapajus libidinosus). J. Hum. Evol. 63, 851–858.

Elftman, H. and Manter, J. (1935). Chimpanzee and Human Feet in Bipedal Walking. Am. J. Phys. Anthropol. 20, 69–79.

Fisher, R. A. (2000). The Genetical Theory of Natural Selection. 1 edition. (ed. Bennett, J. H.) Oxford: Oxford University Press.

Foley, R. (1987). Another unique species: patterns in human evolutionary ecology. Longman Sc & Tech.

Foster, A. D., Raichlen, D. A. and Pontzer, H. (2013). Muscle force production during bent-knee, bent-hip walking in humans. J. Hum. Evol. 65, 294–302.

Fries, E. C. and Hellebrandt, F. A. (1943). The influence of pregnancy on the location of the center of gravity, postural stability, and body alignment. American Journal of Obstetrics and Gynecology 46, 374–380.

Frost, B. J., Wylie, D. R. and Wang, Y. C. (1994). The Analysis of Motion in the Visual Systems of Birds. In Perception and Motor Control in Birds: An Ecological Approach (ed. Davies, M. N. O.) and Green, P. R.), pp. 248–269. Berlin, Heidelberg: Springer.

Gatesy, S. M. and Biewener, A. A. (1991). Bipedal locomotion: effects of speed, size and limb posture in birds and humans. Journal of Zoology, Journal of Zoology 224, 127–147.

Gebo, D. L. (1992). Plantigrady and foot adaptation in African apes: Implications for hominid origins. American Journal of Physical Anthropology 89, 29–58. 54

Gosman, J. H. and Ketcham, R. A. (2008). Patterns in ontogeny of human trabecular bone from SunWatch Village in the Prehistoric Ohio Valley: General features of microarchitectural change. American Journal of Physical Anthropology 138, 318–332.

Gotaas, T. (2009). Running: A Global History. University of Chicago Press.

Gray, A. A. (1908). The Labyrinth of Animals: Including Mammals, Birds, Reptiles and Amphibians. J. & A. Churchill.

Green, D. J. and Alemseged, Z. (2012). Australopithecus afarensis Scapular Ontogeny, Function, and the Role of Climbing in Human Evolution. Science 338, 514–517.

Grove, M. (2009). Hunter-gatherer movement patterns: Causes and constraints. J. Anthropol. Archaeol. 28, 222–233.

Gruss, L. T. and Schmitt, D. (2015). The evolution of the human pelvis: changing adaptations to bipedalism, obstetrics and thermoregulation. Philos Trans R Soc Lond B Biol Sci 370,.

Hadžiselimović, H. and Savković, L. J. (1964). Appearance of semicircular canals in birds in relation to mode of life. Cells Tissues Organs 57, 306–315.

Haeusler, M. (2002). New insights into the locomotion of Australopithecus africanus based on the pelvis. Evolutionary Anthropology: Issues, News, and Reviews 11, 53–57.

Haeusler, M. and McHenry, H. M. (2004). Body proportions of Homo habilis reviewed. Journal of Human Evolution 46, 433–465.

Haeusler, M. and McHenry, H. M. (2007). Evolutionary reversals of limb proportions in early hominids? evidence from KNM-ER 3735 (Homo habilis). Journal of Human Evolution 53, 383–405.

Haight, D. J., Lerner, Z. F., Board, W. J. and Browning, R. C. (2014). A comparison of slow, uphill and fast, level walking on lower extremity biomechanics and tibiofemoral joint loading in obese and nonobese adults. Journal of Orthopaedic Research 32, 324–330.

Hallemans, A., D’Août, K., De Clercq, D. and Aerts, P. (2003). Pressure distribution patterns under the feet of new walkers: the first two months of independent walking. Foot Ankle Int 24, 444–453.

Halverson, H. M. (1937). Studies of the grasping responses of early infancy: I. The Pedagogical Seminary and Journal of Genetic Psychology 51, 371–392.

Hamill, J., Derrick, T. R. and Holt, K. G. (1995). Shock attenuation and stride frequency during running. Human Movement Science 14, 45–60.

Hanna, J. B., Schmitt, D., Wright, K., Eshchar, Y., Visalberghi, E. and Fragaszy, D. (2015). Kinetics of bipedal locomotion during load carrying in capuchin monkeys. J. Hum. Evol. 85, 149–156.

Hannah, A. C. and McGrew, W. C. (1987). Chimpanzees using stones to crack open oil palm nuts in Liberia. Primates 28, 31–46. 55

Hasegawa, M., Di Rienzo, A., Kocher, T. D. and Wilson, A. C. (1993). Toward a more accurate time scale for the human mitochondrial DNA tree. J Mol Evol 37, 347–354.

Hatala, K. G., Dingwall, H. L., Wunderlich, R. E. and Richmond, B. G. (2013). Variation in Foot Strike Patterns during Running among Habitually Barefoot Populations. PLOS ONE 8, e52548.

Hempel, C. G. (1945). Studies in the Logic of Confirmation (I.). Mind 54, 1–26.

Hennig, E. M., Staats, A. and Rosenbaum, D. (1994). Plantar Pressure Distribution Patterns of Young School Children in Comparison to Adults. Foot Ankle Int. 15, 35–40.

Herbert, T. D., Lawrence, K. T., Tzanova, A., Peterson, L. C., Caballero-Gill, R. and Kelly, C. S. (2016). Late Miocene global cooling and the rise of modern ecosystems. Nature Geosci 9, 843–847.

Herries, A. I. R., Martin, J. M., Leece, A. B., Adams, J. W., Boschian, G., Joannes-Boyau, R., Edwards, T. R., Mallett, T., Massey, J., Murszewski, A., et al. (2020). Contemporaneity of Australopithecus, Paranthropus, and early Homo erectus in South Africa. Science 368,.

Hill, K., Kaplan, H., Hawkes, K. and Hurtado, A. M. (1987). Foraging decisions among Aché hunter- gatherers: New data and implications for optimal foraging models. Ethology and Sociobiology 8, 1–36.

Hilton, C. E. and Greaves, R. D. (2004). Age, Sex, and Resource Transport in Venezuelan Foragers. In From Biped to Strider (ed. Meldrum, D. J.) and Hilton, C. E.), pp. 163–181. Springer US.

Hinde, K. and Milligan, L. A. (2011). Primate milk: Proximate mechanisms and ultimate perspectives. Evolutionary Anthropology: Issues, News, and Reviews 20, 9–23.

Hirasaki, E., Moore, S. T., Raphan, T. and Cohen, B. (1999). Effects of walking velocity on vertical head and body movements during locomotion. Exp. Brain Res. 127, 117–130.

Hogervorst, T., Bouma, H. W. and de Vos, J. (2009). Evolution of the hip and pelvis. Acta Orthopaedica 80, 1–39.

Holowka, N. B. and Lieberman, D. E. (2018). Rethinking the evolution of the human foot: insights from experimental research. Journal of Experimental Biology 221,.

Huang, T. P. and Kuo, A. D. (2014). Mechanics and energetics of load carriage during human walking. J Exp Biol 217, 605–613.

Hurtado, A. M., Hawkes, K., Hill, K. and Kaplan, H. (1985). Female subsistence strategies among Ache hunter-gatherers of Eastern Paraguay. Hum Ecol 13, 1–28.

Johnson, R. L. (1986). Mother-infant contact and maternal maintenance activities among free-ranging rhesus monkeys. Primates 27, 191–203.

Jones, G. M. and Spells, K. E. (1963). A theoretical and comparative study of the functional dependence of the semicircular canal upon its physical dimensions. Proc. R. Soc. Lond., B, Biol. Sci. 157, 403– 419. 56

Jungers, W. (1982). Lucy Limbs - Skeletal Allometry and Locomotion in Australopithecus-Afarensis. Nature 297, 676–678.

Jungers, W. (1988). Relative Joint Size and Hominoid Locomotor Adaptations with Implications for the Evolution of Hominid Bipedalism. J. Hum. Evol. 17, 247–265.

Junqueira, L. D., Amaral, L. Q., Iutaka, A. S. and Duarte, M. (2015). Effects of transporting an infant on the posture of women during walking and standing still. Gait Posture 41, 841–846.

Kalkwarf, H. J., Laor, T. and Bean, J. A. (2011). Fracture risk in children with a forearm injury is associated with volumetric bone density and cortical area (by peripheral QCT) and areal bone density (by DXA). Osteoporosis Int. 22, 607–616.

Kaplan, H. (1996). A theory of fertility and parental investment in traditional and modern human societies. In Yearbook of Physical Anthropology, Yearbook Series Vol 39: Supplement 23 (ed. Steegmann, A. T.), pp. 91–135. New York: Wiley-Liss, Inc.

Kappeler, P. M. (1998). Nests, tree holes, and the evolution of primate life histories. Am. J. Primatol. 46, 7–33.

Kawai, M. (1965). Newly-acquired pre-cultural behavior of the natural troop of Japanese monkeys on Koshima islet. Primates 6, 1–30.

Kelly, D. R. L. (2013). The Lifeways of Hunter-Gatherers: The Foraging Spectrum. 2 edition. Cambridge: Cambridge University Press.

Kennedy, G. E. (1985). Bone thickness in Homo erectus. Journal of Human Evolution 14, 699–708.

Key, A. J. M. (2016). Manual Loading Distribution During Carrying Behaviors: Implications for the Evolution of the Hominin Hand. PLoS One 11, e0163801.

Kimbel, W. H., Johanson, D. C. and Rak, Y. (1994). The first skull and other new discoveries of Australopithecus afarensis at Hadar, Ethiopia. Nature 368, 449–451.

King, F. A. and Taub, D. M. (1986). Current Perspectives in Primate Biology. Van Nostrand Reinhold.

Klein, R. G. (2009). The Human Career: Human Biological and Cultural Origins, Third Edition. Third Edition, Third Edition. Chicago, IL: University Of Chicago Press.

Kozma, E. E., Raichlen, D. A., Wood, B. M. and Pontzer, H. (2016). Energetics and Muscle Use of Human Climbing. In American Journal of Physical Anthropology, pp. 196–196. Wiley-Blackwell.

Kozma, E. E., Webb, N. M., Harcourt-Smith, W. E., Raichlen, D. A., D’Août, K., Brown, M. H., Finestone, E. M., Ross, S. R., Aerts, P. and Pontzer, H. (2018). Hip extensor mechanics and the evolution of walking and climbing capabilities in humans, apes, and fossil hominins. Proceedings of the National Academy of Sciences 115, 4134–4139.

Kramer, K. L. (2002). Variation in juvenile dependence. Hum Nat 13, 299–325. 57

Kramer, K. L. (2005). Children’s Help and the Pace of Reproduction: Cooperative Breeding in Humans. Evol. Anthropol. 14, 224–237.

Kramer, P. and Eck, G. (2000). Locomotor energetics and leg length in hominid bipedality. J. Hum. Evol. 38, 651–666.

Kuhn, S. L., Raichlen, D. A. and Clark, A. E. (2016). What moves us? How mobility and movement are at the center of human evolution. Evol. Anthropol. 25, 86–97.

Kurki, H. (2011). Pelvic dimorphism in relation to body size and body size dimorphism in humans. Journal of Human Evolution 61, 631–643.

Larney, E. and Larson, S. G. (2004). Compliant walking in primates: Elbow and knee yield in primates compared to other mammals. Am. J. Phys. Anthropol. 125, 42–50.

Larsen, C. S. (2003). Animal Source Foods and Human Health during Evolution. J. Nutr. 133, 3893S-3897S.

Larson, S. G. (2009). Evolution of the Hominin Shoulder: Early Homo. In The First Humans – Origin and Early Evolution of the Genus Homo, pp. 65–75. Springer, Dordrecht.

Latimer, B. (1991). Locomotor adaptations in Australopithecus afarensis: the issue of arboreality. Origine (s) de la Bipédie chez les Hominidés 169–176.

Latimer, B. and Lovejoy, C. (1989). The Calcaneus of Australopithecus-Afarensis and Its Implications for the Evolution of Bipedality. Am. J. Phys. Anthropol. 78, 369–386.

LaVelle, M. (1995). Natural selection and developmental sexual variation in the human pelvis. American Journal of Physical Anthropology 98, 59–72.

Le Galliard, J. F., Clobert, J. and Ferriere, R. (2004). Physical performance and darwinian fitness in lizards. Nature 432, 502–505.

Leakey, M. D. and Hay, R. L. (1979). Pliocene footprints in the Laetolil Beds at Laetoli, northern Tanzania. , Published online: 22 March 1979; | doi:10.1038/278317a0 278, 317–323.

Lee, R. B. (2003). The Dobe Ju/’hoansi. [Belmont, Calif.] ; London: Wadsworth/ Thomson Learning.

Lee, C. R. and Farley, C. T. (1998). Determinants of the center of mass trajectory in human walking and running. Journal of Experimental Biology 201, 2935–2944.

Levinger, P. and Gilleard, W. (2005). The heel strike transient during walking in subjects with patellofemoral pain syndrome. Physical Therapy in Sport 6, 83–88.

Lewton, K. L. and Scott, J. E. (2017). Ischial Form as an Indicator of Bipedal Kinematics in Early Hominins: A Test Using Extant Anthropoids. Anat Rec (Hoboken) 300, 845–858.

Liebenberg, L. (2006). Persistence hunting by modern hunter-gatherers. Curr. Anthropol. 47, 1017–1025.

Liebenberg, L. (2008). The relevance of persistence hunting to human evolution. Journal of Human Evolution 55, 1156–1159. 58

Lieberman, D. (2011). The Evolution of the Human Head. Harvard University Press.

Lieberman, D. E. (2012). What We Can Learn About Running from Barefoot Running: An Evolutionary Medical Perspective. Exerc. Sport Sci. Rev. 40, 63–72.

Lieberman, D. E., Raichlen, D. A., Pontzer, H., Bramble, D. M. and Cutright-Smith, E. (2006). The human gluteus maximus and its role in running. J. Exp. Biol. 209, 2143–2155.

Lieberman, D. E., Bramble, D. M., Raichlen, D. A. and Shea, J. J. (2007). The Evolution of Endurance Running and the Tyranny of Ethnography: A Reply to Pickering and Bunn (2007).

Lieberman, D. E., Bramble, D. M., Raichlen, D. A. and Shea, J. J. (2009). Brains, Brawn, and the Evolution of Human Endurance Running Capabilities. In The First Humans – Origin and Early Evolution of the Genus Homo (ed. Grine, F. E.), Fleagle, J. G.), and Leakey, R. E.), pp. 77–92. Springer Netherlands.

Lieberman, D. E., Venkadesan, M., Werbel, W. A., Daoud, A. I., D’Andrea, S., Davis, I. S., Mang’Eni, R. O. and Pitsiladis, Y. (2010). Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature 463, 531–535.

Light, L. and Mclellan, G. (1977). Skeletal Transients Associated with Heel Strike. J. Physiol.-London 272, P9–P10.

Lordkipanidze, D., Jashashvili, T., Vekua, A., León, M. S. P. de, Zollikofer, C. P. E., Rightmire, G. P., Pontzer, H., Ferring, R., Oms, O., Tappen, M., et al. (2007). Postcranial evidence from early Homo from Dmanisi, Georgia. Nature 449, nature06134.

Lowie, R. H. (1924). Notes on Shoshonean ethnography. Anthropological papers of the AMNH; v. 20, pt. 3.

MacLellan, M. J., Ivanenko, Y. P., Cappellini, G., Labini, F. S. and Lacquaniti, F. (2012). Features of hand- foot crawling behavior in human adults. Journal of Neurophysiology 107, 114–125.

Malina, R. M. and Little, B. B. (2008). Physical activity: The present in the context of the past. Am. J. Hum. Biol. 20, 373–391.

Malinzak, M. D., Kay, R. F. and Hullar, T. E. (2012). Locomotor head movements and semicircular canal morphology in primates. PNAS 109, 17914–17919.

Marlowe, F. W. (2005). Hunter-gatherers and human evolution. Evol. Anthropol. 14, 54–67.

Marlowe, F. (2010). The Hadza: Hunter-gatherers of Tanzania. University of California Press.

Marzke, M. W., Longhill, J. M. and Rasmussen, S. A. (1988). Gluteus maximus muscle function and the origin of hominid bipedality. American Journal of Physical Anthropology 77, 519–528.

Mason, W. A. and Mendoza, S. P. Primate Social Conflict. SUNY Press. 59

Mbada, C. E., Adebayo, O. S., Olaogun, M. O., Johnson, O. E., Ogundele, A. O., Ojukwu, C. P., Akinwande, O. A. and Makinde, M. O. (2019). Infant-carrying techniques: Which is a preferred mother- friendly method? Health Care for Women International 0, 1–14.

McHenry, H. M. and Coffing, and K. (2000). Australopithecus to Homo: Transformations in Body and Mind. Annual Review of Anthropology 29, 125–146.

Micheels, A., Eronen, J. and Mosbrugger, V. (2009). The Late Miocene climate response to a modern Sahara desert. Global and Planetary Change 67, 193–204.

Millet, G. Y. (2011). Can Neuromuscular Fatigue Explain Running Strategies and Performance in Ultra- Marathons? The Flush Model. Sports Med. 41, 489–506.

Mulavara, A. P. and Bloomberg, J. J. (2002). Identifying head-trunk and lower limb contributions to gaze stabilization during locomotion. J Vestib Res 12, 255–269.

Neumann, D. A. and Cook, T. M. (1985). Effect of Load and Carrying Position on the Electromyographic Activity of the Gluteus Medius Muscle During Walking. Physical Therapy 65, 305–311.

Novacheck, T. (1998). The biomechanics of running. Gait & Posture 7, 77–95.

O’Connell, J. F., Hawkes, K. and Jones, N. B. (1988). Hadza scavenging: Implications for Plio/Pleistocene hominid subsistence. Current Anthropology 356–363.

Ohman, J. C., Krochta, T. J., Lovejoy, C. O., Mensforth, R. P. and Latimer, B. (1997). Cortical bone distribution in the femoral neck of hominoids: Implications for the locomotion of Australopithecus afarensis. American Journal of Physical Anthropology 104, 117–131.

O’Keefe, J. H., Vogel, R., Lavie, C. J. and Cordain, L. (2011). Exercise Like a Hunter-Gatherer: A Prescription for Organic Physical Fitness. Progress in Cardiovascular Diseases 53, 471–479.

Oman, C. M., Marcus, E. N. and Curthoys, I. S. (1987). The Influence of Semicircular Canal Morphology on Endolymph Flow Dynamics: An Anatomically Descriptive Mathematical Model. Acta Oto- Laryngologica 103, 1–13.

Opala-Berdzik, A., Bacik, B., Cieslinska-Swider, J., Plewa, M. and Gajewska, M. (2010). The influence of pregnancy on the location of the center of gravity in standing position. J Hum Kinet 26, 5–11.

Paciulli, L. M. (1995). Ontogeny of phalangeal curvature and positional behavior in chimpanzees. Am J Phys Anthropol 20, 165.

Pickering, T. R. and Bunn, H. T. (2007). The endurance running hypothesis and hunting and scavenging in savanna-woodlands. J. Hum. Evol. 53, 434–438.

Pontzer, H. (2007). Effective limb length and the scaling of locomotor cost in terrestrial animals. Journal of Experimental Biology 210, 1752.

Pontzer, H. (2017). Economy and Endurance in Human Evolution. Current Biology 27, R613–R621. 60

Pontzer, H. and Wrangham, R. W. (2004). Climbing and the daily energy cost of locomotion in wild chimpanzees: implications for hominoid locomotor evolution. J. Hum. Evol. 46, 317–335.

Pontzer, H. and Wrangham, R. W. (2006). Ontogeny of Ranging in Wild Chimpanzees. Int J Primatol 27, 295.

Pontzer, H., Lieberman, D. E., Momin, E., Devlin, M. J., Polk, J. D., Hallgrímsson, B. and Cooper, D. M. L. (2006). Trabecular bone in the bird knee responds with high sensitivity to changes in load orientation. Journal of Experimental Biology 209, 57–65.

Pontzer, H., Holloway, J. H., Raichlen, D. A. and Lieberman, D. E. (2009). Control and function of arm swing in human walking and running. Journal of Experimental Biology 212, 523–534.

Pontzer, H., Rolian, C., Rightmire, G. P., Jashashvili, T., de Leon, M. S. P., Lordkipanidze, D. and Zollikofer, C. P. E. (2010). Locomotor anatomy and biomechanics of the Dmanisi hominins. J. Hum. Evol. 58, 492–504.

Pontzer, H., Raichlen, D. A., Wood, B. M., Mabulla, A. Z. P., Racette, S. B. and Marlowe, F. W. (2012). Hunter-Gatherer Energetics and Human Obesity. PLoS ONE 7, e40503.

Pontzer, H., Raichlen, D. A. and Rodman, P. S. (2014). Bipedal and quadrupedal locomotion in chimpanzees. Journal of Human Evolution 66, 64–82.

Pontzer, H., Raichlen, D. A., Wood, B. M., Emery Thompson, M., Racette, S. B., Mabulla, A. Z. P. and Marlowe, F. W. (2015). Energy expenditure and activity among Hadza hunter-gatherers. Am. J. Hum. Biol. 27, 628–637.

Pozzo, T., Berthoz, A. and Lefort, L. (1990). Head stabilization during various locomotor tasks in humans. Exp Brain Res 82, 97–106.

Preece, S. J., Mason, D. and Bramah, C. (2016). The coordinated movement of the spine and pelvis during running. Human Movement Science 45, 110–118.

Preuschoft, H. (2004). Mechanisms for the acquisition of habitual bipedality: are there biomechanical reasons for the acquisition of upright bipedal posture? Journal of Anatomy 204, 363–384.

Rahnama, N., Lees, A. and Reilly, T. (2006). Electromyography of selected lower-limb muscles fatigued by exercise at the intensity of soccer match-play. Journal of Electromyography and Kinesiology 16, 257–263.

Raichlen, D. A. and Polk, J. D. (2013). Linking brains and brawn: exercise and the evolution of human neurobiology. Proc. R. Soc. B-Biol. Sci. 280, 20122250.

Raichlen, D. A., Gordon, A. D., Harcourt-Smith, W. E. H., Foster, A. D. and Haas, Wm. R. (2010). Laetoli Footprints Preserve Earliest Direct Evidence of Human-Like Bipedal Biomechanics. PLoS One 5,.

Raichlen, D. A., Armstrong, H. and Lieberman, D. E. (2011). Calcaneus length determines running economy: Implications for endurance running performance in modern humans and Neandertals. Journal of Human Evolution 60, 299–308. 61

Raichlen, D. A., Gordon, A. D., Foster, A. D., Webber, J. T., Sukhdeo, S. M., Scott, R. S., Gosman, J. H. and Ryan, T. M. (2015). An ontogenetic framework linking locomotion and trabecular bone architecture with applications for reconstructing hominin life history. Journal of human evolution 81, 1–12.

Raichlen, D. A., Webber, J. T. and Pontzer, H. (2019). The evolution of the human endurance phenotype. Routledge Handbook of Sport and Exercise Systems Genetics 135–147.

Rak, Y. (1991). Lucy’s pelvic anatomy: its role in bipedal gait. Journal of Human Evolution 20, 283–290.

Revill, A. L., Perry, S. D., Michelle Edwards, A. and Dickey, J. P. (2008). Variability of the impact transient during repeated barefoot walking trials. Journal of biomechanics 41, 926–930.

Reynolds, T. R. (1987). Stride length and its determinants in humans, early hominids, primates, and mammals. American Journal of Physical Anthropology 72, 101–115.

Richmond, B. G. (2000). Ontogeny and biomechanics of phalangeal form in primates.

Richmond, B. (2007). Biomechanics of phalangeal curvature. Journal of Human Evolution 53, 678–690.

Ricklan, D. (1987). Functional anatomy of the hand of Australopithecus africanus. Journal of Human Evolution 16, 643–664.

Roberts, T. J. and Gabaldón, A. M. (2008). Interpreting muscle function from EMG: lessons learned from direct measurements of muscle force. Integr Comp Biol 48, 312–320.

Rodman, P. and Mchenry, H. (1980). Bioenergetics and the Origin of Hominid Bipedalism. Am. J. Phys. Anthropol. 52, 103–106.

Rolian, C., Lieberman, D. E., Hamill, J., Scott, J. W. and Werbel, W. (2009). Walking, running and the evolution of short toes in humans. J. Exp. Biol. 212, 713–721.

Rose, M. (1991). The process of bipedalization in hominids. Otigine (s) de la Bipedie chez les hominides. 37–48.

Ross, C. (2001). Park or Ride? Evolution of Infant Carrying in Primates. International Journal of Primatology 22, 749–771.

Roters, B. and Henrich, R. (2010). The middle to late Miocene climatic development of Southwest Africa derived from the sedimentological record of ODP Site 1085A. Int J Earth Sci (Geol Rundsch) 99, 459–471.

Ruff, C. (2003a). Growth in bone strength, body size, and muscle size in a juvenile longitudinal sample. Bone 33, 317–329.

Ruff, C. (2003b). Ontogenetic adaptation to bipedalism: age changes in femoral to humeral length and strength proportions in humans, with a comparison to baboons. J. Hum. Evol. 45, 317–349. 62

Ruff, C. (2009). Relative limb strength and locomotion in Homo habilis. Am. J. Phys. Anthropol. 138, 90– 100.

Ruff, C. B. and Hayes, W. C. (1982). Subperiosteal expansion and cortical remodeling of the human femur and tibia with aging. Science 217, 945–948.

Ruff, C., Holt, B. and Trinkaus, E. (2006). Who’s afraid of the big bad Wolff?: “Wolff’s law” and bone functional adaptation. Am. J. Phys. Anthropol. 129, 484–498.

Ruff, C. B., Burgess, M. L., Ketcham, R. A. and Kappelman, J. (2016). Limb Bone Structural Proportions and Locomotor Behavior in A.L. 288-1 (“Lucy”). PLOS ONE 11, e0166095.

Ryan, T. M. and Krovitz, G. E. (2006). Trabecular bone ontogeny in the human proximal femur. Journal of Human Evolution 51, 591–602.

Saibene, F. and Minetti, A. E. (2003). Biomechanical and physiological aspects of legged locomotion in humans. Eur. J. Appl. Physiol. 88, 297–316.

Savage, A., Snowdon, C. T., Giraldo, L. H. and Soto, L. H. (1996). Parental Care Patterns and Vigilance in Wild Cotton-Top Tamarins (Saguinus oedipus). In Adaptive Radiations of Neotropical Primates, pp. 187–199. Springer, Boston, MA.

Schmid, P., Churchill, S. E., Nalla, S., Weissen, E., Carlson, K. J., Ruiter, D. J. de and Berger, L. R. (2013). Mosaic Morphology in the Thorax of Australopithecus sediba. Science 340,.

Schwaller, J. F. (2019). The Fifteenth Month: Aztec History in the Rituals of Panquetzaliztli. Norman: University of Oklahoma Press.

Shapiro, L. (1993). Evaluation of “unique” aspects of human vertebral bodies and pedicles with a consideration of Australopithecus africanus. Journal of Human Evolution 25, 433–470.

Shea, J. J. (2006). The origins of lithic projectile point technology: evidence from Africa, the Levant, and Europe. Journal of Archaeological Science 33, 823–846.

Shefelbine, S. J., Tardieu, C. and Carter, D. R. (2002). Development of the femoral bicondylar angle in hominid bipedalism. Bone 30, 765–770.

Sheridan, M. D. (1975). The developmental progress of infants and young children. 3rd ed. London, H.M.S.O.,.

Shimooka, Y. (2005). Sexual differences in ranging of Ateles belzebuth belzebuth at La Macarena, Colombia. International Journal of Primatology 26, 385–406.

Simon, S. R., Paul, I. L., Mansour, J., Munro, M., Abernethy, P. J. and Radin, E. L. (1981). Peak dynamic force in human gait. Journal of Biomechanics 14, 817–822.

Simpson, S. W., Quade, J., Levin, N. E., Butler, R., Dupont-Nivet, G., Everett, M. and Semaw, S. (2008). A Female Homo erectus Pelvis from Gona, Ethiopia. Science 322, 1089–1092. 63

Slijper, E. J. (1942). Biologic-anatomical investigations on the bipedal gait and upright posture in mammals, with special reference to a little goat, born without forelegs. Proc Konink Ned Akad Wet 45, 288– 295.

Sockol, M. D., Raichlen, D. A. and Pontzer, H. (2007). Chimpanzee locomotor energetics and the origin of human bipedalism. Proc. Natl. Acad. Sci. U. S. A. 104, 12265–12269.

Spoor, F. (2003). The semicircular canal system and locomotor behaviour, with special reference to hominin evolution. Courier-Forschungsinstitut Senckenberg 93–104.

Spoor, F. and Zonneveld, F. (1998). Comparative review of the human bony labyrinth. Am. J. Phys. Anthropol. Suppl 27, 211–251.

Spoor, F., Wood, B. and Zonneveld, F. (1994). Implications of Early Hominid Labyrinthine Morphology for Evolution of Human Bipedal Locomotion. Nature 369, 645–648.

Spoor, F., Garland, T., Krovitz, G., Ryan, T. M., Silcox, M. T. and Walker, A. (2007). The primate semicircular canal system and locomotion. PNAS 104, 10808–10812.

Stern, J. T. (1972). Anatomical and functional specializations of the human gluteus maximus. Am. J. Phys. Anthropol. 36, 315–339.

Stern, J. and Susman, R. (1983). The Locomotor Anatomy of Australopithecus Afarensis. Am. J. Phys. Anthropol. 60, 279–317.

Stern, J. T., Paré, E. B. and Schwartz, J. M. (1980). New perspectives on muscle use during locomotion: electromyographic studies of rapid and complex behaviors. J Am Osteopath Assoc 80, 287–291.

Steudel, K. (1990). The work and energetic cost of locomotion. I. The effects of limb mass distribution in quadrupeds. Journal of Experimental Biology 154, 273–285.

Steudel-Numbers, K. L. (2006). Energetics in Homo erectus and other early hominins: The consequences of increased lower-limb length. Journal of Human Evolution 51, 445–453.

Steudel-Numbers, K. L. and Tilkens, M. J. (2004). The effect of lower limb length on the energetic cost of locomotion: implications for fossil hominins. Journal of Human Evolution 47, 95–109.

Steudel-Numbers, K. L., Weaver, T. D. and Wall-Scheffler, C. M. (2007). The evolution of human running: Effects of changes in lower-limb length on locomotor economy. J. Hum. Evol. 53, 191–196.

Surovell, T. A. (2000). Early Paleoindian Women, Children, Mobility, and Fertility. American Antiquity 65, 493–508.

Susman, R., Stern, J. and Jungers, W. (1984). Arboreality and Bipedality in the Hadar Hominids. Folia Primatol. 43, 113–156.

Sutherland, D. (1997). Review paper: The development of mature gait. Gait & Posture 6, 163–170. 64

Sutherland, D. H., Olshen, R., Cooper, L. and Woo, S. (1980). The development of mature gait. J. Bone Joint Surg.-Am. Vol. 62, 336–353.

Sutou, S. (2012). Hairless mutation: a driving force of humanization from a human–ape common ancestor by enforcing upright walking while holding a baby with both hands. Genes to Cells 17, 264–272.

Sylvester, A. D., Mahfouz, M. R. and Kramer, P. A. (2011). The Effective Mechanical Advantage of A.L. 129-1a for Knee Extension. Anat. Rec. 294, 1486–1499.

Tardieu, C. (2010). Development of the human hind limb and its importance for the evolution of bipedalism. Evolutionary Anthropology: Issues, News, and Reviews 19, 174–186.

Tardieu, C. and Trinkaus, E. (1994). Early ontogeny of the human femoral bicondylar angle. American journal of physical anthropology 95, 183–195.

Tardif, S. D., Carson, R. L. and Gangaware, B. L. (1992). Infant-care Behavior of Non-reproductive Helpers in a Communal-care Primate, the Cotton-top Tamarin (Saguinus oedipus). Ethology 92, 155–167.

Taylor, C., Heglund, N., Mcmahon, T. and Looney, T. (1980). Energetic Cost of Generating Muscular Force During Running - a Comparison of Large and Small Animals. J. Exp. Biol. 86, 9–18.

Tecot, S. R., Baden, A. L., Romine, N. K. and Kamilar, J. M. (2012). Infant parking and nesting, not allomaternal care, influence Malagasy primate life histories. Behav Ecol Sociobiol 66, 1375–1386.

Tecot, S. R., Baden, A. L., Romine, N. and Kamilar, J. M. (2013). Reproductive strategies and infant care in the malagasy primates. Building Babies: Primate Development in Proximate and Ultimate Perspective 321–359.

Thompson, N. E., Demes, B., O’Neill, M. C., Holowka, N. B. and Larson, S. G. (2015). Surprising trunk rotational capabilities in chimpanzees and implications for bipedal walking proficiency in early hominins. Nature Communications 6, ncomms9416.

Thorstensson, A., Nilsson, J., Carlson, H. and Zomlefer, M. R. (1984). Trunk movements in human locomotion. Acta Physiologica Scandinavica 121, 9–22.

Tobias, P. V. (1965). Australopithecus, Homo Habilis, Tool-Using and Tool-Making. The South African Archaeological Bulletin 20, 167–192.

Tracer, D. P. (2009). Infant carrying and prewalking locomotor development: proximate and evolutionary perspectives. Am. J. Phys. Anthropol. 257–257.

Usherwood, J. R., Channon, A. J., Myatt, J. P., Rankin, J. W. and Hubel, T. Y. (2012). The Human Foot and Heel–Sole–Toe Walking Strategy: A Mechanism Enabling an Inverted Pendular Gait with Low Isometric Muscle Force? J. R. Soc. Interface.

Venkadesan, M., Yawar, A., Eng, C. M., Dias, M. A., Singh, D. K., Tommasini, S. M., Haims, A. H., Bandi, M. M. and Mandre, S. (2020). Stiffness of the human foot and evolution of the transverse arch. Nature 579, 97–100. 65

Vigotsky, A. D., Halperin, I., Lehman, G. J., Trajano, G. S. and Vieira, T. M. (2018). Interpreting Signal Amplitudes in Surface Electromyography Studies in Sport and Rehabilitation Sciences. Front Physiol 8,.

Visalberghi, E., Spagnoletti, N., Silva, E. D. R. da, Andrade, F. R. D., Ottoni, E., Izar, P. and Fragaszy, D. (2009). Distribution of potential suitable hammers and transport of hammer tools and nuts by wild capuchin monkeys. Primates 50, 95–104.

Wagnild, J. and Wall-Scheffler, C. M. (2013). Energetic Consequences of Human Sociality: Walking Speed Choices among Friendly Dyads. PLoS One 8,.

Walker, A. and Leakey, R. E. (1993). The Nariokotome Homo erectus skeleton. Harvard University Press.

Wall-Scheffler, C. M. and Myers, M. J. (2013). Reproductive costs for everyone: How female loads impact human mobility strategies. J. Hum. Evol. 64, 448–456.

Wall-Scheffler, C. m., Geiger, K. and Steudel-Numbers, K. l. (2007). Infant carrying: The role of increased locomotory costs in early tool development. Am. J. Phys. Anthropol. 133, 841–846.

Ward, C. V. (1993). Torso morphology and locomotion in Proconsul nyanzae. Am. J. Phys. Anthropol. 92, 291–328.

Ward, C. V. (2002). Interpreting the posture and locomotion of Australopithecus afarensis: Where do we stand? Am. J. Phys. Anthropol. 119, 185–215.

Ward, J. P. and Hopkins, W. D. (1993). Primate Laterality: Current Behavioral Evidence of Primate Asymmetries. Springer Science & Business Media.

Ward, C., Leakey, M. and Walker, A. (1999). The new hominid species Australopithecus anamensis. Evolutionary Anthropology: Issues, News, and Reviews 7, 197–205.

Watanabe, S. (1969). Knowing and guessing; a quantitative study of inference and information. New York : Wiley.

Watson, J. C., Payne, R. C., Chamberlain, A. T., Jones, R. K. and Sellers, W. I. (2008). The energetic costs of load-carrying and the evolution of bipedalism. J. Hum. Evol. 54, 675–683.

Webber, J. T. and Raichlen, D. A. (2013). Heel-strike and impact transient during bipedal walking: Implications for the acquisition of a habitual bipedal gait. Am. J. Phys. Anthropol. 150, 287–287.

Webber, J. T. and Raichlen, D. A. (2016). The role of plantigrady and heel-strike in the mechanics and energetics of human walking with implications for the evolution of the human foot. Journal of Experimental Biology 219, 3729–3737.

Webber, J. T. and Raichlen, D. A. (2017). Effects of high speed and weighted walking on head pitch and knee forces. Am J Phys Anthropol 162, 1–423.

Wells, J. C. K., DeSilva, J. M. and Stock, J. T. (2012). The obstetric dilemma: an ancient game of Russian roulette, or a variable dilemma sensitive to ecology? Am. J. Phys. Anthropol. 149 Suppl 55, 40–71. 66

West-Eberhard, M. J. (2003). Developmental Plasticity and Evolution. 1st ed. New York, NY: Oxford University Press, USA.

Wilson, V. J. (2013). Mammalian Vestibular Physiology. Springer Science & Business Media.

Wirtz, P. and Ries, G. (1992). The Pace of Life - Reanalysed: Why Does Walking Speed of Pedestrians Correlate With City Size? Behaviour 123, 77–83.

Wittman, A. B. and Wall, L. L. (2007). The Evolutionary Origins of Obstructed Labor: Bipedalism, Encephalization, and the Human Obstetric Dilemma. Obstetrical & Gynecological Survey 62, 739– 748.

Wolff, J. (1892). Das gesetz der transformation der knochen. DMW-Deutsche Medizinische Wochenschrift 19, 1222–1224.

Wrangham, R. W. (2000). Why are male chimpanzees more gregarious than mothers? A scramble competition hypothesis. Primate males: causes and consequences of variation in group composition. Cambridge University Press, Cambridge 248–258.

Zeininger, A., Schmitt, D., Jensen, J. L. and Shapiro, L. J. (2018). Ontogenetic changes in foot strike pattern and calcaneal loading during walking in young children. Gait & Posture 59, 18–22.

Zihlman, A. L. and Brunker, L. (1979). Hominid bipedalism: then and now. Yb. Physical Anthropol 22, 132– 162.

Zimmermann, C. L., Cook, T. M., Bravard, M. S., Hansen, M. M., Honomichl, R. T., Karns, S. T., Lammers, M. A., Steele, S. A., Yunker, L. K. and Zebrowski, R. M. (1994). Effects of Stair-Stepping Exercise Direction and Cadence on EMG Activity of Selected Lower Extremity Muscle Groups. J Orthop Sports Phys Ther 19, 173–180.

Zipfel, B., DeSilva, J. M., Kidd, R. S., Carlson, K. J., Churchill, S. E. and Berger, L. R. (2011). The Foot and Ankle of Australopithecus sediba. Science 333, 1417–1420.

APPENDIX A: MANUSCRIPT 1

Initial ground contact location, impact forces, and the development of heel-strike walking in children

James T. Webber1,*, Adam D Foster2, James H. Gosman3, Timothy M. Ryan4, and David A. Raichlen5

1 School of Anthropology, University of Arizona. Tucson, AZ 85721, USA

2 Department of Anatomy, School of Osteopathic Medicine, Campbell University, Buies Creek, NC 27506, USA

3 Department of Anthropology, The Ohio State University, Columbus, OH 43210-1106, USA

4 Department of Anthropology, Pennsylvania State University, University Park, PA 16802, USA

5 Human and Evolutionary Biology Section, Department of Biological Science, University of Southern California, Los Angeles, CA 90089, USA

* [email protected]

Abstract Background Children transition to a committed heel-strike walking pattern between years three and four. Prior to the adoption of habitual rearfoot strikes, children display a variety of foot strike patterns including forefoot or midfoot touchdowns. However, the role of foot strike pattern variation and the related impact forces during lower limb development is not well understood. Rearfoot strikes cause a rapid increase in the ground reaction force magnitude during walking and running, called the impact transient. Compared with non- rearfoot-strike initial foot contacts, rearfoot strikes during adult walking lead to significantly higher impact transients, suggesting foot strike pattern can alter impact transients.

Research Question We examined whether non-rearfoot-striking gaits used by children at young ages reduce impact transients.

Methods Using an experimental approach, we compared impact transients, speed, and ground contact location in mature walkers (children >3.5 years, n = 13), immature walkers (children <3.5 years, n = 11; divided following gait stabilization proposed to occur around 4 years), and adults (n = 10) during walking using kinetic and kinematic data to determine whether children use gaits that minimize impact transients.

Results Child gaits displayed average impact transients significantly higher than adults (p < 0.0001). The immature group varied significantly in center of pressure location at touchdown with a large proportion of initial ground contact occurring near the ankle (p = 0.045). However, impact transients were significantly reduced as average ground contact location moved both anteriorly and posteriorly to the ankle joint (p < 0.0001).

Conclusions The absolute distance from the ankle provides a more nuanced explanation of impact transient magnitude than foot strike pattern alone. Changes in impact forces during the development of mature walking gaits may be crucial in understanding adult foot morphology, and this study contributes new quantitative insight into the kinetics of foot-strike in young walkers.

Introduction Early human growth and development is characterized by a period of significant lower limb anatomical change and locomotor force variation (1). Between ages one and three, human femoral strength increases rapidly (2), and the orientation, thickness, and volume of trabecular bone in the lower limb changes (3,4). These shifts are attributed to the transition to unassisted bipedalism which occurs in most children around year one (5), and likely reflects variation in lower limb kinematics (1). Young walkers often experience higher impact forces than adults relative to bodyweight during unassisted walking (6,7), suggesting children encounter a range of locomotor forces throughout development. Thus, it is unclear how young children accommodate loads while practicing a range of locomotor behaviors (such as crawling or assisted walking) that differ from adults. Here, we explore how children experience external locomotor loading during bipedal walking while bone strength is still lower than adult values.

The ontogeny of human gait is divided into two stages, where a transition between immature and mature walking occurs between three and a half to four years of age (8). A consistent rearfoot strike (RFS) at foot touchdown is a key component of this transition between gaits (8,9).

An extended leg and accompanying heel strike improve walking economy (10), marking these attributes as adult-like. Yet, young children (< 3.5 years) often contact the ground with the foot plantarflexed rather than dorsiflexed prior to touchdown (6,11), leading to initial contact at the mid- or forefoot. This kinematic shift in foot strike is often interpreted in the context of gait maturation (8) and neurobiological development (12), but it is possible that young children adopt these foot strike patterns to alter loading patterns at ground contact.

During locomotion, the interaction between the foot and the ground causes a reaction force with an impact peak known as the impact transient (IT) shortly after heel touchdown (13–16).

Non- rearfoot-strike (NRFS) gaits (where landing occurs on the mid- or fore-foot, anterior to the 70 ankle, and the heel touches down after initial contact) reduce the magnitude and rate of loading

(ROL) of the IT when compared to RFS walking and running in adults (13,15,17,18). While RFS walking is an energetically economical gait in adults compared to NRFS gaits (10,19), reduced ITs during the early development of walking could still make NRFS steps beneficial, especially in young children whose developing skeleton may be susceptible to injury or deformation in the context of relatively high ITs (20). For example, since fracture risk in children is associated with bone mechanical properties (21), locomotor strategies such as NRFS walking may be a valuable component to avoiding bone damage in developing walkers.

Previous research by Zeininger and colleagues (6) found that NRFS steps in young children are often midfoot strikes resulting in a flat orientation and lead to higher ITs than RFS gaits. This result is contrary to the relationship between foot strike patterns and ITs in adults (17), suggesting there may be more to impact forces than foot posture alone. While high ITs in adults are often considered dangerous (13,22), many studies have suggested that forces experienced during ontogeny shape the growth of cortical and trabecular bone (23–29). Therefore, high ITs during ontogeny may help shape adult lower limb morphology. Thus, the goal of this study is to build upon Zeininger et al’s (6) results and examine why NRFS steps in young children appear to show a different loading pattern compared with NRFS walking in adults.

As a foundation for determining why NRFS steps may not always lead to reduced ITs, we use a modified model described by Lieberman et al. (15). These researchers modeled the foot and shank as an L-shaped double pendulum, and showed that, in NRFS gaits, as ground contact location moves anterior to the ankle (Fig 1), a larger proportions of the impact forces are converted to rotational energy (15). Therefore, foot contact directly below the ankle joint limits the amount of impact force that can be translated into rotational energy and should result in high ITs (6). We 71 suggest an alteration of this model, to include a heel posterior to the ankle. In this case, the foot and ankle are modeled as an inverted T, and landing on the portion of the foot posterior to the ankle can also lead to a conversion of impact force into rotational energy. In this version of the model, the highest impacts would be experienced during landings where the center of pressure is directly under the ankle. Based on the inverted T model, it is a flat-foot strike, similar those described in children by of Zeininger et al. (6), which minimize the conversion of landing forces into foot rotation and would be associated with the highest impact forces. Landing with the center of pressure either posterior to, or anterior to the ankle should reduce impact forces.

Fig 1. Inverted T lower limb modeling. Rearfoot strikes (RFS) significantly posterior to the ankle may convert impact transient (IT) force to rotational energy by the same mechanism that non-rearfoot-strike (NRFS) postures are thought to reduce impacts. Therefore, modeling the lower limb as an L may obscure the role of heel-strike on IT attenuation. Pink segments represent L-shaped modeling, teal line represents added inverted-T segment. Orange arrows represent the resulting ground reaction force.

The purpose of this study is to examine the relationship between ground contact location in relation to the foot and IT during the development of walking and to determine how landing position alters impact forces, as described in the model above. Furthermore, to examine whether the ground contact location (and not some other age-related biomechanical factor) plays a significant role in the generation of impact forces, child foot strikes are compared with experimentally generated adult NRFS foot strikes. We hypothesize that as ground contact location 72 moves anterior to the ankle (as in NRFS gaits), impact forces will decrease, but that immature walkers will have higher relative impact forces and rates of loading than mature walkers during similar foot strike patterns.

Materials and methods Twenty-five children, classified into mature (> 3.5 years) and immature (< 3.5 years) gait groups (8), participated in this study (Table 1). Groupings were based on Sutherland’s (9) review of gait maturation, which showed that walking mechanics in children stabilize between 3.5 and 4 years of age. The mature gait group included 13 children with a mean age of 5.8 ± 1.4 years

(ranging from 3.7 to 8.5 years) and a body mass of 22.3 ± 6.5 kg. The immature gait group consisted of 12 children with a mean age of 1.8 ± 0.7 years (ranging from 1.1 to 3.3 years) and a body mass of 11.4 ± 1.5 kg. Child subjects were recruited continuously between 08/2011 and

05/2013. We also analyzed data from 10 adults (Table 1, adult subject numbers start at 100 to differentiate from child subjects) aged 18 to 33 years with a mean body mass of 68.8 ± 14.4 kg who were recruited separately between 07/2012 and 12/2012 (17). All subjects (children and adult samples) were recruited from the local Tucson, Arizona community, via word of mouth and departmental fliers. Subjects performed all tasks barefoot. The University of Arizona's Institutional

Review Board (IRB) granted approval for the human experimental study described in this paper, which was titled “Locomotor Development in Humans.” All subjects or legal guardians (when subjects were minors) gave their written consent to participate, a procedure approved by the aforementioned IRB committee.

Table 1. Child and adult subject data.

Immature Gait Group – (< 3.5 years) Subject Sex Age (y) BM (kg) Total Steps NRFS 21 m 1.1 10 1 0 25 f 1.2 10.9 3 1 24 f 1.3 8.7 1 0 73

31 m 1.3 13.1 1 1 36 f 1.3 11 2 1 42 f 1.5 9.9 2 2 30 f 1.6 11.5 2 1 34 f 1.6 10.9 2 1 6 f 2.8 12.7 1 0 15 f 2.8 13.3 1 0 41 f 3.3 13.1 2 1 Mean 1.80 11.37 1.64 0.73 Mature Gait Group – (≥ 3.5 years) Subject Sex Age (y) BM (kg) Total Steps NRFS 12 m 3.7 16 1 0 38 f 4.2 15.3 1 1 32 f 4.8 15.3 2 1 17 f 5 16.6 1 0 27 m 5 24.2 4 0 35 m 5.3 22.1 3 1 16 m 5.5 19 1 0 7 m 5.7 16.5 1 0 9 m 6 38 3 2 10 m 6 25.3 2 1 26 f 7.3 27.5 4 0 5 m 8.5 29.1 3 0 20 m 8.5 24.7 2 0 Mean 5.81 22.28 2.15 0.46 Adult Gait Group – (≥ 18 years) Subject Sex Age (y) BM (kg) Total Steps ENRFS 113 f 18 66 7 3 112 f 19 68.5 5 2 103 f 21 60.7 6 2 105 m 21 66.2 6 4 106 f 21 43.3 7 4 107 m 22 63.7 8 4 111 m 22 96.1 2 1 114 m 29 61.9 6 3 102 m 31 91.4 3 1 104 f 33 70.1 4 2 Mean 23.70 68.79 5.40 2.60 SD 5.00 14.36 1.80 1.11 y = years, BM = body mass in kilograms, NRFS = number of non-rearfoot-strike steps of total steps, ENRFS = number of experimentally induced non-rearfoot-strike steps of total steps, SD = standard deviation.

We used a Vicon high-speed six-camera motion capture system (Vicon T160 cameras and

Vicon Nexus v1.6.1, Oxford, UK) and an AMTI force plate (OR6-6, Watertown, MA) to collect kinematic and kinetic walking data. Reflective markers were affixed to joint centers and foot segments including the greater trochanter, lateral knee, lateral ankle, and the distal head of the first metatarsal. We digitally collected and filtered kinematic data at 200 Hz using a fourth order zero- lag phase Butterworth low pass filter with a cut-off frequency of 6 Hz (30) and captured kinetic data at 4 kHz. To preserve the impact transient spike kinetic data were not filtered. The force plate was placed off-center along a 4-meter raised track to capture single foot-strikes in the youngest children who were unable to clear the entire distance of the force plate with a single step. Children walked barefoot at self-selected preferred speeds without instruction for as many trials as they would tolerate. Successful trials required complete, single foot contact with the force plate determined by examining the ground reaction force trace. All steps were examined visually and data where individuals reduced or increased step length to reach the plate were removed from the analysis. Trials with double limb support (more than one foot on the force plate) or where the subject missed the force plate entirely were discarded. Though this resulted in a significant portion trials being eliminated from the dataset, we collected enough trials to analyze our data with sufficient statistical power. Child trials were not discarded due to speed unless the subject used a running gait but walking speed was included in the statistical analysis.

Adults followed the same protocol but were asked to walk both naturally and to use an experimental NRFS gait (where initial ground contact occurs anterior to the ankle) for five trials

(17). For the NRFS gaits subjects were instructed using the following script: Next you are going to walk using an experimental gait, where you are to land on your forefoot, a little bit like tiptoeing.

It is important that your heel does not touch the ground first, but after your forefoot touches the 75 ground you can finish the step normally and your heel can contact the surface. Trials where the foot did not land completely on the force plate, or where subjects used altered gait to achieve single foot contact were not used for analysis in this study (see full subject dataset in Table S1).

Maximum IT magnitude was calculated from the force plate data. A custom MATLAB

(MATLAB version R2015b, 3.3.3, MathWorks, Natick, MA) program calculated the peak vertical ground reaction force or the average force between 1.61 and 3.72% of stance if no peak was present

(as during NRFS steps) for adults (Fig 2A), reflecting the 95% confidence interval of visible ITs during HS trials (15). We standardized IT as a percentage of stance following Lieberman et al.

(15) to assure a uniform definition, using the average IT magnitude during this time frame in trials where a visible impact spike was not present. Children’s foot contact times (Tc) were significantly shorter than adults’ (31), (assessed using a linear mixed effects model, p < 0.0001, -0.16 seconds

± 0.02, Fig 2B), therefore, an absolute time window (0.0107 to 0.0355 seconds) was used for the child data so that ITs in steps with very short contact times were not incorrectly calculated. This time window was calculated as the average foot contact time at 1.61 and 3.72% of stance in the adult sample. If the kinetic data did not include an IT peak, we used the average ground reaction force during this time frame (see: [16]). Finally, we calculated rate of loading (ROL) by dividing

IT force by the time at the impact peak. 76

Fig 2. Vertical ground reaction forces and ground contact time. A: Adult vertical ground reaction force (VGRF; scaled to body mass) as an example of an impact transient (IT; circled) calculation. B: IT was calculated as the first peak between 0.01 and 0.036 seconds due to differences in child and adult foot contact times (Tc; p < 0.0001). I = immature (<3.5 yo), M = mature (>3.5 yo), A = adult.

Center of pressure (COP, the point of application of the ground reaction force vector) position at initial ground contact varied within and between individuals. To quantify and scale foot strikes between the child and adult datasets, we used the relationship between the COP and foot position. Typically a foot strike index (a percent location of the COP in relation to total foot length) is used to specify ground contact location (15,32), but our children’s sample lacked phalangeal markers to accurately generate foot lengths. Therefore, the distance between the lateral malleolus and the distal head of the first metatarsal in the sagittal plane was utilized for both the children and adults to accommodate the simple child marker set (Fig 3). The foot-strike ratio (FSr) was calculated as COPd / FL where COPd is the distance in the sagittal plane from the lateral malleolus

(distal being negative and anterior being positive) to the COP at touchdown (m) and FL is the length from the lateral ankle to the distal head of the first metatarsal measured in the sagittal plane 77 at midstance. FSr accounts for changes in foot length related to age or size and allowed for the definition of a RFS as ground contact initiating posterior to the lateral malleolus, whereas a NRFS occurred anterior to the lateral malleolus. This method allows for an objective and quantitative description of foot strike location, which is important considering the foot can rotate in the frontal plane (inversion and eversion) making visual assessment of foot strike pattern in the sagittal plane difficult.

Fig 3. Foot strike ratio (FSr). The distance from the lateral malleolus to the head of the first metatarsal was used in place of foot length to quantify initial ground contact position. The teal COP arrow represents an example -0.10 FSr RFS. The orange COP arrow represents an example +0.60 FSr NRFS.

To allow for comparisons across a broad range of body sizes, impact forces were normalized to body mass. Additionally, Froude numbers (33) were used in place of walking velocity. The Froude number (Fr) is calculated as v2 / gL, where v is velocity (m / s), g is gravitational acceleration (9.81 m / s2), and L is a characteristic length, typically hip height. Fr is a dimensionless speed value that accounts for differences in lower limb length between subjects and age groups (33–35).

Data analyses were conducted using Linear Mixed Effects Models ([LMM], ‘lmerTest’ package version 2.0-33 in R version 3.3.3 (36)). LMMs are a robust statistical technique used to compare groups that include repeated measurements from individuals, including when the number of measures per individual differ within and between groups (37). FSr, Fr, age (years), and age categories (immature, mature, and adult) were treated as fixed effects. Absolute distance from the ankle was expected to influence ITs, so FSr was treated as the polynomial term FSr2 to account 78 for both RFS and NRFS initial ground contact (6,15). Subject number was added as a random effect to allow us to adjust the error terms to account for repeated measures from multiple steps from the same individual. Likelihood ratio tests were used to examine the effects of foot strike location on impact forces and to calculate associated p-values. IT (body weights) and ROL (body weights / second) were treated as the continuous dependent variables and compared against null models without FSr2.

Results Child ITs were higher than adult values during non-experimental walking gaits after controlling for speed (p < 0.0001, Fig 4A), supporting the hypothesis that children tend to experience higher relative impact forces. Furthermore, IT values decreased by 0.25 body weights

± 0.05 as walkers transitioned into older age categories suggesting immature walkers in this sample experience the highest relative IT forces. While young walkers displayed frequent NRFS steps, the immature walkers had FSr values significantly closer to the ankle joint (-0.12 FSr2 ± 0.06) than mature children or adults (p = 0.045). When ITs from adults walking with experimentally induced

NRFS gaits were included, there was no significant interaction between age category or age (as a continuous value) and FSr2 (age category p = 0.20, age p = 0.69), suggesting experimental and natural NRFS steps are similar. Comparing all steps, ground contact location, FSr2, was significantly associated with IT, and lower ITs were linked with increased distance of FSr, either anterior or posterior, from the ankle joint (p < 0.0001, Fig 4B, Table 2). Unsurprisingly, ROL were also lower as FSr2 increased in either posterior or anterior directions (p = 0.0006, Table 2).

Fig 4. Adult and child ITs by distance from the ankle. A: Children displayed higher average impact transients (IT) during non-experimental walking trials (p < 0.0001). B: Foot strike ratio (FSr) reduced IT forces in children and adults (p < 0.0001). Adult data above 0 FSr (dashed vertical line) represents experimental NRFS steps. Trend lines are fitted as a quadratic function including the squared term FSr. Dot sizes indicate walking speed.

Table 2. Linear mixed-effects models of IT and ROL.

Parameter Estimate Std. Error df t P value Impact Transient Intercept 0.688 0.057 37.56 12.015 <0.0001 FSr2 -0.275 0.044 74.29 -6.239 <0.0001 Age Category -0.297 0.043 31.53 -6.979 <0.0001 Fr 2.165 0.408 85.26 5.313 <0.0001 Rate of Loading Intercept 46.325 6.054 36.10 7.652 <0.0001 FSr2 -17.847 5.050 78.87 -3.534 0.0007 Age Category -27.982 4.464 29.68 -6.268 <0.0001 Fr 225.745 44.740 75.72 5.046 <0.0001 FSr = foot strike ratio, Fr = Froude.

Discussion Our results support both aspects of our hypothesis and suggest that children and adults can effectively reduce ITs and ROL through foot strike pattern alterations. Previous research has shown that NRFS steps in children are responsible for large IT values (6), however, our data 80 suggest that the absolute distance (whether posterior or anterior) from the ankle to foot contact location offer a more nuanced explanation of impact forces than foot strike pattern categories alone.

Our results provide support for Zeininger et al’s (6) conclusion that walking steps with the COP anterior to the ankle at landing can have high ITs, and many young walkers in our study displayed initial ground contact just anterior to the ankle resulting in flat foot strikes. Building on their results, we show that not only do children have high ITs when they land with flatter foot strikes, but that the distance of the COP from the ankle plays a key role in determining IT magnitude, whether they land with the COP anterior to, or posterior to the ankle. The lack of interaction between age and

FSr suggests that child gait patterns are following the same biomechanical constraints as adults.

Therefore, high IT NRFS steps may be best described as the product of gait maturation (8) or neurobiological development (12), where young children do not have the muscular control to land with the COP significantly posterior or anterior to the ankle joint.

Our results may be explained, in part, by modeling the foot and shank as an inverted T rather than L-shaped double pendulum as previously described (Fig. 1). We suggest this model better accounts for impact force attenuation during both NRFS and RFS walking by adding a segment posterior to the ankle that impact forces act upon during RFS gaits. Thus, although the average child IT values were significantly higher than adult ITs, children who were competent

RFS walkers, or who used NRFS steps with initial center of pressure contact significantly anterior to the ankle, displayed reduced relative ITs compared to walkers with flat foot strike orientations across both age categories. The significant reduction in impact force associated with age suggests that walkers gain the ability to land with the COP further posterior to the ankle over the course of development (38), but steps with the COP significantly anterior to the ankle at landing can still reduce IT and ROL in young walkers. 81

In addition to managing forces, NRFS walking and the developmental timing of RFS gaits may explain variation in bone ontogeny across populations. Many studies have suggested that forces experienced during ontogeny shape the growth of cortical and trabecular bone (23–29), although not without debate. Recent work has detailed variation in the growth of bone mechanical properties across populations in the past, including those that practiced different subsistence strategies (39–41). Interestingly, the age at which children start to use RFS gaits may also vary geographically, possibly across subsistence strategies. For example, children in Kenya develop

RFS gaits around 30 months (42) whereas American-born children start heel-striking between 18 and 20 months (43,44), possibly due to differences in shoe usage. These differences in developmental timing could lead to later high ITs in some groups, with associated variance in the timing of bone mechanical development. For example, researchers have shown that children in the

US attained bone mechanical properties more similar to adults by age 3, whereas matched samples from Neolithic and Byzantine agricultural populations attained more adult-like properties later in development (40). Changes of this nature may reflect the later development of adult-like gaits in these populations.

Our results support previous work showing that IT values can be high in children using

NRFS gaits (6), however we build on this work to show that IT values vary continuously with the distance of the COP relative to the ankle. Children can, and do, sometimes land with the COP far anterior to the ankle, leading to lower ITs. However, at young ages, the higher ITs in children are driven mainly by landing with the COP under then ankle. Children display significantly higher average relative IT values than adults, however, these impact forces are significantly smaller than those seen in typical running gaits. Both children and adults appear able to mitigate relatively high impact forces by altering foot strike and can do so throughout gait development. However, the 82 percentage of steps children use with COPs significantly anterior to the ankle during daily walking are unknowns. Later in development, children adapt to a heel-striking gait, minimizing impact forces as they near an adult-like gait. How these changes in impact forces affect development remains unknown. Future research should seek to understand the factors that lead to the initiation of RFS gaits in children, measure daily foot-strike usage patterns, and quantify the effects of the ontogeny of foot strike patterns on adult skeletal morphology. We suggest that studies of the ontogeny of foot strike patterns can help us better understand the loading environments experienced by children during key periods of bone growth and development.

Acknowledgements We would like to thank all the participants and parents or guardians for their time and effort.

This study was funded by National Science Foundation Behavioral and Cognitive Science

(1028799, DAR; 1028904, TMR; and 1028793, JHG).

References 1. Raichlen DA, Gordon AD, Foster AD, Webber JT, Sukhdeo SM, Scott RS, et al. An ontogenetic framework linking locomotion and trabecular bone architecture with applications for reconstructing hominin life history. Journal of human evolution. 2015;81:1–12.

2. Ruff C. Growth in bone strength, body size, and muscle size in a juvenile longitudinal sample. Bone. 2003 Sep;33(3):317–29.

3. Ryan TM, Krovitz GE. Trabecular bone ontogeny in the human proximal femur. Journal of Human Evolution. 2006 Dec;51(6):591–602.

4. Gosman JH, Ketcham RA. Patterns in ontogeny of human trabecular bone from SunWatch Village in the Prehistoric Ohio Valley: General features of microarchitectural change. American Journal of Physical Anthropology. 2008;138(3):318–32.

5. Sheridan MD. The developmental progress of infants and young children. 3rd ed. London, H.M.S.O.,; 1975.

6. Zeininger A, Schmitt D, Jensen JL, Shapiro LJ. Ontogenetic changes in foot strike pattern and calcaneal loading during walking in young children. Gait & Posture. 2018 Jan 1;59(Supplement C):18–22.

7. Hennig EM, Staats A, Rosenbaum D. Plantar Pressure Distribution Patterns of Young School Children in Comparison to Adults. Foot Ankle Int. 1994 Jan 1;15(1):35–40.

8. Sutherland D. Review paper: The development of mature gait. Gait & Posture. 1997;6(2):163–170.

9. Sutherland DH, Olshen R, Cooper L, Woo S. The development of mature gait. J Bone Joint Surg-Am Vol. 1980;62(3):336–53.

10. Cunningham CB, Schilling N, Anders C, Carrier DR. The influence of foot posture on the cost of transport in humans. Journal of Experimental Biology. 2010 Mar 1;213(5):790–7.

11. Hallemans A, D’Août K, De Clercq D, Aerts P. Pressure distribution patterns under the feet of new walkers: the first two months of independent walking. Foot Ankle Int. 2003 May;24(5):444–53.

12. Berger W, Altenmueller E, Dietz V. Normal and impaired development of children’s gait. Hum Neurobiol. 1983 Dec;3(3):163–70.

13. Daoud AI, Geissler GJ, Wang F, Saretsky J, Daoud YA, Lieberman DE. Foot strike and injury rates in endurance runners: a retrospective study. Med Sci Sports Exerc. 2012 Jul;44(7):1325–34.

14. Lieberman DE. What We Can Learn About Running from Barefoot Running: An Evolutionary Medical Perspective. Exerc Sport Sci Rev. 2012 Apr;40(2):63–72. 84

15. Lieberman DE, Venkadesan M, Werbel WA, Daoud AI, D’Andrea S, Davis IS, et al. Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature. 2010 Jan 28;463(7280):531–5.

16. Wakeling JM, Liphardt A-M, Nigg BM. Muscle activity reduces soft-tissue resonance at heel-strike during walking. Journal of Biomechanics. 2003 Dec 1;36(12):1761–9.

17. Webber JT, Raichlen DA. The role of plantigrady and heel-strike in the mechanics and energetics of human walking with implications for the evolution of the human foot. Journal of Experimental Biology. 2016 Dec 1;219(23):3729–37.

18. Gillespie KA, Dickey JP. Determination of the effectiveness of materials in attenuating high frequency shock during gait using filterbank analysis. Clinical Biomechanics. 2003;18(1):50–59.

19. Usherwood JR, Channon AJ, Myatt JP, Rankin JW, Hubel TY. The Human Foot and Heel– Sole–Toe Walking Strategy: A Mechanism Enabling an Inverted Pendular Gait with Low Isometric Muscle Force? J R Soc Interface [Internet]. 2012 May 9 [cited 2012 May 10]; Available from: http://rsif.royalsocietypublishing.org/content/early/2012/04/26/rsif.2012.0179

20. Bernhardt DB. Prenatal and Postnatal Growth and Development of the Foot and Ankle. Phys Ther. 1988 Dec 1;68(12):1831–9.

21. Kalkwarf HJ, Laor T, Bean JA. Fracture risk in children with a forearm injury is associated with volumetric bone density and cortical area (by peripheral QCT) and areal bone density (by DXA). Osteoporosis Int. 2011 Feb;22(2):607–16.

22. Altman AR, Davis IS. Barefoot Running: Biomechanics and Implications for Running Injuries. Curr Sport Med Rep. 2012 Oct;11(5):244–50.

23. Barak MM, Lieberman DE, Hublin J-J. A Wolff in sheep’s clothing: Trabecular bone adaptation in response to changes in joint loading orientation. Bone. 2011 Dec;49(6):1141– 51.

24. Carlson KJ, Judex S. Increased non-linear locomotion alters diaphyseal bone shape. Journal of Experimental Biology. 2007 Sep 1;210(17):3117–25.

25. Pontzer H, Lieberman DE, Momin E, Devlin MJ, Polk JD, Hallgrímsson B, et al. Trabecular bone in the bird knee responds with high sensitivity to changes in load orientation. Journal of Experimental Biology. 2006 Jan 1;209(1):57–65.

26. Ruff CB, Hayes WC. Subperiosteal expansion and cortical remodeling of the human femur and tibia with aging. Science. 1982;217(4563):945–8.

27. Ruff C, Holt B, Trinkaus E. Who’s afraid of the big bad Wolff?: “Wolff’s law” and bone functional adaptation. Am J Phys Anthropol. 2006 Apr 1;129(4):484–98. 85

28. Wolff J. Das gesetz der transformation der knochen. DMW-Deutsche Medizinische Wochenschrift. 1892;19(47):1222–4.

29. Cowgill LW, Warrener A, Pontzer H, Ocobock C. Waddling and toddling: The biomechanical effects of an immature gait. American Journal of Physical Anthropology. 2010 Sep 1;143(1):52–61.

30. Winter DA. Biomechanics and Motor Control of Human Movement. 4th ed. Hoboken, NJ: Wiley; 2009. 384 p.

31. Beck RJ, Andriacchi TP, Kuo KN, Fermier RW, Galante JO. Changes in the gait patterns of growing children. J Bone Joint Surg Am. 1981 Dec;63(9):1452–7.

32. Altman AR, Davis IS. A kinematic method for footstrike pattern detection in barefoot and shod runners. Gait & Posture. 2012 Feb;35(2):298–300.

33. Alexander RM. Optimization and Gaits in the Locomotion of Vertebrates. Physiol Rev. 1989 Oct 1;69(4):1199–227.

34. Pontzer H. Predicting the energy cost of terrestrial locomotion: a test of the LiMb model in humans and quadrupeds. J Exp Biol. 2007 Feb 1;210(3):484–94.

35. Saibene F, Minetti AE. Biomechanical and physiological aspects of legged locomotion in humans. Eur J Appl Physiol. 2003 Jan;88(4–5):297–316.

36. Team RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2016. 2017.

37. Fox J. Applied regression analysis and generalized linear models. Sage Publications; 2015.

38. Straus WL. Growth of the human foot and its evolutionary significance. Contributions to Embryology. 1927 Aug;19(101):95-U4.

39. Cowgill LW. The Ontogeny of Holocene and Late Pleistocene Human Postcranial Strength. Am J Phys Anthropol. 2010 Jan;141(1):16–37.

40. Cowgill LW, Hager LD. Variation in the development of postcranial robusticity: An example from Catalhoyuk, Turkey. Int J Osteoarchaeol. 2007 Jun;17(3):235–52.

41. Osipov B, Temple D, Cowgill L, Harrington L, Bazaliiskii VI, Weber AW. Evidence for genetic and behavioral adaptations in the ontogeny of prehistoric hunter-gatherer limb robusticity. Quaternary International [Internet]. 2016 Feb [cited 2016 May 13]; Available from: http://www.sciencedirect.com/science/article/pii/S104061821501472X

42. Hennessy MJ, Dixon SD, Sheldon R. Simon. The development of gait: A study in African children ages one to five. Child Development. 1984 Jun 1;55(3):844–53. 86

43. Burnett CN, Johnson EW. Development of gait in childhood: Part II. Developmental Medicine & Child Neurology. 1971;13(2):207–215.

44. Sutherland D, Olshen R, Biden E. The Development of Mature Walking. London, England: Mac Keith Press; 1991. 277 p.

Supporting information S1 Table. Subject metrics and data for analysis. Full subject dataset. S# Sx Ag KG FSr V Fr Tc VGRF IT ROL Ad AC 5 1 8.5 29.1 -0.1609233 0.81921 0.09550456 0.663 1.1521855 0.4245611 28.304074 0 1 5 1 8.5 29.1 -0.192767249 0.80991 0.09334814 0.639 1.0738014 0.52730314 37.66451 0 1 5 1 8.5 29.1 -0.222219868 0.88505 0.11147196 0.657 1.2052353 0.62876344 48.366419 0 1 6 0 2.8 12.7 0.115488255 1.08348 0.21743002 0.406 1.4149177 0.87773726 73.144772 0 0 7 1 5.7 16.5 -0.160064161 0.79802 0.11796157 0.441 1.4238028 0.84559304 65.045619 0 1 9 1 6 38 -0.297476589 0.49793 0.0362576 0.792 1.0236771 0.36923191 9.716629 0 1 9 1 6 38 0.795153538 1.02957 0.15501391 0.616 1.3656596 0.19221138 24.026422 0 1 9 1 6 38 0.744634126 0.90931 0.12091436 0.655 1.129504 0.10922676 9.929706 0 1 10 1 6 25.3 -0.16431004 0.65745 0.07883539 0.782 1.1201278 0.9308722 116.359026 0 1 10 1 6 25.3 0.236478909 0.90491 0.14935127 0.607 1.4224081 0.39288651 32.740542 0 1 12 1 3.7 16 -0.23469791 0.8284 0.16289374 0.556 1.0448842 0.45635873 16.902175 0 1 15 0 2.8 13.3 -0.142292809 0.65363 0.10094076 0.453 1.2842652 0.89349605 89.349605 0 0 16 1 5.5 19 -0.131228614 0.74169 0.10542969 0.689 1.1948793 0.76378258 76.378258 0 1 17 0 5 16.6 -0.246038485 1.19358 0.2384059 0.336 1.3695728 1.23561466 123.561466 0 1 20 1 8.5 24.7 -0.34109571 0.79203 0.09631154 0.645 1.1645626 0.43161825 11.358375 0 1 20 1 8.5 24.7 -0.349218071 0.99233 0.15118495 0.584 1.1474609 0.28252822 7.434953 0 1 21 1 1.1 10 -0.284313237 0.15769 0.00798457 0.768 1.0712996 1.02125162 26.875043 0 0 24 0 1.3 8.7 -0.190612643 0.36917 0.04466248 0.443 1.1930413 0.95857294 73.73638 0 0 25 0 1.2 10.9 0.342933411 0.11486 0.00443268 0.712 0.9075513 0.43541593 22.916628 0 0 25 0 1.2 10.9 0.964108471 0.39428 0.0522311 0.656 0.9179064 0.15551877 38.879694 0 0 25 0 1.2 10.9 -0.01363886 0.26219 0.02309694 0.425 1.0887688 0.65548293 36.415718 0 0 26 0 7.3 27.5 -0.422775155 0.52943 0.04275318 1.07975 1.0383033 0.43857654 31.896476 0 1 26 0 7.3 27.5 -0.322808361 0.5835 0.05193115 0.96625 0.9969659 0.37628969 24.276754 0 1 26 0 7.3 27.5 -0.325093602 0.77041 0.09053064 0.8075 1.1394958 0.48704991 38.963993 0 1 26 0 7.3 27.5 -0.407796226 0.67524 0.06954556 0.7955 1.2226152 0.61332091 48.103601 0 1 27 1 5 24.2 -0.367158629 0.57013 0.05758974 0.644 0.9753222 0.4853481 13.481892 0 1 27 1 5 24.2 -0.543650516 0.61976 0.06805123 0.61 0.9552522 0.67636841 21.818336 0 1 27 1 5 24.2 -0.304360049 0.71635 0.09091754 0.603 1.0761539 0.77346568 29.74868 0 1 27 1 5 24.2 -0.094366909 0.77518 0.10646224 0.46 1.3298664 1.20250984 63.289992 0 1 30 0 1.6 11.5 0.033481297 0.38478 0.04473903 0.52075 1.2421402 1.24214023 134.28543 0 0 30 0 1.6 11.5 -0.150987938 0.36658 0.0406067 0.6645 1.0144393 0.68240256 25.274169 0 0 31 1 1.3 13.1 0.085040818 0.42638 0.05702216 0.49575 1.3897898 1.38978975 80.567522 0 0 32 0 4.8 15.3 -0.107699317 0.64226 0.08509507 0.6115 1.059309 0.58068469 15.90917 0 1 32 0 4.8 15.3 0.128206166 0.81737 0.13782074 0.5745 1.0690809 0.65125597 33.831479 0 1 34 0 1.6 10.9 -0.031321631 0.43332 0.05479042 0.44 1.1244296 0.80693071 67.244226 0 0 34 0 1.6 10.9 0.198875083 0.33078 0.03192653 0.53575 1.102013 0.91122879 65.087771 0 0 35 1 5.3 22.1 0.131823559 0.68966 0.08972797 0.5665 1.0732282 0.72854716 32.024051 0 1 35 1 5.3 22.1 -0.09269829 1.09291 0.22533122 0.4305 1.9522034 1.42815089 136.014371 0 1 35 1 5.3 22.1 -0.282988719 0.99844 0.18806047 0.51475 1.2788566 0.81535526 67.946272 0 1 36 0 1.3 11 0.135145019 0.26302 0.02226851 0.51525 1.0309795 0.64576041 17.692066 0 0 88

36 0 1.3 11 -0.093836746 0.32329 0.03364281 0.601 1.0115006 0.6485505 43.969526 0 0 38 0 4.2 15.3 0.436160678 0.5322 0.05997935 0.639 1.03519 0.34789974 27.286254 0 1 41 0 3.3 13.1 -0.009149737 0.61126 0.08795485 0.462 1.1961101 0.95074832 69.145333 0 0 41 0 3.3 13.1 0.049528905 0.60892 0.08728307 0.3455 0.9667497 0.85109927 77.372661 0 0 42 0 1.5 9.9 -0.125188306 0.21464 0.01409448 0.52175 1.1267999 0.57468896 54.732282 0 0 42 0 1.5 9.9 0.042500998 0.12796 0.00500979 0.625 1.0173228 0.52997528 35.930527 0 0 102 1 31 91.4 -0.188902046 1.43848 0.21209111 0.6745 1.037131 0.65946353 45.480244 1 2 102 1 31 91.4 -0.130117033 1.57118 0.25302683 0.687 1.1463542 0.76383956 61.107165 1 2 102 1 31 91.4 0.53790922 1.41162 0.20424461 0.6595 1.1856048 0.22256185 17.455831 1 2 103 0 21 60.7 -0.157032725 0.96447 0.10760161 0.65275 1.1824236 0.38104456 18.144979 1 2 103 0 21 60.7 -0.191213155 1.06416 0.13099334 0.62675 1.1652069 0.35918753 16.14326 1 2 103 0 21 60.7 -0.193407035 1.01789 0.11985132 0.63625 1.1902154 0.36881986 18.213326 1 2 103 0 21 60.7 -0.191309279 1.05208 0.12803758 0.6115 1.1810734 0.37707328 18.393819 1 2 103 0 21 60.7 -0.247194438 1.04266 0.12575509 0.62775 1.1497202 0.42668196 22.756371 1 2 103 0 21 60.7 0.575993789 0.9789 0.11084359 0.683 1.1704422 0.12622766 3.458292 1 2 103 0 21 60.7 0.703232451 0.96076 0.10677375 0.689 1.1929564 0.20695921 5.670115 1 2 104 0 33 70.1 -0.236910569 0.92679 0.09984861 0.6752778 1.018935 0.3446015 20.00912 1 2 104 0 33 70.1 -0.273414099 0.86586 0.08715093 0.6938889 1.0478501 0.58918517 43.287074 1 2 104 0 33 70.1 0.635046138 0.48522 0.0273682 1.2394444 1.0268259 0.03042298 3.776646 1 2 104 0 33 70.1 0.674780584 0.68101 0.0539125 0.8508333 1.0717389 0.13152627 3.58708 1 2 105 1 21 66.2 0.136011972 1.29393 0.2048933 0.5941667 1.1894556 0.27771601 7.574073 1 2 105 1 21 66.2 0.041500367 1.27601 0.19925599 0.5961111 1.1157242 0.27469873 7.491784 1 2 105 1 21 66.2 0.669629076 1.14646 0.16085009 0.5694444 1.1823138 0.34878968 9.512446 1 2 105 1 21 66.2 0.194807055 1.36638 0.22848061 0.555 1.1773324 0.373153 10.1769 1 2 105 1 21 66.2 -0.212978177 1.768 0.38253341 0.4461111 1.4290057 1.11560798 64.777238 1 2 106 0 21 43.3 -0.192567764 1.11614 0.15224446 0.6019444 1.2466473 0.73291623 52.769968 1 2 106 0 21 43.3 -0.227885165 1.13827 0.15834158 0.5822222 1.2610603 0.5669477 36.446638 1 2 106 0 21 43.3 0.593392968 1.0259 0.12862169 0.7261111 1.0897046 0.32831237 8.953974 1 2 106 0 21 43.3 0.74992017 1.17261 0.16804006 0.6472222 1.1476363 0.45826126 12.498034 1 2 106 0 21 43.3 -0.222371863 1.10259 0.14856921 0.6525 1.2801563 0.38990442 10.633757 1 2 106 0 21 43.3 0.524251203 1.17837 0.16969425 0.635 1.3442403 0.39665845 10.817958 1 2 106 0 21 43.3 0.340314764 1.13176 0.15653416 0.5986111 1.2440067 0.3781361 10.312803 1 2 107 1 22 63.7 -0.179354479 0.98247 0.11437322 0.6813889 1.0783158 0.45006826 31.769524 1 2 107 1 22 63.7 -0.042788568 1.26513 0.18964912 0.7030556 1.0466143 0.60949346 44.779111 1 2 107 1 22 63.7 -0.175497819 0.90607 0.09727525 0.7305556 1.1154672 0.36810441 19.205448 1 2 107 1 22 63.7 -0.237586144 0.85527 0.08667479 0.7672222 1.0933451 0.43045331 27.671999 1 2 107 1 22 63.7 0.642440082 1.00056 0.1186242 0.6755556 1.2688838 0.30016985 8.186451 1 2 107 1 22 63.7 0.673079175 0.98826 0.1157243 0.6791667 1.2198692 0.38168263 10.409526 1 2 107 1 22 63.7 0.633347769 1.0348 0.12687956 0.6463889 1.171393 0.35063679 9.562821 1 2 107 1 22 63.7 0.69800516 0.99967 0.11841118 0.6530556 1.2085961 0.31300847 8.536595 1 2 111 1 22 96.1 -0.160606253 0.64114 0.04493517 0.9522222 1.0149054 0.20090178 8.610076 1 2 111 1 22 96.1 0.592713987 0.8921 0.08699902 0.7761111 1.096711 0.11597739 3.16302 1 2 112 0 19 68.5 -0.53793845 1.14284 0.14573138 0.75625 1.1442425 0.28816047 18.590998 1 2 89

112 0 19 68.5 -0.608814176 1.04866 0.12270151 0.73925 1.1473712 0.30857144 16.240602 1 2 112 0 19 68.5 0.766193275 0.72889 0.05927993 1.0035 1.0098001 0.082202 5.390295 1 2 112 0 19 68.5 0.730266733 0.77457 0.06694193 0.929 1.020747 0.06970682 5.690353 1 2 112 0 19 68.5 0.47137026 0.98257 0.10772338 0.8905 1.1218008 0.15838966 12.929768 1 2 113 0 18 66 -0.205926684 1.05288 0.11509785 0.7565 1.1607239 0.77040458 52.230819 1 2 113 0 18 66 -0.27214985 1.19624 0.14857503 0.70125 1.1999844 0.6726626 42.708736 1 2 113 0 18 66 -0.233712766 1.24966 0.16214033 0.6675 1.1353077 0.72825054 44.815418 1 2 113 0 18 66 -0.227229673 1.26355 0.16576461 0.63625 1.1411669 0.72723771 43.417177 1 2 113 0 18 66 0.981370676 1.06797 0.1184196 0.72 1.1272014 0.12924643 9.942033 1 2 113 0 18 66 0.93595058 1.11461 0.12898801 0.69925 1.1192446 0.12016539 10.013783 1 2 113 0 18 66 0.966109089 1.08806 0.12291593 0.7295 1.131649 0.12267076 10.222563 1 2 114 1 29 61.9 -0.271236092 1.41848 0.23221894 0.653 1.2638656 0.6432739 42.181895 1 2 114 1 29 61.9 -0.311453655 1.47448 0.25091676 0.6305 1.3194336 0.80025947 64.020758 1 2 114 1 29 61.9 0.444849205 1.39758 0.22542486 0.62125 1.2005426 0.4066864 11.142093 1 2 114 1 29 61.9 0.203658721 1.35115 0.21069708 0.60075 1.2069099 0.39871557 10.923714 1 2 114 1 29 61.9 0.555181154 1.34464 0.20867037 0.608 1.241052 0.34373869 9.417498 1 2 114 1 29 61.9 -0.015289751 1.33768 0.20651571 0.60125 1.2678747 0.3214266 8.806208 1 2

S# = Subject Number, Sx = Sex (1 = male, 0 = female), Ag = Age (years), Kg = Weight

(kilograms), FSr = footstrike ratio, V = Velocity (m/s), Fr = Froude, Tc = Foot Contact Time

(seconds), VGRF = Maximal Vertical Ground Reaction Force, IT = Impact Transient (% bodyweight), ROL = Rate of Loading (IT / s), Ad = Adult (1 = yes, 0 = no), AC = Age Category

(0 = immature, 1 = mature, 2 = adult)

APPENDIX B: MANUSCRIPT 2

Head kinematics of load carrying while walking and the evolution of the semicircular canal in early members of the genus Homo

James T. Webber1,* and David A. Raichlen2

1 School of Anthropology, University of Arizona. Tucson, AZ 85721, USA

2 Human and Evolutionary Biology Section, Department of Biological Science, University of Southern California, Los Angeles, CA 90089, USA

* [email protected]

Abstract The semicircular canals (SCC) are an organ system in the inner ear responsible for relaying head acceleration information to the eyes in order to coordinate a visual reflex. Changes in the hominin semicircular canal system have been used to interpret locomotor behaviors in the fossil record. Specifically, enlarged canal diameters suggest increased sensitivity of the vestibulo-ocular reflex during significant head perturbations where accelerations are high. Previous work suggests enlarged SCCs in humans and Homo erectus may be linked with high-speed locomotor activities, specifically running, which generate high head pitch accelerations. However, there are alternative locomotor behaviors that can increase head pitch rates in humans, potentially including high-speed and loaded walking. Here we test the hypothesis that load carrying while walking at high speeds will produce maximal head pitch rates equal to those seen during running. Subjects carried 9 or 18 kilograms in their arms in front of their body across a range of speeds while wearing a 3d accelerometer on their forehead. Head pitch acceleration in loaded trials were compared against unloaded walking and two unloaded running trials. Load carrying significantly increased head pitch rates (p < 0.0001) and overlapped with running between 1.33 and 1.66 meters per second. When walking speeds were highest (2.00 m/s), load carrying generated significantly higher head pitch rates than running

(p < 0.01). Thus, changes in hominin semicircular canal diameter size may signify selective pressures on non-agile behaviors rather than endurance running.

Introduction Analyses of hominin fossil remains suggest many derived skeletal traits useful for high-speed locomotion have undergone a mosaic of transformations from the time of the first upright walkers to our present configuration (Berge, 1994; Cunningham et al., 2010; Latimer and Lovejoy, 1989). These changes may reflect the fact that, while bipedalism is a defining characteristic of the hominin lineage (Darwin, 1871), extant humans have many bipedal locomotor modes, including walking, running, load-carrying, tip-toeing, and jumping, which cause a range of biomechanical challenges (Birrell et al., 2007; Bramble and Lieberman,

2004; McKay et al., 2005; Webber and Raichlen, 2013; Wright and Weyand, 2001). Ranging and locomotor patterns in early members of the genus Homo are characterized by a transition from short daily movement ranges, similar to those of great apes, to hunting and gathering lifestyles which required an increase in daily travel and physical activity (Raichlen et al., 2019). It is thought that these changes began around two million years ago following the origins of the genus Homo (Aiello and Wells, 2002; Kuhn et al., 2016; Lieberman et al., 2009; Malina and Little, 2008; Pontzer et al., 2015, 2012; Raichlen et al., 2011). While several morphological aspects of the human lower limb are likely linked to energetically efficient walking gaits that were apparent early in our evolution (Cunningham et al., 2010; Webber and Raichlen, 2013), a suite of later derived traits in early members of the genus Homo have been suggested to specifically aid higher- speed gaits, with many skeletal adaptations linked to the management of higher loads experienced during running (Bramble and Lieberman, 2004; Carrier, 1984).

To explain the origins of these traits and their links to high-speed gaits, some researchers have proposed that persistence hunting, which requires higher speed pursuit of prey leading to hyperthermia, may have acted as an adaptive pressure for the acquisition of endurance running (ER) capabilities (Bramble and Lieberman, 2004; Liebenberg, 2008, 2006; Lieberman et al., 2009). However, the persistence hunting hypothesis is contentious (Liebenberg, 2008, 2006), and it is possible walking speeds may induce hyperthermic states in some mammals (Taylor and Lyman, 1972). Given debates over the role of pursuit hunting in hominin evolution, we remain unsure whether traits found within the genus Homo are best linked with ER. Here, we examine other locomotor behaviors that induce high loads, including high-speed walking 93

and carrying (Birrell et al., 2007; Park et al., 2014; Webber and Raichlen, 2013), that may have acted as selection pressures for skeletal traits during the evolution of the genus Homo.

Semi-circular canals and locomotor behavior

While several traits across the skeleton have been implicated in the shift to higher intensity movement in Homo erectus, here, we focus on morphological aspects of the skull that have been linked to high speed locomotion (Bramble and Lieberman, 2004; Cox and Jeffery, 2010; Lieberman, 2011; Spoor and Zonneveld, 1998). Specifically, researchers have linked changes in the semi-circular canal (SCC) system to shifts in hominin locomotor behaviors, and some suggest changes in canal diameter size across hominin evolution support a shift toward high-speed gaits (Cox and Jeffery, 2010; Malinzak et al., 2012;

Spoor et al., 2007). The SCC system, located in the inner ear, consists of a group of three torus shaped boney ducts including the anterior, posterior, and lateral canals. Canals are positioned at approximately right angles to each other, that individually sense angular accelerations (the change in rotational velocity per unit time) in the sagittal, coronal, and transverse planes (Malinzak et al., 2012). The primary function of the SCCs are the stabilization of gaze during locomotion by integrating visual stimuli with body movements (Frost et al., 1994; Wilson, 2013). Gaze stabilization is produced via the vestibulo-ocular

(VOC) reflex, which is a combination of cranial and eye muscle activity in response to head rotation. Left unchecked, rapid head movements can inundate the VOC reflex, resulting in a loss of vision (Atkin and

Bender, 1968). In mammals, SCC diameters generally follow negative allometric scaling with body-size

(Jones and Spells, 1963), but previous research has suggested that the canals vary with respect to differences in locomotor speed, agility, or behavior when holding body-size constant (Cox and Jeffery, 2010; Malinzak et al., 2012; Spoor et al., 2007; Spoor and Zonneveld, 1998). For example, researchers found small canal diameters relative to body size in slow-moving sloths and whales (Gray, 1908; Spoor et al., 2002), whereas highly agile birds had relatively large canal diameters adjusted for body size (Hadžiselimović and Savković,

1964). In nonhuman primate studies, species that used highly agile locomotor modes, especially at high speeds, have larger canal diameters than species that use less agile locomotor modes (King and Taub, 1986;

Spoor, 2003; Spoor and Zonneveld, 1998). These results, combined with biophysical models (Spoor, 2003), 94

suggest that an increase in diameter size allows for greater sensitivity to head accelerations, and therefore better gaze stabilization. However, the primate studies specifically linked canal diameters to locomotor speed and not actual head acceleration rates. In hominins, compared with other apes, relatively large anterior canal diameters first appear in H. erectus (Bramble and Lieberman, 2004; Lieberman, 2011; Spoor, 2003).

The human anterior SCC is oriented in the sagittal plane and is related to head pitch (the yes-nodding motion of the head), suggesting the hominin VOC reflex and canal system may be adapted to locomotor activities that produce high pitch rates (Bramble and Lieberman, 2004; Cox and Jeffery, 2010; Lieberman, 2011;

Spoor, 2003).

Human head pitch rates during locomotion are related to many biomechanical factors including the magnitude and rate of loading of impact forces, a ground reaction force peak occurring after foot touchdown known as the impact transient (Lieberman et al., 2010; Webber and Raichlen, 2013), lower limb compliance

(Gatesy and Biewener, 1991), vertical and angular displacement of the torso (Bramble and Lieberman,

2004; Hamill et al., 1995; Hirasaki et al., 1999; Mulavara and Bloomberg, 2002), and absolute body mass

(Spoor, 2003). Walking at energetically optimal speeds generates very low impact forces, which when ultimately transmitted to the head, lead to low pitch accelerations (Lieberman, 2011). Yet, impact forces do increase linearly as walking speed increases (Webber and Raichlen, 2013). Additionally, walking causes significant vertical but limited angular displacement of the torso (Hirasaki et al., 1999), and uses a significantly stiffer stance limb than running (Lee and Farley, 1998). During running in experimental settings, impact forces are much higher (Lieberman et al., 2010), and in conjunction with a pitching trunk

(Lieberman et al., 2006), can cause rapid head pitch rates (Lieberman, 2011), even though lower limb compliance may be higher (Alexander, 1991). Studies of habitually barefoot populations, however, have shown markedly reduced impact forces due to differences in lower limb biomechanics (Altman and Davis,

2012; Divert et al., 2005; Lieberman et al., 2010). Thus, since barefoot running, which may better resemble running in our hominin ancestors (Lieberman et al., 2010), generates lower impact forces, there may be other locomotor modes that can produce high head accelerations without requiring high-speed locomotion. 95

For example, studies examining load carrying have also reported an increase in impact forces during walking due to changes in participant center of mass or restriction in arm swing (Birrell et al., 2007;

Castro et al., 2013). While load carrying likely reduces trunk pitch (Fries and Hellebrandt, 1943), an immobile trunk may actually increase head perturbations by more readily transmitting impact forces

(Hamill et al., 1995). Load carrying effectively increases participant body mass which should, all else being equal, increase impact forces. Therefore, habitual load carrying (reflecting evolutionary activities such as infant and resource transport), especially at higher walking speeds, could have played a role in the development of adaptations to high impact forces, specifically those related to maximal head pitch such as the semicircular canal system.

Here we test the hypothesis that combinations of high-speeds and load carrying during walking will increase head pitch accelerations to rates comparable with running. Additionally, we explore the relationship between head velocities and accelerations during walking and running to test the hypothesis that high-speed locomotor activities in humans lead specifically to high accelerations rather than just high velocities. If supported, these hypotheses would lay the groundwork for understanding the evolution of hominin SCC system morphology and its relationship to transitional locomotor behaviors between early hominin bipedal walking and endurance running.

Methods Twenty-one subjects recruited from the University of Arizona community participated in this study.

The sample included eleven females aged 31.1 ± 7.0 years, with a mean body mass of 61.5 ± 7.9 kg, and an average hip height of 87.8 ± 3.6 cm, and ten men aged 31.0 ± 8.4 years, with a mean bodyweight of 74.9

± 14.5 kg, and an average hip height of 96.1 ± 5.2 cm. Subjects performed all trials barefoot, and informed consent (approved for this study by the University of Arizona Institutional Review Board) was collected from each subject prior to involvement in the study. Subjects were free of lower limb injuries at the time of the study and were allowed to skip any trials they felt were beyond their capabilities (see: Table 1). A

Delsys Trigno Wireless Biofeedback System (SP-W06 sensors and SP-W02 base station, Natick, MA) was used to collect trunk and head pitch and lower limb accelerations. Wireless EMG / accelerometer / rate gyro 96

sensors were placed on the right tibialis anterior, right rectus femoris, just lateral to L1 & C7, and on the center of the forehead attached to a headband (range 40 m, resolution 16-bit, sampling frequency 148 Hz, noise < 3.5 mg or 0.05° / sec, see: Fig. 1). Data from two subjects were not used in this study due to sensor errors. 97

Table 1. (Subject details)

1.00 1.33 1.66 2.00 1.00 1.33 1.66 2.00 1.00 1.33 1.66 2.00 2.00 2.66 Subject Age BM HH Sex Walk Walk Walk Walk 9kg 9kg 9kg 9kg 18kg 18kg 18kg 18kg Jog Run 1 28 51.2 0.815 0 2 30 64.8 0.895 0 3 24 57 0.845 0 4 36 64.8 0.870 1 5* 25 57.8 0.825 0 6 48 56.7 0.91 0 7 25 61.5 0.985 1 8 34 67.3 0.98 1 9 31 57.7 0.88 0 10 27 68.9 0.93 0 11 35 52.5 0.84 0 12 26 75.9 0.87 0 13* 26 60.9 0.89 0 14 35 63.7 0.9 1 15 21 57.9 0.97 1 16 25 101.8 1.025 1 17 40 78.2 0.93 1 18 46 91.1 0.98 1 19 22 86.5 1.03 1 20 26 75.7 0.935 1 21 24 49.3 0.86 0

Age in years, BM = Body Mass in Kilograms, HH = Hip Height in Meters, Sex = 0 – Female, 1 – Male. White squares indicate trials that were skipped voluntarily by subjects. The first subject acted as a test for the experiment and systems. Asterisks indicate subject data that was not used due to sensor errors. 98

Figure 1. (Marker placement and load carrying diagram)

F = Forehead, C7 = Seventh Cervical Vertebrae, L1 = First Lumbar Vertebrae, GM = Gluteus Maximus, RF = Rectus Femoris, GA = Medial Gastrocnemius, TA = Tibialis Anterior. Carried load was a 9 or 18kg weighted vest placed inside a pillowcase, held in front of the body.

To cover a range of locomotor speeds across different body sizes, subjects walked for 12 trials that included combinations of walking speeds and carried loads. Walking speeds included 1.0, 1.33, 1.66, or 2.0 meters per second. Loading conditions included no load, or 9 and 18 kg carried in front of the body with both hands (see: Fig. 1). The loads comprised of weighted vests inside pillowcases. Additionally, subjects jogged or ran for two trials at 2.0 or 2.66 meters per second without carrying a load. The order of all 14 trials were randomized for each subject. Subjects were instructed to maintain a stable gaze at an eye level 99

image one meter in front of them throughout each trial. Data were collected for 30 seconds after a 15 second warmup period on the treadmill to ensure full speed had been reached. The first 10 steps (calculated from maximal tibial acceleration [g’s] of the right leg using a custom MATLAB program [MATLAB version

R2015b]) after the midpoint of each trial were used during final analysis (Zijlstra, 2004; Zijlstra and Hof,

2003).

Maximum head and trunk pitch velocity (° / sec) and acceleration (° / sec 2) and lower limb accelerations (in g’s) were averaged across the ten strides after calculating peak accelerations and pitch velocities for each stride. For automated stride detection, tibial acceleration data were filtered using a fourth order Butterworth low pass filter with a cut-off frequency of 2 Hz reflecting expected maximum step rates

(Zijlstra, 2004; Zijlstra and Hof, 2003). Maximal pitch rates are high frequency and amplitude data and were filtered using fourth order Butterworth low pass filter with a cut-off frequency of 75 Hz (Huterer and

Cullen, 2002). To allow for comparisons across a broad range of body sizes Froude numbers were used in place of walking velocity for initial data analysis. The Froude number (Fr) is calculated as v2 / gL, where v is velocity (m / sec), g is gravitational acceleration (9.81 m / sec 2), and L is a characteristic length, typically limb length measured as hip height. Fr is a dimensionless speed value that accounts for differences in lower limb length between subjects.

Statistical analyses were conducted using Linear Mixed Effects Models (‘lmerTest’ package version 2.0-33 in R version 3.3.3). Locomotor speed (Fr), gait (walking or running), and carried load weight

(kg), were treated as fixed effects. Subject number was added as a random effect to allow us to adjust the error terms to account for repeated measures from multiple trials from the same individual. Participant sex and body mass were also added to the model as independent variables. Pitch accelerations were treated as the continuous dependent variables and compared against null models (using a Wald chi-squared test) that did not include load mass or carrying / not carrying. Likelihood ratio tests were used to examine the effects of carrying on head and trunk pitch to calculate associated p-values. A post-hoc multiple comparisons analysis was run to test at what speeds, if any, running and loaded walking maximal head pitch rates overlap. 100

Associated p-values were corrected using Tukey’s honest significant differences method to account for multiple testing.

Results Trunk pitch increased with speed and gait type (Froude p > 0.001, gait p > 0.001, Table 2A & Fig.

2A), as found previously (Lieberman et al., 2006). However, maximal trunk pitch accelerations increased more slowly with increases in locomotor speed during running than compared with walking (Froude:gait interaction p = 0.002). Carried load did not significantly improve upon the null model for maximal trunk pitch (p = 0.952, X2 = 0.004). Neither sex nor body mass significantly are significantly associated with trunk pitch accelerations.

The model predicting maximal head pitch accelerations was significantly improved by including carried load weight (p < 0.0001, X2 = 26.809) when compared to a null model without carried load.

Locomotor speed and carried load significantly increased maximal head pitch accelerations (Froude

11896.73 ± 1088.00° / sec, p < 0.001, Kg 83.28 ± 15.70° / sec, p < 0.001, Table 2B & Fig. 2B) but the interaction of speed and gait type suggests that the effects of speed on head pitch depend on gait, and running gaits may decrease maximal pitch rates compared with high-speed walking (Froude:gait interaction

-11198.51 ± 1892.22° / sec, p < 0.001). Participant sex and body mass were not significantly associated with maximal head pitch rates. Additionally, running was associated with significantly reduced maximal head acceleration by 1121.85 ± 197.54° / sec 2 at similar maximal head velocities (p < 0.0001).

Table 2. (Linear mixed model statistics of trunk and head pitch)

Std. Fixed Effects: Estimate df t Value Pr(>|t|) Error Trunk Pitch Acceleration (° / sec 2) A (Intercept) 466.5626 1248.5623 12.9456 0.374 0.71469 Gait 6797.6947 664.0923 182.6768 10.236 < 2e-16 Froude 6182.7736 741.0538 183.737 8.343 1.68E-14 Sex -226.8293 534.2423 12.6579 -0.425 0.67827 Body Mass 0.4495 19.653 12.2081 0.023 0.98212 Gait:Froude -4089.3044 1291.7432 184.4004 -3.166 0.00181 Head Pitch Acceleration (° / sec 2) B (Intercept) 2142.76 3713.84 16.18 0.577 0.571904 101

Gait 3673.89 982.45 185.19 3.74 0.000246 Froude 11896.73 1088 185.4 10.935 < 2e-16 Carried Kg 83.28 15.7 185.17 5.306 3.18E-07 Sex -1155.76 1592.68 16.11 -0.726 0.478449 Body Mass -18.07 59.07 15.91 -0.306 0.763616 Gait:Froude -11198.51 1892.22 185.67 -5.918 1.54E-08

A: Trunk pitch linear regression statistics, Gait = Running or Walking. B: Head pitch linear regression statistics, Carrying = Carrying or not Carrying a load, Gait = Running or Walking.

Figure 2. (Maximal trunk and head pitch rates across speed and load)

A post-hoc multiple comparisons analysis was performed in order to determine whether running and loaded walking shared similar maximal head accelerations. This analysis included all walking conditions (18kg, 9kg, and unloaded) which were compared with jogging (2.00 m / s) or running (2.66 m / s). At the lowest walking speed (1.00 m / s) both jogging and running generated significantly higher maximal head pitch accelerations only when subjects were unloaded or carried the light load (9kg, Table

2). However, walking at 1.33 – 1.66 meters per second while carrying either load (9 or 18kg) generated maximal head pitch accelerations that were not significantly different than jogging or running (Table 3). 102

Finally, at the fastest walking speed of 2.00 meters per second, maximal head pitch accelerations were higher than both jogging and running while carrying a load (Table 3).

Table 3. (Multiple comparisons analysis of head pitch between speeds)

Max Head Acceleration (° / sec 2) Multiple Comparisons Linear Hypotheses Estimate Std. Error z value Pr(>|z|) Walk(1.00 m/s) – Jog(2.00 m/s) -2346.9 507.8 -4.622 <0.01 Walk(1.00 m/s) – Run(2.66 m/s) -2464.4 573.6 -4.296 <0.01 Walk(1.00 m/s)9kg – Jog(2.00 m/s) -1684.4 501.3 -3.36 0.0151 Walk(1.00 m/s)9kg – Run(2.66 m/s) -1802 567.9 -3.173 0.0275 Walk(1.00 m/s)18kg – Jog(2.00 m/s) -1204.7 501.3 -2.403 0.2167 Walk(1.00 m/s)18kg – Run(2.66 m/s) -1322.3 567.9 -2.328 0.2538 Walk(1.33 m/s) – Jog(2.00 m/s) -1604.9 501.3 -3.202 0.0256 Walk(1.33 m/s) – Run(2.66 m/s) -1722.5 567.9 -3.033 0.0424 Walk(1.33 m/s)9kg – Jog(2.00 m/s) -980.4 501.3 -1.956 0.4905 Walk(1.33 m/s)9kg – Run(2.66 m/s) -1098 567.9 -1.933 0.507 Walk(1.33 m/s)18kg – Jog(2.00 m/s) -189.7 501.3 -0.378 1 Walk(1.33 m/s)18kg – Run(2.66 m/s) -307.3 567.9 -0.541 1 Walk(1.66 m/s) – Jog(2.00 m/s) -835.8 509.1 -1.642 0.7219 Walk(1.66 m/s) – Run(2.66 m/s) -953.4 575.4 -1.657 0.7111 Walk(1.66 m/s)9kg – Jog(2.00 m/s) 626.5 501.3 1.25 0.933 Walk(1.66 m/s)9kg – Run(2.66 m/s) 509 567.9 0.896 0.9946 Walk(1.66 m/s)18kg – Jog(2.00 m/s) 875.2 501.3 1.746 0.6469 Walk(1.66 m/s)18kg – Run(2.66 m/s) 757.6 567.9 1.334 0.9008 Walk(2.00 m/s) – Jog(2.00 m/s) 407.7 518 0.787 0.9984 Walk(2.00 m/s) – Run(2.66 m/s) 290.2 584.1 0.497 1 Walk(2.00 m/s)9kg – Jog(2.00 m/s) 2624.8 581.2 4.516 <0.01 Walk(2.00 m/s)9kg – Run(2.66 m/s) 2507.2 640.7 3.914 <0.01 Walk(2.00 m/s)18kg – Jog(2.00 m/s) 2702.4 646 4.183 <0.01 Walk(2.00 m/s)18kg – Run(2.66 m/s) 2584.8 699.5 3.695 <0.01

Discussion The results of this study suggest that high speeds and load carrying during walking in humans can produce maximal head pitch accelerations equal to or greater than those experienced during running even though carrying a load reduced trunk acceleration. Additionally, as walking speed increased so did head pitch accelerations, similar to results from previous research examining the relationship between walking impact forces, speed, and head pitch accelerations (Cromwell et al., 2001; Hirasaki et al., 1999; Webber 103

and Raichlen, 2013). These results suggest that there may be a range of behaviors that could have played a role in changes to SCC morphology during human evolution.

Historically, the SCC system has been viewed as a window into hominin locomotor behaviors, with a focus on the evolution of bipedalism (Spoor and Zonneveld, 1998). Later work expanded upon the implications of enlarged canal diameters in early members of the genus Homo by linking agile behaviors to canal diameter in other taxa, suggesting SCCs in H. erectus may reflect the use of high-speed locomotion like running as the adopted a hunting and gathering lifestyle (Bramble and Lieberman, 2004; Cox and

Jeffery, 2010; Lieberman, 2011; Lieberman et al., 2009; Malinzak et al., 2012; Spoor, 2003). The present study highlights the importance of distinguishing between high-speed locomotor activities, and those which may produce elevated head perturbations. Previous research on primate SCC diameters have been careful to note that canal size does not always perfectly fit expected size or agility categories (Spoor et al., 2007).

Our work suggests changes in canal morphology, which may aid endurance running behaviors, could also be adaptive for a range of walking behaviors including load carrying and high walking speeds, which may suggest a mosaic acquisition of the human endurance running capacity.

Two forms of carrying behaviors were likely common in bipedal foragers as they transition to a hunting and gathering lifestyle: infant and resource transport. Infant transport behaviors are rare among mammals, but primate juveniles spend long dependent periods carried by their mothers (Ross, 2001), a behavior that adds significant locomotor and postnatal care costs for mammals (Mitani and Watts, 1997;

Watson et al., 2008). Carrying dependent offspring causes additional challenges for mothers aside from added energy demands such as reduced locomotor speeds (Caperos et al., 2012), reduced vigilance

(Altmann, 1980), and increased fall risk (Allman et al., 1998). These risks are likely outweighed by the possible benefits of an increased developmental period in large brained primates (Altmann and Samuels,

1992; Ross, 2001). Non-human primate infant transport often takes the form of dependent riding (Ross,

2001), where the infant clings to the fur a horizontal trunk during quadrupedal movement. Later hairless habitual bipedal walking may therefore cause significant challenges to clinging infants and would have likely required active carrying (Berecz et al., 2020). 104

The adoption of a hunting and gathering lifestyle may have increased the need to carry not only infants, but other resources, and to do so at high speeds over longer distances (Pontzer, 2012). Many small- scale societies practice central place foraging (Kelly, 2013), where resources such as food, artifacts, firewood, and building materials (Hill et al., 1987; Houston and McNamara, 1985; Marlowe, 2010;

Raichlen et al., 2014; Reynolds, 2008; Venkataraman et al., 2017) would have been carried to a central location, and where parents often carry infants and young children during long foraging bouts (Hurtado et al., 1992; Marlowe, 2010). Researchers have suggested that resource transport may have been common as early as 2.5 million years ago (Isaac, 1978, 1981; Klein, 2009), suggesting that early foraging hominins may have participated in carrying behaviors. Extant foragers (including children) often carry heavy loads

(Hill and Hurtado, 2017; Hilton and Greaves, 2008, 2004; Hurtado et al., 1992) especially when moving campsites (Venkataraman et al., 2017). Members of small scale societies have also been recorded traveling at high walking speeds (Hill and Hurtado, 2017; Pontzer et al., 2015), which is especially surprising given the difficulties of traversing natural terrain. Altogether, these factors suggest that high head pitch rates induced by high-speed and loaded walking would have been a significant, regular challenge to foraging bipeds following the transition to a hunting and gathering lifestyle.

While this work has several strengths, including direct measures of head pitch accelerations and controlled locomotor conditions, this study also has some limitations that indicate where future work would be needed. For example, all running activities for this study were performed barefoot, but foot-strike type was not recorded. It is possible that differences in head pitch rates between walking and running are the product of modern running technology (shoes) altering natural locomotor biomechanics (De Wit et al.,

2000; Divert et al., 2005; Lieberman et al., 2010). Previous research finding high impact forces during running are often derived from samples of runners from western contexts who use significantly cushioned shoes and run on flat homogenous surfaces such as a treadmill (De Wit et al., 2000; Divert et al., 2005;

Lieberman et al., 2010). These conditions do not resemble those experienced during human evolution, and research on running in more ecologically relevant settings have found reduced impact forces during running, often equal to or below walking values (Altman and Davis, 2012; Lieberman et al., 2010). If these lower 105

impact forces were more typical of running in earlier hominins, then high speed and loaded walking may have led to even greater head pitch rates compared to running in the fossil record. Future work should include individuals trained in barefoot running with attention focused on foot-strike patterns. In addition, all trials were performed on a treadmill, which provides a highly controlled environment, but lacks real- world obstacles including uneven terrain. Future work should examine how combinations of speed and load alter head kinematics over more ecologically relevant conditions.

Conclusions In humans under experimental settings, carrying a load significantly increases maximal head pitch accelerations. High acceleration head perturbations exist during loaded walking suggesting an enlarged

SCC in early members of the genus Homo may have appeared in response to high-speeds and load carrying during walking, a low speed behavior, paving the way for the adoption of high-speed activities such as endurance running. Our results suggest that a range of behaviors may be linked with traits that seem adapted to resist high impact forces.

Acknowledgments We would like to thank all the subjects who participated in this study for their time and effort in making this study a reality. Additionally, we would like to thank the University of Arizona Social and

Behavior Science Research Institute for the dissertation research grant (#18DRF0885) which funded this study, and the School of Anthropology Haury dissertation fellowship which funded the preparation of this manuscript.

106

References Aiello, L.C., Wells, J.C.K., 2002. Energetics and the Evolution of the Genus Homo. Annu. Rev. Anthropol. 31, 323–338. https://doi.org/10.1146/annurev.anthro.31.040402.085403

Alexander, R., 1991. Energy-Saving Mechanisms in Walking and Running. J. Exp. Biol. 160, 55–69.

Allman, J., Rosin, A., Kumar, R., Hasenstaub, A., 1998. Parenting and survival in anthropoid primates: Caretakers live longer. Proc. Natl. Acad. Sci. 95, 6866–6869.

Altman, A.R., Davis, I.S., 2012. Barefoot Running: Biomechanics and Implications for Running Injuries. Curr. Sports Med. Rep. 11, 244–250. https://doi.org/10.1249/JSR.0b013e31826c9bb9

Altmann, J., 1980. Baboon mothers and infants: J. Altmann.

Altmann, J., Samuels, A., 1992. Costs of maternal care: infant-carrying in baboons. Behav. Ecol. Sociobiol. 29, 391–398. https://doi.org/10.1007/BF00170168

Atkin, A., Bender, M., 1968. Ocular Stabilization During Oscillatory Head Movements - Vestibular System Dysfunction and Relation Between Head and Eye Velocities. Arch. Neurol. 19, 559-.

Berecz, B., Cyrille, M., Casselbrant, U., Oleksak, S., Norholt, H., 2020. Carrying human infants – An evolutionary heritage. Infant Behav. Dev. 60, 101460. https://doi.org/10.1016/j.infbeh.2020.101460

Berge, C., 1994. How did the australopithecines walk? A biomechanical study of the hip and thigh of Australopithecus afarensis. J. Hum. Evol. 26, 259–273. https://doi.org/10.1006/jhev.1994.1016

Birrell, S.A., Hooper, R.H., Haslam, R.A., 2007. The effect of military load carriage on ground reaction forces. Gait Posture 26, 611–614. https://doi.org/10.1016/j.gaitpost.2006.12.008

Bramble, D., Lieberman, D., 2004. Endurance running and the evolution of Homo. Nature 432, 345–352. https://doi.org/10.1038/nature03052

Caperos, J.M., Morcillo, A., Pelaez, F., Fidalgo, A., Sanchez, S., 2012. The Effect of Infant Body Mass on Carrier Travel Speed in Cotton-top Tamarins (Saguinus oedipus). Int. J. Primatol. 33, 447–459. https://doi.org/10.1007/s10764-012-9594-3

Carrier, D.R., 1984. The energetic paradox of human running and hominid evolution. Curr. Anthropol. 25, 483–495. https://doi.org/10.1086/203165

Castro, M., Abreu, S., Sousa, H., Machado, L., Santos, R., Vilas-Boas, J.P., 2013. Ground reaction forces and plantar pressure distribution during occasional loaded gait. Appl. Ergon. 44, 503–509. https://doi.org/10.1016/j.apergo.2012.10.016

Cox, P.G., Jeffery, N., 2010. Semicircular canals and agility: the influence of size and shape measures. J. Anat. 216, 37–47. https://doi.org/10.1111/j.1469-7580.2009.01172.x

Cromwell, R.L., Newton, R.A., Carlton, L.G., 2001. Horizontal plane head stabilization during locomotor tasks. J. Mot. Behav. 33, 49–58. 107

Cunningham, C.B., Schilling, N., Anders, C., Carrier, D.R., 2010. The influence of foot posture on the cost of transport in humans. J. Exp. Biol. 213, 790–797. https://doi.org/10.1242/jeb.038984

Darwin, C., 1871. Descent of Man and Selection in Relation to Sex. Murray, London, England.

De Wit, B., De Clercq, D., Aerts, P., 2000. Biomechanical analysis of the stance phase during barefoot and shod running. J. Biomech. 33, 269–278.

Divert, C., Mornieux, G., Baur, H., Mayer, F., Belli, A., 2005. Mechanical comparison of barefoot and shod running. Int. J. Sports Med. 26, 593–598. https://doi.org/10.1055/s-2004-821327

Fries, E.C., Hellebrandt, F.A., 1943. The influence of pregnancy on the location of the center of gravity, postural stability, and body alignment. Am. J. Obstet. Gynecol. 46, 374–380. https://doi.org/10.1016/S0002-9378(43)90431-4

Frost, B.J., Wylie, D.R., Wang, Y.C., 1994. The Analysis of Motion in the Visual Systems of Birds, in: Davies, M.N.O., Green, P.R. (Eds.), Perception and Motor Control in Birds: An Ecological Approach. Springer, Berlin, Heidelberg, pp. 248–269. https://doi.org/10.1007/978-3-642-75869-0_15

Gatesy, S.M., Biewener, A.A., 1991. Bipedal locomotion: effects of speed, size and limb posture in birds and humans. J. Zool. J. Zool. 224, 127–147. https://doi.org/10.1111/j.1469-7998.1991.tb04794.x

Gray, A.A., 1908. The Labyrinth of Animals: Including Mammals, Birds, Reptiles and Amphibians. J. & A. Churchill.

Hadžiselimović, H., Savković, L.J., 1964. Appearance of semicircular canals in birds in relation to mode of life. Cells Tissues Organs 57, 306–315.

Hamill, J., Derrick, T.R., Holt, K.G., 1995. Shock attenuation and stride frequency during running. Hum. Mov. Sci. 14, 45–60. https://doi.org/10.1016/0167-9457(95)00004-C

Hill, K., Kaplan, H., Hawkes, K., Hurtado, A.M., 1987. Foraging decisions among Aché hunter-gatherers: New data and implications for optimal foraging models. Ethol. Sociobiol. 8, 1–36. https://doi.org/10.1016/0162-3095(87)90055-0

Hill, K.R., Hurtado, A.M., 2017. Ache Life History: The Ecology and Demography of a Foraging People. Transaction Publishers.

Hilton, C.E., Greaves, R.D., 2008. Seasonality and Sex Differences in Travel Distance and Resource Transport in Venezuelan Foragers. Curr. Anthropol. 49, 144–153. https://doi.org/10.1086/524760

Hilton, C.E., Greaves, R.D., 2004. Age, sex, and resource transport in Venezuelan foragers. Kluwer Academic/Plenum Publ, New York.

Hirasaki, E., Moore, S.T., Raphan, T., Cohen, B., 1999. Effects of walking velocity on vertical head and body movements during locomotion. Exp. Brain Res. 127, 117–130. https://doi.org/10.1007/s002210050781 108

Houston, A.I., McNamara, J.M., 1985. A general theory of central place foraging for single-prey loaders. Theor. Popul. Biol. 28, 233–262. https://doi.org/10.1016/0040-5809(85)90029-2

Hurtado, A.M., Hill, K., Hurtado, I., Kaplan, H., 1992. Trade-Offs between female food acquisition and child care among hiwi and ache foragers. Hum. Nat. 3, 185–216. https://doi.org/10.1007/BF02692239

Huterer, M., Cullen, K.E., 2002. Vestibuloocular Reflex Dynamics During High-Frequency and High- Acceleration Rotations of the Head on Body in Rhesus Monkey. J. Neurophysiol. 88, 13–28. https://doi.org/10.1152/jn.2002.88.1.13

Isaac, G., 1978. The Food-sharing Behavior of Protohuman Hominids. Sci. Am. 238, 90–109.

Isaac, G.L., 1981. Archaeological Tests of Alternative Models of Early Hominid Behaviour: Excavation and Experiments. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 292, 177–188.

Jones, G.M., Spells, K.E., 1963. A theoretical and comparative study of the functional dependence of the semicircular canal upon its physical dimensions. Proc. R. Soc. Lond. B Biol. Sci. 157, 403–419. https://doi.org/10.1098/rspb.1963.0019

Kelly, D.R.L., 2013. The Lifeways of Hunter-Gatherers: The Foraging Spectrum, 2 edition. ed. Cambridge University Press, Cambridge.

King, F.A., Taub, D.M., 1986. Current Perspectives in Primate Biology. Van Nostrand Reinhold.

Klein, R.G., 2009. The Human Career: Human Biological and Cultural Origins, Third Edition, Third Edition, Third Edition. ed. University Of Chicago Press, Chicago, IL.

Kuhn, S.L., Raichlen, D.A., Clark, A.E., 2016. What moves us? How mobility and movement are at the center of human evolution. Evol. Anthropol. Issues News Rev. 25, 86–97. https://doi.org/10.1002/evan.21480

Latimer, B., Lovejoy, C., 1989. The Calcaneus of Australopithecus-Afarensis and Its Implications for the Evolution of Bipedality. Am. J. Phys. Anthropol. 78, 369–386. https://doi.org/10.1002/ajpa.1330780306

Lee, C.R., Farley, C.T., 1998. Determinants of the center of mass trajectory in human walking and running. J. Exp. Biol. 201, 2935–2944.

Liebenberg, L., 2008. The relevance of persistence hunting to human evolution. J. Hum. Evol. 55, 1156– 1159. https://doi.org/10.1016/j.jhevol.2008.07.004

Liebenberg, L., 2006. Persistence hunting by modern hunter-gatherers. Curr. Anthropol. 47, 1017–1025. https://doi.org/10.1086/508695

Lieberman, D., 2011. The Evolution of the Human Head. Harvard University Press.

Lieberman, D.E., Bramble, D.M., Raichlen, D.A., Shea, J.J., 2009. Brains, Brawn, and the Evolution of Human Endurance Running Capabilities, in: Grine, F.E., Fleagle, J.G., Leakey, R.E. (Eds.), The First Humans 109

– Origin and Early Evolution of the Genus Homo, Vertebrate Paleobiology and Paleoanthropology. Springer Netherlands, pp. 77–92. https://doi.org/10.1007/978-1-4020-9980-9_8

Lieberman, D.E., Raichlen, D.A., Pontzer, H., Bramble, D.M., Cutright-Smith, E., 2006. The human gluteus maximus and its role in running. J. Exp. Biol. 209, 2143–2155. https://doi.org/10.1242/jeb.02255

Lieberman, D.E., Venkadesan, M., Werbel, W.A., Daoud, A.I., D’Andrea, S., Davis, I.S., Mang’Eni, R.O., Pitsiladis, Y., 2010. Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature 463, 531–535. https://doi.org/10.1038/nature08723

Malina, R.M., Little, B.B., 2008. Physical activity: The present in the context of the past. Am. J. Hum. Biol. 20, 373–391. https://doi.org/10.1002/ajhb.20772

Malinzak, M.D., Kay, R.F., Hullar, T.E., 2012. Locomotor head movements and semicircular canal morphology in primates. Proc. Natl. Acad. Sci. 109, 17914–17919. https://doi.org/10.1073/pnas.1206139109

Marlowe, F., 2010. The Hadza: Hunter-gatherers of Tanzania. University of California Press.

McKay, H., Tsang, G., Heinonen, A., MacKelvie, K., Sanderson, D., Khan, K.M., 2005. Ground reaction forces associated with an effective elementary school based jumping intervention. Br. J. Sports Med. 39, 10–14. https://doi.org/10.1136/bjsm.2003.008615

Mitani, J.C., Watts, D., 1997. The evolution of non-maternal caretaking among anthropoid primates: do helpers help? Behav. Ecol. Sociobiol. 40, 213–220. https://doi.org/10.1007/s002650050335

Mulavara, A.P., Bloomberg, J.J., 2002. Identifying head-trunk and lower limb contributions to gaze stabilization during locomotion. J. Vestib. Res. Equilib. Orientat. 12, 255–269.

Park, H., Branson, D., Kim, S., Warren, A., Jacobson, B., Petrova, A., Peksoz, S., Kamenidis, P., 2014. Effect of armor and carrying load on body balance and leg muscle function. Gait Posture 39, 430–435. https://doi.org/10.1016/j.gaitpost.2013.08.018

Pontzer, H., 2012. Ecological Energetics in Early Homo. Curr. Anthropol. 53, S346–S358. https://doi.org/10.1086/667402

Pontzer, H., Raichlen, D.A., Wood, B.M., Emery Thompson, M., Racette, S.B., Mabulla, A.Z.P., Marlowe, F.W., 2015. Energy expenditure and activity among Hadza hunter-gatherers. Am. J. Hum. Biol. 27, 628–637. https://doi.org/10.1002/ajhb.22711

Pontzer, H., Raichlen, D.A., Wood, B.M., Mabulla, A.Z.P., Racette, S.B., Marlowe, F.W., 2012. Hunter- Gatherer Energetics and Human Obesity. PLoS ONE 7, e40503. https://doi.org/10.1371/journal.pone.0040503

Raichlen, D.A., Armstrong, H., Lieberman, D.E., 2011. Calcaneus length determines running economy: Implications for endurance running performance in modern humans and Neandertals. J. Hum. Evol. 60, 299–308. https://doi.org/10.1016/j.jhevol.2010.11.002 110

Raichlen, D.A., Webber, J.T., Pontzer, H., 2019. The evolution of the human endurance phenotype. Routledge Handb. Sport Exerc. Syst. Genet. 135–147. https://doi.org/10.4324/9781315146287- 11

Raichlen, D.A., Wood, B.M., Gordon, A.D., Mabulla, A.Z.P., Marlowe, F.W., Pontzer, H., 2014. Evidence of Lévy walk foraging patterns in human hunter–gatherers. Proc. Natl. Acad. Sci. 111, 728–733. https://doi.org/10.1073/pnas.1318616111

Reynolds, A.M., 2008. Optimal random Lévy-loop searching: new insights into the searching behaviours of central-place foragers. EPL Europhys. Lett. 82, 20001.

Ross, C., 2001. Park or Ride? Evolution of Infant Carrying in Primates. Int. J. Primatol. 22, 749–771. https://doi.org/10.1023/A:1012065332758

Spoor, F., 2003. The semicircular canal system and locomotor behaviour, with special reference to hominin evolution. Cour.-Forschungsinstitut Senckenberg 93–104.

Spoor, F., Bajpai, S., Hussain, S.T., Kumar, K., Thewissen, J.G.M., 2002. Vestibular evidence for the evolution of aquatic behaviour in early cetaceans. Nature 417, 163–166. https://doi.org/10.1038/417163a

Spoor, F., Garland, T., Krovitz, G., Ryan, T.M., Silcox, M.T., Walker, A., 2007. The primate semicircular canal system and locomotion. Proc. Natl. Acad. Sci. 104, 10808–10812. https://doi.org/10.1073/pnas.0704250104

Spoor, F., Zonneveld, F., 1998. Comparative review of the human bony labyrinth. Am. J. Phys. Anthropol. Suppl 27, 211–251.

Taylor, C., Lyman, C., 1972. Heat storage in running antelopes: independence of brain and body temperatures. Am. J. Physiol.-Leg. Content 222, 114–117. https://doi.org/10.1152/ajplegacy.1972.222.1.114

Venkataraman, V.V., Kraft, T.S., Dominy, N.J., Endicott, K.M., 2017. Hunter-gatherer residential mobility and the marginal value of rainforest patches. Proc. Natl. Acad. Sci. 114, 3097–3102. https://doi.org/10.1073/pnas.1617542114

Watson, J.C., Payne, R.C., Chamberlain, A.T., Jones, R.K., Sellers, W.I., 2008. The energetic costs of load- carrying and the evolution of bipedalism. J. Hum. Evol. 54, 675–683. https://doi.org/10.1016/j.jhevol.2007.10.004

Webber, J.T., Raichlen, D.A., 2013. Heel-strike and impact transient during bipedal walking: Implications for the acquisition of a habitual bipedal gait. Am. J. Phys. Anthropol. 150, 287–287.

Wilson, V.J., 2013. Mammalian Vestibular Physiology. Springer Science & Business Media.

Wright, S., Weyand, P.G., 2001. The application of ground force explains the energetic cost of running backward and forward. J. Exp. Biol. 204, 1805–1815. 111

Zijlstra, W., 2004. Assessment of spatio-temporal parameters during unconstrained walking. Eur. J. Appl. Physiol. 92, 39–44. https://doi.org/10.1007/s00421-004-1041-5

Zijlstra, W., Hof, A.L., 2003. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture 18, 1–10. https://doi.org/10.1016/S0966-6362(02)00190-X

112

APPENDIX C: MANUSCRIPT 3

A comparison of gluteus maximus activation during running and loaded walking in humans

James T. Webber1,* and David A. Raichlen2

1 School of Anthropology, University of Arizona. Tucson, AZ 85721, USA

2 Human and Evolutionary Biology Section, Department of Biological Science, University of Southern California, Los Angeles, CA 90089, USA

* [email protected]

113

Abstract Several derived traits found in members of the genus Homo, including an increased size of the gluteus maximus (GM), appear to have their origins in the resistance of rapid of trunk pitch, which some have linked to running activities. Previous research suggests the enlarged size of the GM may be an adaptation to resist trunk pitch during endurance running or sprinting behaviors, but no research has explored the role of load carrying on gluteal activity when compared to running. Carrying a load may alter the location of a subject’s center of mass, and specifically, frontal loads may increase trunk pitch due the anterior position of the load compared to the subjects’ natural center of mass. To examine the effects of load carrying on GM function, electromyography data were collected from the GM and three lower limb muscles (rectus femoris, tibialis anterior, and gastrocnemius) from 20 subjects while they walked unloaded, carrying a load in their arms, or instead ran unloaded. While carrying a load significantly increased normalized GM activity (p = 0.003), maximal electromyography amplitudes were significantly higher during running than any load / walking speed combination (p < 0.001). Conversely, activity in other lower limb muscles increased with speed, but were not significantly altered by running itself (rectus femoris p =

0.71, gastrocnemius p = 0.20, tibialis anterior p = 0.93). Thus, it appears that this research supports endurance running hypotheses for the derived GM size in the genus Homo.

114

Introduction Bipedalism is a defining characteristic of the hominin lineage (Darwin, 1871), and fossil evidence suggests there may be many ways of being bipedal (DeSilva et al., 2013; Latimer and Lovejoy, 1989).

Much of the lower limb has undergone mosaic transformations from the time of the first upright walkers to our present configuration (Aiello and Dean, 1990; Lovejoy, 1988; Ward, 2002). The early hominin lower limb musculoskeletal system appears best adapted for energetically economical walking gaits (Cunningham et al., 2010; Harcourt-Smith and Aiello, 2004; Pontzer, 2017; Ward, 2002). Other locomotor modes have been suggested to be important to later hominin foraging and may have also generated significant selective pressures on musculoskeletal morphology (Berecz et al., 2020; Carrier, 1984). One such mode is endurance running (ER), which is thought to have been a key behavior aiding the acquisition of meat starting around

2 million years ago during the evolution of the genus Homo (Bramble and Carrier, 1983; Bramble and

Lieberman, 2004; Carrier, 1984; Hora et al., 2020; Liebenberg, 2008).

Many derived musculoskeletal traits in early members of the genus Homo have been linked to the adoption of habitual ER (Lieberman et al., 2006; Zimmermann et al., 1994), underscoring the potential importance of this locomotor behavior in shaping the human body. One such trait, an enlarged gluteus maximus (GM) is distinct in humans compared to great apes, and reconstructions of GM size generally suggest more human-like morphology beginning with Homo erectus (Bramble and Lieberman, 2004;

Lieberman et al., 2006). The GM acts as both a hip extensor and a trunk stabilizer (Lieberman et al., 2006;

Marzke et al., 1988; Stern, 1972), and researchers have suggested that the evolutionary increase in GM size may be associated with activities that require trunk stabilization against flexion moments, such as ER, traversing hills, or sprinting (Bartlett et al., 2014; Bramble and Lieberman, 2004; Zimmermann et al., 1994).

The purpose of this study is to expand upon human GM research by including a range of locomotor behaviors missing from previous research that may also induce trunk flexion like load carrying and high- speed walking, and that reflect variation in modes likely present during hominin evolution.

The GM originates on the superior portion of the iliac crest and crosses the hip joint, inserting onto the superior gluteal ridge of the femur (Aiello and Dean, 1990; Stern, 1972). When the GM contracts it 115

causes extension of the lower limb when the limb is free to move. If the limb is less mobile (i.e, foot in ground contact), the GM can act as a trunk extensor (Lieberman et al., 2006; Stern, 1972). Since the muscle can act as a trunk extensor, it can also act to resist trunk flexion and stabilize the torso though isometric contractions (Marzke et al., 1988; Wall-Scheffler et al., 2010). High ground reaction forces (GRF) at foot touchdown during running have been linked to increased GM activity (Lieberman et al., 2006; Stern et al.,

1980) as the rapid translation of this impact force could cause high trunk pitch velocities. Indeed maximal trunk pitch rates and GM activity are highly correlated, and are both significantly increased during running

(Lieberman et al., 2006). These comparisons suggest that the derived features of the human GM (including enlarged attachment sites) may be the product of behaviors that affect trunk pitch (Marzke et al., 1988).

However, studies examining impact forces have found that running, walking speed, and load carrying all can increase landing GRFs (Birrell et al., 2007; Lieberman et al., 2010; Webber and Raichlen,

2013). In fact, previous research found increased gluteus medius activity during load carrying, with the authors speculated was due specifically to the posterior fibers responsible for hip extension (Neumann and

Cook, 1985). Thus, a range of behaviors may induce the kinds of trunk pitch rates that would require an enlarged GM, and examining GM activity in these conditions will help us better interpret evolutionary changes in GM morphology.

The purpose of this research is to test three hypotheses exploring whether load carrying during walking requires similar maximal GM activation to ER. H1: GM activation is associated with greater trunk pitch. H2: GM activity is greater running that during a range of loaded walking modes within subjects. H3:

GM displays a different patter of activation with speed and load than other lower limb muscles that are not linked with ER. Testing these hypotheses will help us determine whether the GM functions uniquely during running gaits, or whether increased excitation found previously is the product of increased locomotor speeds and GRFs divorced from a specific gait.

Methods Subjects 116

Twenty-one individuals participated in this study at the University of Arizona. The sample included eleven females and ten males who were between the ages of 21 and 48 (see: Table 1). Subjects performed all trials barefoot, and informed consent (approved for this study by the University of Arizona Institutional

Review Board) was collected from each subject prior to involvement in the study. Average hip height was

91.3 ± 6.3 cm (range: 81.5 – 103.0 cm) and mean body mass was 66.7 ± 13.7 kg (range: 49.3 – 101.8 kg).

A Delsys Trigno Wireless Biofeedback System (SP-W06 sensors and SP-W02 base station, Natick, MA) was used to collect lower limb muscle activity. Wireless EMG sensors were affixed using double sided tape and athletic tape (to reduce movement artifacts) to the estimated midpoints of muscle bodies, along their longitudinal axis, on the right lower limb. Muscle sites include tibialis anterior (TA), medial gastrocnemius

(GA), rectus femoris (RF), and gluteus maximus (GM) as described by Basmajian and DeLuca (1985, see:

Figure 1). EMG data were collected at 2000 Hz. Prior to affixing the sensors to the subject, sites were shaved and cleaned using isopropyl alcohol swabs. Additionally, subjects wore one sensor lateral to the spinous process of C7 to capture trunk pitch rates which were also collected at 2000 Hz. All subjects were free of lower limb injury at the time of the study and performed all trials barefoot. 117

Table 1. (Subject details)

1.00 1.33 1.66 2.00 1.00 1.33 1.66 2.00 1.00 1.33 1.66 2.00 2.00 2.66 Subject Age BM HH Sex Walk Walk Walk Walk 9kg 9kg 9kg 9kg 18kg 18kg 18kg 18kg Jog Run 1 28 51.2 0.815 0 2 30 64.8 0.895 0 3 24 57 0.845 0 4 36 64.8 0.870 1 5 25 57.8 0.825 0 6 48 56.7 0.91 0 7 25 61.5 0.985 1 8 34 67.3 0.98 1 9 31 57.7 0.88 0 10 27 68.9 0.93 0 11 35 52.5 0.84 0 12 26 75.9 0.87 0 13 26 60.9 0.89 0 14 35 63.7 0.9 1 15 21 57.9 0.97 1 16 25 101.8 1.025 1 17 40 78.2 0.93 1 18 46 91.1 0.98 1 19 22 86.5 1.03 1 20 26 75.7 0.935 1 21 24 49.3 0.86 0

118

Figure 1. (Marker placement and load carrying diagram)

Data collection

Subjects conducted 12 unique walking trials on the same treadmill (SOLE F63, Salt Lake, UT) which included different combinations of walking speeds and carried loads. Trials included walking speeds of 1.00, 1.33, 1.66, or 2.0 meters per second to cover a range of challenges for subjects of differing body sizes. Therefore, subjects could opt out of any speed and load combination they were not comfortable attempting (see Table 1). During the walking trials subjects carried loads of 9 and 18 kg in front of the body with both hands (see: Fig. 1), or no load at all. For this study the loads were weighted vests inside pillowcases to make carrying easier. Additionally, subjects jogged or ran for two trials at 2.00 or 2.66 meters 119

per second without carrying a load. The order of all 14 trials were randomized for each subject. One-minute trials started after a 15 second delay to allow the treadmill to reach full speed. Data were collected from the last 30 seconds of each trial. The first 10 steps (calculated from maximal acceleration [g’s] of the right leg tibialis anterior sensor using a custom MATLAB program [MATLAB version R2015b], collected at 2000

Hz and filtered using a 4th order zero-lag Butterworth filter with a cutoff of 2 Hz) from the data collected for each trial were used during final analysis (Zijlstra, 2004).

Data processing

To account for movement artefacts, EMG data were filtered using a fourth-order zero-lag

Butterworth filter with cut-off frequencies of 10 and 350 Hz (De Luca et al., 2010; Rahnama et al., 2006;

Zijlstra, 2004). The data was then rectified and filtered using a fourth-order Butterworth low pass filter with a 6 Hz cutoff to obtain the linear envelope of the muscle activity signal (Rahnama et al., 2006). The maximum amplitude during the first half of the stride was used to ensure only stance phase activity was used. Maximum amplitudes of muscle activity at each muscle site were averaged across the ten strides after data processing. All EMG data were normalized to the maximum trial amplitude within each subject. To allow for comparisons across a broad range of body sizes Froude numbers were used in place of walking velocity for initial data analysis. The Froude number (Fr) is calculated as v2 / gL, where v is velocity (m/s), g is gravitational acceleration (9.81 m/s2), and L is a characteristic length, typically limb length measured as hip height. Fr is a dimensionless speed value that accounts for differences in lower limb length between subjects. Additionally, loads were scaled to body mass for analysis.

Statistics

Statistical analyses were conducted using Linear Mixed Effects Models (‘lmerTest’ package version 2.0-33 in R version 3.3.3). Locomotor speed (Fr), gait (walking or running), and carried load

(kilograms), were treated as fixed effects. Subject number was added as a random effect to allow us to adjust the error terms to account for repeated measures from multiple trials from the same individual.

Additionally, participant sex, body mass, and trial order number were included in the models. Likelihood ratio tests were used to examine the effects of load and speed on lower limb muscle activity to calculate 120

associated p-values. Muscle excitation data were treated as the continuous dependent variables and compared against null models without gait (running or walking) to determine whether differences in activity were the product of biomechanical differences between walking and running. To determine whether running was significantly different from any of the walking conditions a Tukey’s HSD post-hoc multiple comparisons analysis was conducted to test the differences between each condition mean. By including both speed and gait in the models, these methods allow us to tease apart the separate effects of gait mechanics compared with just increased movement velocity on GM activity.

Results Maximal trunk pitch during both loaded walking and running was significantly correlated with GM excitation supporting Hypothesis 1 (H2, r2 = 0.92, Fig. 2) as found previously (Lieberman et al., 2006).

Following Hypothesis 2 (H2), normalized GM amplitude was significantly higher during running after controlling for speed, carried load, sex, body mass, and trial order (X2 = 48.00, p < 0.001, Fig. 3). Running increased maximal scaled muscle amplitude by 30.1 ± 4.1 % of subject max average EMG amplitude compared to walking at similar speeds (p < 0.001, Table 2). For other lower limb muscles (H3), while speed was significantly related to maximum muscle amplitude (Table 2), adding running did not improve upon the null model (RF X2 = 0.13, p = 0.71, TA X2 = 0.01, p = 0.93, GA X2 = 1.69, p = 0.20, Fig. 3). Post- hoc multiple comparisons analysis found that GM activity during running was significantly higher than all other walking conditions (Table 3). The rest of the lower limb muscles tested showed similar activity levels during jogging (2.00 m/s) and fast (1.66 m/s) walking, and during the highest walking speed (2.00 m/s) and running (2.66 m/s, see: Table 3).

121

Figure 2. (Gluteus maximus muscle activity and trunk pitch)

Table 2. (Lower limb muscle activity linear mixed model results)

Muscle Parameter Estimate Std.Error df t-value p-value Gluteus Ma ximus (Intercept) 0.482924 0.155234 18.26743 3.111 0.00595 Froude Number 0.671831 0.081422 228.8307 8.251 1.2E-14 Load (kg) 0.004412 0.00145 226.1732 3.042 0.00262 Gait (w vs r) 0.300515 0.041271 227.0291 7.282 5.4E-12 Sex 0.130121 0.065015 16.93132 2.001 0.06164 Body Mass (kg) -0.0061 0.002442 16.69975 -2.497 0.02332 Trial Order -0.00432 0.002073 228.5505 -2.086 0.0381

Rectus Femoris (Intercept) 0.07558 0.1865 19.1 0.405 0.6899 Froude Number 0.9724 0.1154 230.6 8.429 3.8E-15 Load (kg) 0.002521 0.002073 227.5 1.216 0.2252 Gait (w vs r) -0.02152 0.05895 228.8 -0.365 0.7154 Sex 0.002414 0.07753 17.18 0.031 0.9755 Body Mass (kg) 0.000944 0.002909 16.88 0.325 0.7495 Trial Order -0.0063 0.002946 230.4 -2.139 0.0335

Tibialis Anterior (Intercept) 0.244037 0.204683 17.76562 1.192 0.2488 Froude Number 0.650053 0.085229 228.5182 7.627 6.4E-13 Load (kg) 0.002108 0.001528 227.1005 1.38 0.1691 Gait (w vs r) 0.003072 0.043502 227.6813 0.071 0.9438 Sex -0.09018 0.086344 16.94015 -1.044 0.3109 Body Mass (kg) 0.002825 0.003248 16.80776 0.87 0.3966 Trial Order -0.00658 0.002177 228.4544 -3.022 0.0028

Medial Gastroc (Intercept) 0.289979 0.20583 17.71974 1.409 0.17619 Froude Number 0.700196 0.079563 228.3658 8.801 3.4E-16 Load (kg) 0.001519 0.001426 227.1464 1.065 0.28796 Gait (w vs r) -0.05317 0.040604 227.6451 -1.31 0.19167 Sex -0.07436 0.086973 17.00897 -0.855 0.40446 Body Mass (kg) 0.001979 0.003273 16.89468 0.605 0.55347 Trial Order -0.00658 0.002032 228.3117 -3.239 0.00138

122

Figure 3. (Lower limb muscle activity)

RF = Rectus Femoris, TA = Tibialis Anterior, GA = Medial Gastrocnemius, GM = Gluteus Maximus. *’s indicate a significant difference from jogging (2.00 m/s), #’s indicate a significant difference from running (2.66 m/s)

123

Table 3. (Post-hoc multiple comparisons analysis)

Linear Hypotheses: GM Max Amp GA Max Amp TA Max Amp RF Max Amp Est Std. Er z Val p Est Std. Er z Val p Est Std. Er z Val p Est Std. Er z Val p 1.00 Walk - 2.00 Jog -0.56 0.05 -11.07 <0.01 -0.22 0.05 -4.55 <0.01 -0.28 0.05 -5.36 <0.01 -0.49 0.07 -7.27 <0.01 1.00 Walk 9kg - 2.00 Jog -0.54 0.05 -10.84 <0.01 -0.19 0.05 -4.02 <0.01 -0.27 0.05 -5.23 <0.01 -0.47 0.07 -7.07 <0.01 1.00 Walk 18kg - 2.00 Jog -0.51 0.05 -10.18 <0.01 -0.22 0.05 -4.62 <0.01 -0.30 0.05 -5.92 <0.01 -0.43 0.07 -6.35 <0.01 1.00 Walk - 2.66 Run -0.69 0.05 -12.98 <0.01 -0.39 0.05 -7.70 <0.01 -0.39 0.05 -7.19 <0.01 -0.54 0.07 -7.62 <0.01 1.00 Walk 9kg - 2.66 Run -0.67 0.05 -12.77 <0.01 -0.36 0.05 -7.24 <0.01 -0.38 0.05 -7.09 <0.01 -0.52 0.07 -7.43 <0.01 1.00 Walk 18kg - 2.66 Run -0.65 0.05 -12.14 <0.01 -0.40 0.05 -7.77 <0.01 -0.42 0.05 -7.72 <0.01 -0.47 0.07 -6.74 <0.01 1.33 Walk - 2.00 Jog -0.53 0.05 -10.82 <0.01 -0.17 0.05 -3.64 <0.01 -0.22 0.05 -4.31 <0.01 -0.42 0.07 -6.30 <0.01 1.33 Walk 9kg - 2.00 Jog -0.47 0.05 -9.47 <0.01 -0.13 0.05 -2.62 0.14 -0.19 0.05 -3.71 <0.01 -0.28 0.07 -4.29 <0.01 1.33 Walk 18kg - 2.00 Jog -0.45 0.05 -9.10 <0.01 -0.12 0.05 -2.48 0.19 -0.16 0.05 -3.19 0.028 -0.32 0.07 -4.86 <0.01 1.33 Walk - 2.66 Run -0.67 0.05 -12.76 <0.01 -0.35 0.05 -6.88 <0.01 -0.33 0.05 -6.21 <0.01 -0.46 0.07 -6.69 <0.01 1.33 Walk 9kg - 2.66 Run -0.61 0.05 -11.49 <0.01 -0.30 0.05 -5.90 <0.01 -0.30 0.05 -5.64 <0.01 -0.33 0.07 -4.78 <0.01 1.33 Walk 18kg - 2.66 Run -0.59 0.05 -11.15 <0.01 -0.29 0.05 -5.77 <0.01 -0.27 0.05 -5.14 <0.01 -0.37 0.07 -5.33 <0.01 1.66 Walk - 2.00 Jog -0.42 0.05 -8.45 <0.01 -0.09 0.05 -1.80 0.63 -0.15 0.05 -2.93 0.06 -0.18 0.07 -2.75 0.10 1.66 Walk 9kg - 2.00 Jog -0.38 0.05 -7.75 <0.01 -0.05 0.05 -1.00 0.99 -0.13 0.05 -2.50 0.18 -0.17 0.07 -2.60 0.14 1.66 Walk 18kg - 2.00 Jog -0.31 0.05 -6.24 <0.01 -0.03 0.05 -0.53 1.00 -0.06 0.05 -1.07 0.98 -0.20 0.07 -3.03 0.05 1.66 Walk - 2.66 Run -0.56 0.05 -10.52 <0.01 -0.26 0.05 -5.07 <0.01 -0.26 0.05 -4.87 <0.01 -0.23 0.07 -3.29 0.02 1.66 Walk 9kg - 2.66 Run -0.52 0.05 -9.87 <0.01 -0.22 0.05 -4.35 <0.01 -0.24 0.05 -4.49 <0.01 -0.22 0.07 -3.16 0.03 1.66 Walk 18kg - 2.66 Run -0.45 0.05 -8.47 <0.01 -0.20 0.05 -3.87 <0.01 -0.17 0.05 -3.10 0.04 -0.25 0.07 -3.58 <0.01 2.00 Walk - 2.00 Jog -0.32 0.05 -6.17 <0.01 0.08 0.05 1.51 0.82 -0.01 0.05 -0.17 1 -0.10 0.07 -1.43 0.87 2.00 Walk 9kg - 2.00 Jog -0.32 0.06 -5.54 <0.01 -0.01 0.06 -0.26 1.00 -0.08 0.06 -1.33 0.91 0.06 0.08 0.84 1.00 2.00 Walk 18kg - 2.00 Jog -0.22 0.06 -3.46 0.011 0.09 0.06 1.43 0.87 0.05 0.07 0.80 1.00 -0.04 0.09 -0.47 1.00 2.00 Walk - 2.66 Run -0.46 0.05 -8.36 <0.01 -0.09 0.05 -1.79 0.64 -0.12 0.06 -2.16 0.37 -0.15 0.07 -2.02 0.46 2.00 Walk 9kg - 2.66 Run -0.46 0.06 -7.60 <0.01 -0.19 0.06 -3.21 0.03 -0.19 0.06 -3.11 0.04 0.02 0.08 0.22 1.00 2.00 Walk 18kg - 2.66 Run -0.36 0.07 -5.42 <0.01 -0.08 0.06 -1.30 0.93 -0.06 0.07 -0.88 1.00 -0.09 0.09 -1.00 0.99

124

Discussion This study compared GM activity across a range of locomotor behaviors, including walking while carrying a load and running. Our results support the hypothesis that the derived features of the human GM aid the resistance of rapid trunk pitch rates (H1), which include those experienced during high-speed running. Here, we found that maximal GM activity was significantly higher during running and jogging than at comparable walking speeds (H2), even while carrying heavy loads. While recent research has shown that sprinting is especially likely to require increased GM activity (Bartlett et al., 2014), even low speed jogging significantly increased GM EMG amplitude far beyond heavy load carrying at high walking speeds.

For other lower limb muscles, maximal muscle EMG amplitudes sampled in this study were not significantly altered by running (H3). However, lower limb muscle activity did increase in magnitude with locomotor speed regardless of gait type, similar to previous findings (Tsuji et al., 2012; Wall-Scheffler et al., 2010). These results highlight the novelty of the GM activity during running and support previous ER hypotheses.

As found previously (Lieberman et al., 2006), greater trunk pitch was associated with increased

GM magnitudes, in line with previous hypothesis that GM activity during endurance running is linked to stabilizing the trunk. Our results build on this previous work by showing that the relationship between trunk pitch and GM activation is maintained across a range of load-carrying behaviors. Thus, overall, our results support the hypothesis that enlargement of the GM during human evolution would have aided the adoption of ER behaviors (Bramble and Lieberman, 2004; Lieberman et al., 2006; Marzke et al., 1988). Although it is not possible to directly test the hypothesis that an enlarged GM is an adaptation for ER, our results add to the notion that this derived trait would have aided ER activity in fossil hominins. We also found that other common activities, such as walking while carrying weight, while challenging, would not have required muscle forces as high as those required during ER.

While our study provides support for the ER hypothesis, our experiments do have some limitations that form the foundation for future experimental studies of human GM activity. For example, our findings were focused on walking and running behaviors, and we cannot not rule out other activities that may require 125

trunk stabilization such as climbing, bending down, or traversing more difficult terrain. In addition, our study was conducted on a treadmill, and uneven terrain, or terrain with obstacles may generate increased trunk pitch requiring greater GM activation. While lateral stability is controlled by the gluteus medius and minimus (Soderberg and Dostal, 1978), likely due to the inherent coronal plane instability of bipedalism, frontal loading could provide a significant challenge to the GM on unstable ground or on hilly terrain. Thus, future loaded walking studies need to be conducted across complex terrain rather than homogenous pathways.

In addition, frontal carrying positions are not the only way individuals transport objects. While asymmetrical or head / back loading are less likely to increase trunk pitch rates they remain possible torso destabilizers. Further studies should examine the effects of other load carrying postures on GM activation during walking.

Finally, this work is predicated on the notion that higher levels of muscle activity may have been a selection pressure for increased muscle size across our evolutionary history. While plausible, this idea is difficult to test, and we will likely not be able to link changes in muscle morphology to the adoption of a single behavior during human evolution. Despite these limitations, our study suggests that increased GM

EMG amplitudes are linked to high-speed locomotor activities and not carrying behaviors. These results provide further support for the hypothesis that GM enlargement may have improved ER performance during human evolution.

Conclusions The findings of this study support previous research hypotheses linking trunk pitch rates and GM activity. Here it appears that the GM acts as a trunk stabilizer during rapid pitching accelerations which highest during running compared to other locomotor behaviors. Lower limb muscle activity is not significantly altered by load carrying or running specifically but appears to be dependent primarily upon locomotor speed. These data support the hypothesis that derived features of human GM anatomy are linked to running rather than walking activities and suggest that enlargement of the GM during human evolution may be associated with increased use of ER behaviors in a hunting and gathering lifestyle. 126

Acknowledgements We would like to thank all the subjects who agreed to participate in this study. Additionally, we would like to thank the University of Arizona Social and Behavior Science Research Institute for the dissertation research grant (#18DRF0885) which funded this study, and the School of Anthropology Haury

Dissertation Fellowship which supported the preparation of this manuscript.

127

References Aiello, L., Dean, C.D. (Ph, 1990. An Introduction to Human Evolutionary Anatomy. Academic Press.

Bartlett, J.L., Sumner, B., Ellis, R.G., Kram, R., 2014. Activity and Functions of the Human Gluteal Muscles in Walking, Running, Sprinting, and Climbing. Am. J. Phys. Anthropol. 153, 124–131. https://doi.org/10.1002/ajpa.22419

Basmajian, J.V., De Luca, C.J., 1985. Muscles alive: their functions revealed by electromyography. Williams & Wilkins.

Berecz, B., Cyrille, M., Casselbrant, U., Oleksak, S., Norholt, H., 2020. Carrying human infants – An evolutionary heritage. Infant Behavior and Development 60, 101460. https://doi.org/10.1016/j.infbeh.2020.101460

Birrell, S.A., Hooper, R.H., Haslam, R.A., 2007. The effect of military load carriage on ground reaction forces. Gait & Posture 26, 611–614. https://doi.org/10.1016/j.gaitpost.2006.12.008

Bramble, D., Carrier, D., 1983. Running and Breathing in Mammals. Science 219, 251–256. https://doi.org/10.1126/science.6849136

Bramble, D., Lieberman, D., 2004. Endurance running and the evolution of Homo. Nature 432, 345–352. https://doi.org/10.1038/nature03052

Carrier, D.R., 1984. The energetic paradox of human running and hominid evolution. Curr. Anthropol. 25, 483–495. https://doi.org/10.1086/203165

Cunningham, C.B., Schilling, N., Anders, C., Carrier, D.R., 2010. The influence of foot posture on the cost of transport in humans. Journal of Experimental Biology 213, 790–797. https://doi.org/10.1242/jeb.038984

Darwin, C., 1871. Descent of Man and Selection in Relation to Sex. Murray, London, England.

De Luca, C.J., Gilmore, L.D., Kuznetsov, M., Roy, S.H., 2010. Filtering the surface EMG signal: Movement artifact and baseline noise contamination. J Biomech 43, 1573–1579. https://doi.org/10.1016/j.jbiomech.2010.01.027

DeSilva, J.M., Holt, K.G., Churchill, S.E., Carlson, K.J., Walker, C.S., Zipfel, B., Berger, L.R., 2013. The Lower Limb and Mechanics of Walking in Australopithecus sediba. Science 340. https://doi.org/10.1126/science.1232999

Haeusler, M., 2002. New insights into the locomotion of Australopithecus africanus based on the pelvis. Evolutionary Anthropology: Issues, News, and Reviews 11, 53–57. https://doi.org/10.1002/evan.10056

Harcourt-Smith, W.E.H., Aiello, L.C., 2004. Fossils, feet and the evolution of human bipedal locomotion. J. Anat. 204, 403–416. https://doi.org/10.1111/j.0021-8782.2004.00296.x

Hora, M., Pontzer, H., Wall-Scheffler, C.M., Sládek, V., 2020. Dehydration and persistence hunting in Homo erectus. Journal of Human Evolution 138, 102682. https://doi.org/10.1016/j.jhevol.2019.102682 128

Liebenberg, L., 2008. The relevance of persistence hunting to human evolution. Journal of Human Evolution 55, 1156–1159. https://doi.org/10.1016/j.jhevol.2008.07.004

Lovejoy, C.O., 1988. Evolution of Human Walking. Scientific American 259, 118–125. https://doi.org/10.1038/scientificamerican1188-118

Marzke, M.W., Longhill, J.M., Rasmussen, S.A., 1988. Gluteus maximus muscle function and the origin of hominid bipedality. American Journal of Physical Anthropology 77, 519–528. https://doi.org/10.1002/ajpa.1330770412

Neumann, D.A., Cook, T.M., 1985. Effect of Load and Carrying Position on the Electromyographic Activity of the Gluteus Medius Muscle During Walking. Physical Therapy 65, 305–311.

Pontzer, H., 2017. Economy and Endurance in Human Evolution. Current Biology 27, R613–R621. https://doi.org/10.1016/j.cub.2017.05.031

Rahnama, N., Lees, A., Reilly, T., 2006. Electromyography of selected lower-limb muscles fatigued by exercise at the intensity of soccer match-play. Journal of Electromyography and Kinesiology 16, 257–263. https://doi.org/10.1016/j.jelekin.2005.07.011

Soderberg, G.L., Dostal, W.F., 1978. Electromyographic Study of Three Parts of the Gluteus Medius Muscle During Functional Activities. Phys Ther 58, 691–696. https://doi.org/10.1093/ptj/58.6.691

Stern, J.T., 1972. Anatomical and functional specializations of the human gluteus maximus. Am. J. Phys. Anthropol. 36, 315–339. https://doi.org/10.1002/ajpa.1330360303

Stern, J.T., Paré, E.B., Schwartz, J.M., 1980. New perspectives on muscle use during locomotion: electromyographic studies of rapid and complex behaviors. J Am Osteopath Assoc 80, 287–291.

Tsuji, K., Soda, N., Okada, N., Ueki, T., Oba, K., Ikedo, Y., Imaizumi, H., 2012. A comparison of the lower limb muscles activities between walking and jogging performed at the same speed. Journal of Physical Therapy Science 24, 23–26.

Wall-Scheffler, C.M., Chumanov, E., Steudel-Numbers, K., Heiderscheit, B., 2010. EMG activity across gait and incline: The impact of muscular activity on human morphology. Am J Phys Anthropol 143, 601–611. https://doi.org/10.1002/ajpa.21356

Ward, C.V., 2002. Interpreting the posture and locomotion of Australopithecus afarensis: Where do we stand? Am. J. Phys. Anthropol. 119, 185–215. https://doi.org/10.1002/ajpa.10185 129

Webber, J.T., Raichlen, D.A., 2013. Heel-strike and impact transient during bipedal walking: Implications for the acquisition of a habitual bipedal gait. Am. J. Phys. Anthropol. 150, 287–287.

Zijlstra, W., 2004. Assessment of spatio-temporal parameters during unconstrained walking. European Journal of Applied Physiology 92, 39–44. https://doi.org/10.1007/s00421-004-1041-5

Zimmermann, C.L., Cook, T.M., Bravard, M.S., Hansen, M.M., Honomichl, R.T., Karns, S.T., Lammers, M.A., Steele, S.A., Yunker, L.K., Zebrowski, R.M., 1994. Effects of Stair-Stepping Exercise Direction and Cadence on EMG Activity of Selected Lower Extremity Muscle Groups. J Orthop Sports Phys Ther 19, 173–180. https://doi.org/10.2519/jospt.1994.19.3.173

130

APPENDIX D: HOMININ SKELETAL MORPHOLOGY SUPPLEMENT

Beginning with the lower limb, from the feet to the pelvis, morphology of australopithecines differ from that of living great apes in ways that enhance bipedal walking capabilities. Aside from adult gorillas, the extant great apes are largely arboreal and possess skeletal morphology reflective of this locomotor behavior (Larson, 2009; Paciulli, 1995; Pontzer and Wrangham, 2004; Richmond, 2007), some of which is also present in early human ancestors

(Berge, 1994; Dart, 1925; Jungers, 1982; Stern and Susman, 1983). Shorter and flexed hindlimbs with mobile ankles and feet, long forelimbs and carpal phalanges, mobile shoulder joints, and a strong and stable trunk are skeletal indicators of arboreality, many of which reduce bipedal locomotor efficiency (Latimer, 1991; Susman et al., 1984). Features related to arboreal life are present in the australopithecines suggesting some reliance on arboreality, yet the lower limb morphology of the australopithecines, specifically the pelvic girdle and feet, suggests that they were proficient bipedal walkers (Berge, 1994; Jungers, 1982; McHenry and Coffing, 2000).

Starting with the feet, extant apes have curved phalanges which reflect suspensory or climbing behaviors (Burgess and Ruff, 2015; Richmond, 2000; Richmond, 2007). As the hands and feet may be well adapted to the shape of the substrate an organism travels on, curvature in australopithecine hand and feet bones likely reflects arboreal behaviors (Stern and Susman, 1983).

However, derived pedal features appear with the emergence of members of the genus Homo which contrast with the flexible feet of the australopithecines. In H. sapiens, the foot is rigid, flat, and typically does not demonstrate a midtarsal break (dorsiflexion of the midfoot) during walking

(DeSilva, 2010). The medial and transverse arches of the foot create curvature in the foot and combine to make an exceptionally ridged structure (Venkadesan et al., 2020), useful for push off during walking (i.e., the windlass mechanism). While the human foot is more rigid than in extant 131 apes, the arches of the foot can be compressed in humans (DeSilva, 2010), which has been shown to actually improve running performance (Holowka and Lieberman, 2018) possibly suggesting competing selective pressures between walking and running.

A range of pedal morphologies have been described for australopithecines (primarily A. afarensis), featuring a mixture of primitive and modern features. The A. afarensis remains from

Hadar has been described as having feet that show adaptation for arboreality (Susman et al., 1984) to the possible detriment of their walking gaits. A. afarensis have long, curved phalanges suggesting a life in the trees and appear to be smaller bodied, which could reflect a shift in locomotor environments later in hominin evolution similar to how gorillas and chimps spend more time in the trees early in their lives (Burgess and Ruff, 2015). Others have argued that presence of curved phalanges could be indicative of a difference in the locomotor behavior between the sexes

(Susman et al., 1984). Short toes are especially important to reduce pedal stress during running and appear only later in the genus Homo (Rolian et al., 2009), suggesting this high-speed activity may not have been important early in our evolution. The australopithecine species also possess adducted first pedal phalanges (Ward, 2002) and long rigid feet that improve bipedal walking economy (Stern and Susman, 1983; Webber and Raichlen, 2016). These adaptations appear over time in a mosaic fashion, with some researchers suggesting that australopithecine feet even had some degree of hallux abduction (Berillon, 1999) to improve grasping or climbing capabilities.

The lower appendicular skeleton of the australopithecines appear to be well adapted to bipedal locomotion (Berge, 1994; Foster et al., 2013; Sylvester et al., 2011). The morphology of the australopithecine tibia suggests their feet aligned were directly below the knee joint (Stern and

Susman, 1983; Ward et al., 1999), allowing for greater stability during locomotion. Accompanying a flat tibial plateau is the development of a femoral bicondylar angle, the angle between the distal 132 head of the femur and the shaft, which helps to center the stance leg below the walkers center of gravity (Tardieu and Trinkaus, 1994). The australopithecines share this knee morphology with humans marking them as bipeds (Shefelbine et al., 2002). Relatedly, the femoral neck must support the weight of the body during bipedal locomotion (Ruff, 2003b). This femoral neck stress generates a marked pattern of cortical bone adaptation which is present in australopith remains

(Ohman et al., 1997). The acetabulum, the pelvic socket with which the femoral head articulates, is also more robust than one would predict for non-biped in the australopithecines (Berger et al.,

2010), indicating two-legged locomotion.

Chimpanzees walk with flexed limbs when bipedal, and this posture has been shown to entail higher locomotor costs, via the activation of hamstrings muscles to counteract limb collapse at the hip, when compared to the extended limbs used by humans (Cunningham et al., 2010; Foster et al., 2013; Raichlen et al., 2010; Sockol et al., 2007; Steudel-Numbers and Tilkens, 2004;

Steudel-Numbers et al., 2007; Webber and Raichlen, 2016). However, flexed limbs are useful for clinging to circular and vertical substrates (Gebo, 1992). Preserved footprints associated with A. afarensis suggest that early australopithecines were using an extended limb with an accompanying heel-strike as far back as 3.664 million years ago (Raichlen et al., 2010), marking their bipedal locomotion strikingly modern, and supporting the interpretations of calcaneal morphology

(Latimer and Lovejoy, 1989). Elongated lower limbs reduce the energy costs per unit mass of walking and running in mammals, including humans (Kramer and Eck, 2000; Pontzer, 2007;

Steudel-Numbers and Tilkens, 2004; Steudel-Numbers et al., 2007), and it appears this increase in locomotor economy was important during the evolution of early Homo. H. erectus (2.0 MA)

(Herries et al., 2020) has especially long lower limbs, which have been suggested to have reduced the cost of walking by nearly 50% compared to A. afarensis (Steudel-Numbers, 2006). Fossils 133 from Dmanisi (1.8 MA) demonstrate that early members of the genus Homo, even outside of Africa, possessed human-like, long limb proportions, with only a slightly smaller tibia than that seen in modern humans (Lordkipanidze et al., 2007; Pontzer et al., 2010). However, the earliest member of the genus Homo, H. habilis, has been suggested to have more primitive limb proportions

(Haeusler and McHenry, 2004; Ruff, 2009), which has led it to be attributed to the australopithecine clade occasionally even though they may have had slightly larger brain cases and were likely tool makers (Tobias, 1965).

Where the australopithecine lower limb joints appear to be adapted to bipedal walking, members of the genus Homo have significantly larger lower limb joint surface areas than the extant great apes or australopithecines (Jungers, 1988). Large joint surface areas have been suggested to function as a means to dissipate large or repetitive impact forces (Jungers, 1988), especially those generated from activities like endurance running that lead to large ground reaction forces (Bramble and Lieberman, 2004). A. afarensis had some enlargement of the joint surface areas (Jungers,

1982), suggesting some adaptation toward habitual bipedalism, but it is not until Homo erectus that we see significant enlargement across the lower limb (Bramble and Lieberman, 2004; Walker and Leakey, 1993). The increased joint robusticity is also found in the Dmanisi skeletal remains

(Lordkipanidze et al., 2007). H. habilis however, seems to have possessed smaller lower limb joints (Berger et al., 2010), although the lower limb remains of this species are not well preserved.

The calcaneus, the heel bone of the foot, is significantly more robust in humans than in extant apes, likely in order to tolerate large impact forces at landing (Holowka and Lieberman, 2018; Light and

Mclellan, 1977). The calcaneus is similarly hardy in A. afarensis (Latimer and Lovejoy, 1989).

Altogether, aspects of the australopithecine foot and lower limb suggest adaptation to both heel- 134 strike bipedalism (Foster et al., 2013; Raichlen et al., 2010) and arboreality (Latimer, 1991;

Susman et al., 1984).

The pelvis of the australopithecines also shows piecewise accumulation of traits that aid both bipedalism and climbing behaviors (Haeusler, 2002; Hogervorst et al., 2009). Extant apes have pelves with long iliac blades that end near the lower ribs, creating an inflexible body suited for climbing (Hogervorst et al., 2009). The australopithecines, however, appear to have enlarged gluteal muscle attachment sites to allow for the strong limb extensions required for energetically economical bipedal gaits (Berge, 1994; Hogervorst et al., 2009). Yet, the australopithecine pelvic shape is intermediate between the ape morphology and the human pelvic shape where the iliac blades are much shorter and wrapped around anteriorly (Stern and Susman, 1983; Susman et al.,

1984), resulting in an overall wider and shorter pelvis (Gruss and Schmitt, 2015). Humans have a unique pelvic configuration which is often described as short, wide, and curved (Hogervorst et al.,

2009). The derived pelvic shape creates ample attachment area for the strong gluteal muscles that help keep the body upright and combat trunk pitching forces that arise from running gaits (Aiello and Dean, 1990; Lieberman et al., 2006; Stern, 1972). Researchers have linked high trunk pitch rates to high-speed locomotor activities and climbing (Lieberman et al., 2006; Stern, 1972), but not to lower speed activities such as walking where the gluteal muscles are far less active.

The lumbar spine of the australopithecines are missing some of the hallmark morphologies thought to be related to high-speed bipedalism including large surface areas compared to the thoracic and cervical spine which are present in members of the genus Homo (Shapiro, 1993).

Furthermore, the narrow waist of the H. erectus KNM-WT 15000 juvenile skeleton (Walker and

Leakey, 1993) may have aided endurance running specifically by allowing counterrotation of the upper and lower body and easier placement of the foot below the center of mass (Thompson et al., 135

2015). Yet, recent work on a wide female H. erectus pelvis suggests that selection for narrow hips due to endurance running may not be ubiquitous within the species, but rather sexually dimorphic via the of challenges presented by giving birth to large-brained offspring (Simpson et al., 2008).

Due to the unique features of the australopithecine pelves, researchers have argued that A. afarensis would have used a unique form of bipedalism, where a wide pelvis could have helped reduce perturbations to the center of mass, important for walking economy (Crowe et al., 1995;

Lee and Farley, 1998). Therefore, the derived narrow pelvic width in humans may be the product of alternative selective pressures (Rak, 1991). The narrow human pelvic width is conspicuous considering the difficulties of human childbirth (Hogervorst et al., 2009; LaVelle, 1995), which led to the obstetric dilemma hypothesis (Wittman and Wall, 2007) where the competing selective pressures of energetically efficient bipedal locomotion and safe childbirth would have both been at play during hominin evolution (Kurki, 2011; Wells et al., 2012).

Together, the fossil remains of the lower limb and pelvis of the australopithecines paint a picture of mosaic collection of bipedal and arboreal morphologies. While these early hominins were habitually bipedal, the still retained many skeletal morphologies indicative of a life in the trees. Given the increased locomotor economy of an extended hip and knee during bipedal walking compared to quadrupedalism seen in our last common ancestor (Foster et al., 2013; Sockol et al.,

2007), it would seem that the australopithecines relied on both terrestrial bipedalism and arboreal locomotion. Selective pressures for efficient terrestrial locomotion among australopithecines have not been argued to have been related to more time spent in terrestrial locomotion or longer daily ranges compared to extant apes. Instead, increased energy demands from pregnancy or reduced food quality due to loss of forest fruits could have initiated a more efficient use of their mobility.

For instance, chimpanzees often participate in long periods of travel during territory patrolling that 136 likely costs them considerable amounts of energy when compared to typical foraging (Amsler,

2010). If these behaviors were swapped for a more efficient mode of travel (extended knee and hip bipedalism for example), in the face of new food foraging, little could change from typical primate behavior and time budgets aside from a reduction in locomotor costs.

The musculoskeletal morphology of the australopithecine upper body tells a different story, with clear adaptations for climbing and arboreality, resembling morphologies in extant primates

(Green and Alemseged, 2012). These features are thought to negatively affect running but have little negative effects on walking (Bramble and Lieberman, 2004). These upper body adaptations include cranially oriented shoulder joints, a cone shaped trunk, long forearms and long forelimbs in relation to hindlimbs (Churchill et al., 2013; Green and Alemseged, 2012; Latimer, 1991;

Ricklan, 1987).

The scapula articulates with the humerus creating the shoulder joint, and its morphology is often tied to arboreal behaviors in primates (Ankel-Simons, 2010). In primates this joint in oriented superiorly to aid in overhand climbing (Ankel-Simons, 2010; Green and Alemseged, 2012), and the scapulae of A. afarensis appears more like those of African apes than those of humans (Green and Alemseged, 2012). A. sediba and A. africanus also share the cranially oriented glenoid fossa, the cuplike articular surface of the humerus and scapula, further establishing australopithecines as often using arboreal locomotor modes (Berger et al., 2010). The earliest members of the genus

Homo, H. habilis, retain these ape-like shoulders for climbing with a superiorly oriented glenoid fossas (McHenry and Coffing, 2000). The juvenile KNM-WT 15000 H. erectus, however, does have lower, wider, and inferiorly pointed shoulder joints (Bramble and Lieberman, 2004; Walker and Leakey, 1993). This derived shoulder orientation has been suggested to aid in balancing, especially of the head, during running behaviors (Bramble and Lieberman, 2004; Lieberman, 137

2011), and would have reduced climbing capacity. Similarly, modern human shoulder joints are not oriented superiorly (Larson, 2009), but because the forelimbs do not support the body during bipedal locomotion this does not impact locomotor economy (Ward, 2002).

Connecting the shoulders and arms to the derived pelvis in members of the genus Homo is a unique barrel-shaped trunk (McHenry and Coffing, 2000). A separation of the pelvis and the upper body allows for independent counter rotations of the upper and lower body (Preece et al.,

2016). During running this allows the body to resist rotation during the aerial phase where the momentum of the legs would cause rotation when there was no contact with the ground (Bramble and Lieberman, 2004) by rotating the torso opposite to the rotation of the hips. KNM-WT 15000

H. erectus has a narrow pelvis and chest that are separated by a narrow waist (Walker and Leakey,

1993), differentiating it convincingly from the strong and connected trunk and pelvis of climbing apes (Rose, 1991). The australopithecines possess a trunk shaped more like a funnel than the barrel-shaped chest of modern humans (McHenry and Coffing, 2000). The narrow shoulder and wide pelvis of the australopithecines likely aids arboreal locomotor modes by helping to resist bending loads during vertical climbing (Ward, 1993). A. sediba, A. afarensis and A. africanus all share the funnel shaped thorax which does not allow for the counterrotation of the hips and shoulders seen in the genus Homo (McHenry and Coffing, 2000; Schmid et al., 2013).

In addition to shoulder morphology to support climbing activities, the australopithecines share limb proportions that suggest they were still committed to climbing (Ruff et al., 2016). Long forelimbs aid during brachiation and climbing (Green and Alemseged, 2012). A. afarensis ulnar/femoral index (ratio of the length of the ulna divided by the length of the femur) has been estimated to be quite high, resembling chimpanzees (Kimbel et al., 1994). A. garhi also appears to be adapted for given their long forearms (Asfaw et al., 1999). A. sediba skeletons also retain 138 primitive forelimb proportions (Churchill et al., 2013). Short lower limbs and long upper limbs are thought to increase climbing efficiency but the tradeoff in arm length between climbing and bipedal locomotor efficiency is debatable (Kozma et al., 2016; Kozma et al., 2018). Shorter forearm should help reduce the energy cost of arm swing especially during running where the arms are held at 90 degrees (Bramble and Lieberman, 2004), at the cost of climbing ability. Mirroring their shoulder morphology, H. habilis has elongated forearms, more similar to apes (Haeusler and

McHenry, 2007). Forearm sizes are not well documented in H. erectus, but modern humans possess much smaller forearms than chimpanzees and the australopithecines in relation to body size (Zihlman and Brunker, 1979), which differ from the specialized elongated hindlimbs (Steudel-

Numbers et al., 2007).

Finally, moving to the head, inner ear morphology has also been tied to high-speed locomotor activities (Spoor, 2003; Spoor and Zonneveld, 1998; Spoor et al., 1994). The semicircular canals are responsible for feeding information to the brain about head movement, and in conjunction with the vestibulo-ocular reflex, coordinate eye movement to focus on targets while the head is moving (Cox and Jeffery, 2010; Hadžiselimović and Savković, 1964; Jones and Spells,

1963; Oman et al., 1987). In extant humans, long distance running represents an activity which produces repetitive high head pitch velocities (Atkin and Bender, 1968; Cromwell et al., 2001).

The semi-circular canals of australopithecines have relatively small diameters compared to extant humans, and are similar in size to extant apes (Spoor et al., 1994). Small diameter sizes have been hypothesized to be less sensitive to head motion during highly agile activities including high-speed climbing or running (Bramble and Lieberman, 2004; Cox and Jeffery, 2010; Spoor et al., 1994;

Spoor et al., 2007). The semi-circular canal diameters in H. erectus are relatively large compared to both the australopithecines and extant apes (Spoor, 2003; Spoor and Zonneveld, 1998; Spoor et 139 al., 1994). Large canal diameters have been interpreted as adaptations to running behaviors which appear with later members of the genus Homo but not within the australopithecines (Bramble and

Lieberman, 2004).

Thus, the australopithecines all appear to have multiple ancestral skeletal structures which would have been advantageous for climbing, but disadvantageous for endurance running. The mixed capacities efficiencies in the trees or on the ground follows hypotheses suggesting that locomotor economy was required to offset reduced food quality or availability but safety for feeding in the forest was still an important aspect of their lives. Tree living must have generated considerable selective pressure for all australopithecines to retain climbing structures at the same time as they evolved lower body adaptations for bipedal locomotion. Adaptations that aid longer distance or endurance walking behaviors could have been added piecewise to continually ratchet up or specialize walking abilities. It has been suggested that the australopithecines could not have been hunter-gathers given their arboreal nature (Latimer, 1991). However, the australopithecines appear to have been subject to competing selective pressures for terrestriality and arboreality, resulting in the mosaic skeletal structures.