Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-26T08:48:01.615Z Has data issue: false hasContentIssue false

Variation, mosaicism and degeneracy in the hominin foot

Published online by Cambridge University Press:  27 December 2021

J. McClymont
Affiliation:
University of Liverpool, Liverpool, UK
K. Davids
Affiliation:
Sheffield Hallam University, Sheffield, UK
R.H. Crompton*
Affiliation:
University of Liverpool, Liverpool, UK
*
*Corresponding author. E-mail: robinhuwcrompton@gmail.com

Abstract

The fossil record is scarce and incomplete by nature. Animals and ecological processes devour soft tissue and important bony details over time and, when the dust settles, we are faced with a patchy record full of variation. Fossil taxa are usually defined by craniodental characteristics, so unless postcranial bones are found associated with a skull, assignment to taxon is unstable. Naming a locomotor category based on fossil bone morphology by analogy to living hominoids is not uncommon, and when no single locomotor label fits, postcrania are often described as exhibiting a ‘mosaic’ of traits. Here, we contend that the unavoidable variation that characterises the fossil record can be described far more rigorously based on extensive work in human neurobiology and neuroanatomy, movement sciences and motor control and biomechanics research. In neurobiology, degeneracy is a natural mechanism of adaptation allowing system elements that are structurally different to perform the same function. This concept differs from redundancy as understood in engineering, where the same function is performed by identical elements. Assuming degeneracy, structurally different elements are able to produce different outputs in a range of environmental contexts, favouring ecological robusticity by enabling adaptations. Furthermore, as degeneracy extends to genome level, genetic variation is sustained, so that genes which might benefit an organism in a different environment remain part of the genome, favouring species’ evolvability.

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Social media summary: Limb-bone variation is explicable by the recombination of a set of bones to produce different outputs in each activity.

1. Introduction

Walking – as with all biological actions – is characterised by functional variability (Arutyunyan et al., Reference Arutyunyan, Gurfinkel and Mirskii1968; Davids et al., Reference Davids, Glazier, Araujo and Bartlett2003). In the living great apes and by extension in our fossil ancestors, a variable array of locomotor behaviour is evident, from bipedal walking on the ground and in trees, to swinging, leaping, vertical climbing, knucklewalking and more. While our habitual locomotor mode is bipedal, we have the ability to perform all of the above-mentioned behaviours: while most of us would fail in an attempt to brachiate on a ‘jungle gym’, consider a parkour athlete or gymnast, or a human baby's ontogenetic climbing phase. Equally, many of us might have seen the widely available video footage of Gorilla gorilla casually standing or walking upright. Not only is there high inter-species variability in locomotor mode, but inter- and-intra-individual variability in extant and extinct great apes is also staggeringly high. Despite the omnipresence of this natural, functional feature of movement, palaeoanthropology lacks a strong theoretical framework anchored in biomechanics, or complex-adaptive-systems biology, from which to interpret variability. As a consequence, a long-running debate regarding the significance of the taxonomic and morphological variability in the fossil record has ensued (Wood and Boyle, Reference Wood and Boyle2016). Calls to further understand variation in locomotion in extant great apes can no longer be ignored (Crompton et al., Reference Crompton, Li, Thorpe, Wang, Savage, Payne and Declerq2003; Alexander, Reference Alexander2013; D'Août & Aerts, 2008; Carlson et al., Reference Carlson, Stout, Jashashvili, De Ruiter, Tafforeau, Carlson and Berger2011; Neufuss et al., Reference Neufuss, Hesse, Thorpe, Vereecke, D'Aout, Fischer and Schilling2014; McClymont et al., Reference McClymont, Pataky, Crompton, Savage and Bates2016; McClymont & Crompton, Reference McClymont and Crompton2021).

The phenotypic morphology of bones reflects habitual movement patterns practised during life (Bock, Reference Bock1965), and this relationship between movement and bone shape is a fundamental interpretive paradigm in bioarchaeology and palaeoanthropology (Jungers and Minns, Reference Jungers and Minns1979; Trinkaus & Ruff, Reference Trinkaus and Ruff1999; MacLatchy et al., Reference MacLatchy, Gebo, Kityo and Pilbeam2000; Madar et al., Reference Madar, Rose, Kelley, MacLatchy and Pilbeam2002; Ruff, Reference Ruff2002; Ruff et al., Reference Ruff, Holt and Trinkaus2006; Boyle et al., Reference Boyle, McNutt, Sasaki, Suwa, Zipfel and DeSilva2018). Fossil hand and foot bones are rare, but they can be useful for interpreting the evolution of locomotion as they are the primary biomechanical unit to interact with the environment (reviewed e.g. in Klenerman and Wood, Reference Klenerman and Wood2006; D'Août and Aerts, Reference D'Août and Aerts2008; Stolwijk et al., Reference Stolwijk, Duysens, Louwerens, van de Ven and Keijsers2013; Vereecke et al., Reference Vereecke, Van Sint Jan, D'Août, Lescrenier, Van Gheluwe, De Clercq and D'Aout2008). Analysis of bone shape in isolation, however, does not definitively test behaviour or locomotor mode, as relative contributions of soft tissues, relationships between applied forces and the dynamics of the system cannot be accounted for. Given the truly fragmentary nature of the fossil record, it is not uncommon to find that only one skeletal element is available to characterise taxa and locomotor behaviours. More often than not the variability and overlap in bone shape between taxa are noted but is not elaborated on.

The current tradition is that fossil foot elements represent a ‘mosaic’ picture of foot evolution from 7 million years ago (Ma) to the present, enabling locomotor behaviour in both terrestrial and arboreal environments (Zipfel et al., Reference Zipfel, DeSilva, Kidd, Carlson, Churchill and Berger2011; Haile-Selassie et al., Reference Haile-Selassie, Saylor, Deino, Levin, Alene and Latimer2012; DeSilva et al., Reference DeSilva, Holt, Churchill, Carlson, Walker, Zipfel and Berger2013). Complex palaeoenvironments would exert selective pressure for locomotor plasticity to exploit varied, unstable and rapidly changing microhabitats, with hominids displaying a combination of plesiomorphic and apomorphic characteristics (Senut et al., Reference Senut, Pickford, Gommery, Mein, Cheboi and Coppens2001; Lovejoy et al., Reference Lovejoy, Latimer, Suwa, Asfaw and White2009a, Reference Lovejoy, Suwa, Simpson, Matternes and Whiteb). As the fossil record has expanded, author interpretations have uncovered functional overlap in the foot extending from the early Pliocene (circa 4.4 Ma) to the late Miocene (circa 7 Ma), reflecting this apparent plasticity and diversity in locomotor behaviour.

Plasticity hypotheses are long established in evolutionary biology (Via & Lande Reference Via and Lande1985; Schlichting & Pigliucchi Reference Schlichting and Pigliucci1993; Stearns, Reference Stearns1989; Odling-Smee & Braithwaite, Reference Odling-Smee and Braithwaite2003; Laland & Sterelny, Reference Laland and Sterelny2006; Pigliucci, Reference Pigliucci2009; Pigliucci & Müller, Reference Pigliucci and Müller2010; Danchin et al., Reference Danchin, Charmantier, Champagne, Mesoudi, Pujol and Blanchet2011; Laland et al., Reference Laland, Uller, Feldman, Sterelny, Müller, Moczek and Odling-Smee2015) but not in hominin palaeontology, owing probably to the contention over the role that plasticity plays through phenotypic and genetic accommodation (Pfennig and McGee, Reference Pfennig and McGee2010; Moczek et al., Reference Moczek, Sultan, Foster, Ledón-Rettig, Dworkin, Nijhout and Pfennig2011), i.e. in palaeoanthropology the adaptation of parts in response to environmental constraints is independent of genetics. However, plasticity advances diversity in niche construction in unique environments (Odling-Smee & Braithwaite, Reference Odling-Smee and Braithwaite2003) and encourages population-level connectivity and gene flow (Crispo & Chapman, Reference Crispo and Chapman2008). It increases the probability of shifts in adaptive peaks, radiations and speciation events (Price, Reference Price2005; Lande, Reference Lande2009), contributing to the obvious spatio-temporal variation in selection parameters (Huey et al., Reference Huey, Hertz and Sinervo2003; Duckworth, Reference Duckworth2009; Cornwallis & Uller, Reference Cornwallis and Uller2010). In a review on environmental constraints that shape human life-history variation, Kuzawa and Bragg (Reference Kuzawa and Bragg2012) observed that many of the life history traits they examined (including low birth rate, delayed maturity and high fertility), exhibited high phenotypic variation stemming from developmental and behavioural plasticity. These traits were in response to environmental factors such as accidental death or nutrition stress. While the idea of locomotor plasticity has been touched on in the palaeontology literature (Venkataraman et al., Reference Venkataraman, Kraft, DeSilva and Dominy2013a, Reference Venkataraman, Kraft and Dominyb; Boyle et al., Reference Boyle, McNutt, Sasaki, Suwa, Zipfel and DeSilva2018; Crompton et al., Reference Crompton, McClymont, Elton, Thorpe, Sellers, Heaton, Pickering and Clarke2021; McClymont & Crompton, Reference McClymont and Crompton2021), we believe that future studies regarding variation could be firmly conceptualised on the theoretical paradigm of degeneracy, which we elucidate in this position paper.

2. Functional redundancy and degeneracy

In 1962, an English translation of a 1933 Russian volume by influential movement scientist Nikolai Bernstein was published. He began with the observation that many more kinematic degrees of freedom existed in the locomotor system than were required to perform its habitual activities: in other words, the same motion could be achieved with much less complexity of joint arrangement. This was referred to as ‘redundancy’ after engineering design, where potential failure of individual elements is often offset by inclusion of duplicate elements which are ‘redundant’, unless failure occurs elsewhere. The hands and feet provide an excellent example of this, together containing more than 50 bones. The joints between them are complex and multifaceted, crossed by dozens of ligaments and tendons. They are, therefore, typified by an excess of degrees of freedom, or potential ways that joints can interact to produce the appropriate motion for each step. However, unlike redundancy in engineering, in biological systems, elements are structurally different, and can perform the same function. They can also form different combinations, underlying different functions (Tononi et al., Reference Tononi, Sporns and Edelman1999). Such systems comprising multifunctional elements are thus described as ‘degenerate’: systems may thus be characterised by low or high degeneracy.

What is degeneracy?

Unlike redundant systems, degenerate components can produce different outputs while satisfying different performance and environmental constraints (Edelman & Gally, Reference Edelman and Gally2001). A degenerate system can vary the way that different components produce the same functional output and is highly adaptive in response to unpredictable changes in the dynamic environmental conditions underpinning movement. Degeneracy is an inseparable characteristic of biological systems and is a direct consequence of natural selection (Whitaker & Bender, Reference Whitaker and Bender2009). Degeneracy operates from the molecular (McClellan, Reference McClellan2000) to the gene network level (Dudkiewicz et al., Reference Dudkiewicz, Mackiewicz, Nowicka, Kowalczuk, Mackiewicz, Polak and Cebrat2005) and is a primary property of neural networks (Tononi et al., Reference Tononi, Sporns and Edelman1999) and immune system response (Edelman, Reference Edelman1974).

It is fundamental to understanding movement coordination and its acquisition (Chow et al., Reference Chow, Davids, Button, Rein, Hristovski and Koh2009; Davids and Glazier, Reference Davids and Glazier2010; Seifert et al., Reference Seifert, Komar, Araujo and Davids2016), promoting flexibility and stability during complex motor learning (Komar et al., Reference Komar, Chow, Chollet and Seifert2015), and is thus a key property of functional adaptations to tasks and environments. In the domain of movement, degeneracy supports a neurobiological system to organise highly varied movement behaviours, without compromising the original function of the skeletal structure (Edelman & Gally, Reference Edelman and Gally2001; Price & Friston, Reference Price and Friston2002; Mason, Reference Mason2010).

We can illustrate degeneracy in modern humans with reference to the ideas of DeSilva (Reference DeSilva2009). In this paper, data from chimpanzee and human distal tibial morphology was presented to argue that human morphology could not sustain sufficient dorsiflexion to allow chimpanzee-like vertical climbing. A later and largely ecomorphology focussed study found that indigenous human arboreal foragers do produce chimpanzee-like kinematics in vertical climbing (Venkataraman et al., Reference Venkataraman, Kraft, DeSilva and Dominy2013a, Reference Venkataraman, Kraft and Dominyb). Subsequently, Venkataraman and DeSilva combined their individual approaches with field ultrasound techniques, establishing that changes in fibre length of gastrocnemius in habitual arboreal foragers adequately offset any derived features of the ankle associated with bipedalism (Venkataraman et al., Reference Venkataraman, Kraft and Dominy2013b). We argue that the range of gastrocnemius fibre length provides evidence of degeneracy in ourselves. Myatt et al. (Reference Myatt, Crompton and Thorpe2011, Reference Myatt, Crompton, Payne-Davis, Vereecke, Isler, Savage and Thorpe2012) reported another example, demonstrating that the ranges of muscle cross-sectional area and fibre lengths of great apes, in general, overlap considerably with each other, implying that their length/tension and torque/joint angle capacities also overlap, consistent with degenerate function in hominoids as a whole. Amongst the many sources of variation, Boyle et al. (Reference Boyle, McNutt, Sasaki, Suwa, Zipfel and DeSilva2018) noted the well-established contribution of muscles lost in most individuals of living species to intra-species variation. It remains to be shown, however, what genetic and/or developmental mechanisms drive this and other sources of variation.

Next, we contextualise mosaicism in reference to fossil feet and footprints, with specific reference to the way variance and invariance are interpreted in evolutionary biomechanics. This outline is followed by a discussion of the role functional variability plays in locomotion, and finally we discuss the relationship of degeneracy to evolution and adaptation. We do not wish to devalue any previous locomotor assumptions that have accompanied interpretations of fossil bone morphology, but rather to suggest that the degeneracy framework would provide more robust interpretation of observed variance, and of any locomotor assumptions, supported by palaeoenvironmental data and the ecomorphology framework (Wainwright, Reference Wainwright1991).

3. Mosaicism

Mosaicism is a common term in palaeoanthropology, first introduced in reference to Archaeopteryx (de Beer, Reference de Beer1954). It is applied to all anatomical regions (e.g. in the recent discussion of the Homo longi skull from Harbin (Ji et al., Reference Ji, Wu, Ji, Li and Ni2021) which is described as having: ‘a mosaic combination of plesiomorphic and apomorphic features’ (Ji et al., Reference Ji, Wu, Ji, Li and Ni2021, p. 1)). One of the earliest mentions of mosaicism in human evolution was by Day and Napier (Reference Day and Napier1964), referring to the ‘Homo habilis’ OH8 foot bones and OH7 hand bones from Olduvai Bed 1. Oxnard and Lisowski (Reference Oxnard and Lisowski1980) disputed the conclusion of Day and Wood (Reference Day and Wood1968) that the OH8 ‘Homo habilis’ foot possessed human-like arches, and belonged to a biped, if not a striding biped, like us. They argued that the articular surfaces of the bones suggested that an arch was absent. Later, Kidd et al. (Reference Kidd, O'Higgins and Oxnard1996) used the term mosaic, specifically to refer to function of the OH8 foot evidenced by multivariate analyses of ‘biomechanically relevant features’ (Kidd et al., Reference Kidd, O'Higgins and Oxnard1996, p. 269). Discussions surrounding the Australopithecus sediba, and the much later Homo naledi feet, make extensive use of the term mosaicism, suggesting the individual may have practised a ‘unique form of bipedalism with some degree of arboreality’ (Zipfel et al Reference Zipfel, DeSilva, Kidd, Carlson, Churchill and Berger2011, p. 1417). For the foot of Homo naledi, Harcourt-Smith et al. (2015, p. 1) state that it is ‘a unique mosaic previously unknown in the human fossil record’.

This tradition seems to combine uses of mosaicism to describe a combination of different functional features or adaptations. For the A. sediba hand, Kivell et al. (Reference Kivell, Kibii, Churchill, Schmid and Berger2011) continue the tradition of functional mosaicism between features which could be seen as adaptive for arboreal locomotion (such as curved digits) and features which might be seen as adaptive for a precision grip and perhaps toolmaking, such as shorter fingers and longer thumb. They make brief mention of the much earlier StW573, which also combines these manual features. Kivell (Reference Kivell2015), while not using the term mosaicism, argues that the H. naledi hand shows yet another distinct combination of morphological features not yet known in any other hominin.

In the above, joint shape and bone proportions are regarded as crucial evidence for function in both the hands and feet. Particularly in more recent papers, these anatomical features are held to indicate differences in bipedalism and most often differences in arboreal vs. terrestrial adaptation. There is an interplay between perceived locomotor similarity to humans in some features, but dissimilarity in others, and the concept that mosaicism exists in the degree of ‘hominisation’, and the extent to which features are plesiomorphic or apomorphic. In a helpful review of mosaicism, Parravicini and Pievani (Reference Parravicini and Pievani2019) acknowledged this interplay by recognising that their ‘Mosaic type 1’ (‘hominin morphological instability’), characterises the complex morphology of the H. naledi hand and foot, and interacts with their ‘Mosaic type 2’ (‘multiple phylogenetic trajectories for the same trait’), where H. naledi, A. sediba and Australopithecus africanus are seen as having different kinds of bipedalism. Mosaicism, however, has a far wider application: ‘The concept of “mosaic evolution” […] refuted the notion of harmonious development by affirming that individual organs could have independent phyletic histories, despite the evident correlation of parts within any organism’ (Gould, Reference Gould1977, p. 234). Parravicini and Pievani (Reference Parravicini and Pievani2018) give the example of human language, which is not a single trait but a convergence of different traits with different evolutionary history: this type of mosaicism they term ‘Mosaic Type 3’. Nevertheless, in hominin studies, the term mosaicism continues to be applied particularly to the hand and foot.

A recent review of foot evolution in relation to bipedalism, however, suggests that doubt is beginning to be expressed about the usefulness of the mosaicism concept: DeSilva et al. (Reference DeSilva, Carlson, Claxton, Harcourt-Smith, McNutt, Sylvester and Berger2018) conducted an extensive cladistic analysis of foot-bone morphology based on individual bones, reaching similar conclusions to earlier studies on the existence of mosaicism in ‘walking kinematics’ and arboreality in different lineages. We do, however, recognise that particularly given small sample sizes, their cladistic analysis of individual bones may ignore overall equivalence in kinematics, via ‘compensation’ between morphologies of different bony elements. We argue that this is probably the case, and that mosaicism in all three forms simply reflects basic mechanisms of evolvability and ecological robusticity, based on biological variation from the level of the genome all the way to the level of functional behaviour. We propose that mosaicism in the hand and foot is simply a reflection or merely a literal description of the number of bones, the joints they make up and the ligaments and tendons crossing joints, which allow morphologically different bones to contribute to the same external function, and equally to contribute, in different ways, to other external functions.

4. How variance and invariance are treated in evolutionary biomechanical interpretations.

Griffin and Tversky (Reference Griffin and Tversky1992) suggested that palaeontological research focusses on the ‘strengths of the extremeness’ of morphological difference, without a strong interpretive paradigm within which to interpret the observed extremeness. Given the depauperate nature of the fossil record, both in representations of species and in representation of the bony elements of individuals, a search for uniqueness has often prevailed over biological balance. This is exemplified by Spoor et al. (Reference Spoor, Leakey and Leakey2010), in the naming of a new hominin genus and species Kenyanthropus platyops based on a single, taphonomically deformed australopith cranium. White (Reference White2003) strongly (and we agree correctly) criticised this as an example of a lack of recognition of variation in palaeoanthropology. Surprisingly, however, the genus Kenyanthropus continues to be widely recognised. Equally, Brunet et al. (Reference Brunet, Guy, Pilbeam, Mackaye, Likius, Ahounta and Zollikofer2002) declared the 7 Ma Sahelanthropus tchadensis unequivocally hominin, based substantially on foramen magnum angle. This is despite the age of the specimen falling within the most generally accepted age range of the panin–hominin separation, based on molecular evidence (Jensen-Seaman & Hooper-Boyd, Reference Jensen-Seaman and Hooper-Boyd2008). More recently, however, Ruth et al. (Reference Ruth, Raghanti, Meindl and Lovejoy2016) reported that foramen magnum angle is not correlated with locomotor behaviour in rodents, strepsirrhine primates or marsupials, but again this has not led to Brunet et al.'s (Reference Brunet, Guy, Pilbeam, Mackaye, Likius, Ahounta and Zollikofer2002) claim being challenged.

How philosophy, science and the ‘covering law’ model (mis-)shaped traditional understanding of variability

Assumed invariance is the product of a tendency towards biological determinism (Lewontin, Reference Lewontin2001) that has traditionally constrained the interpretation of behavioural interpretations in palaeoanthropology. It is ironic that Darwin paid a significant amount of attention in his writings on evolutionary theory to reducing the emphasis on a ‘group modal’ perspective, in favour of a focus on variability within species (Darwin, Reference Darwin1871). The lack of recognition of variability in palaeoanthropology recalls the Platonic ‘ideal’, whereby variation was long regarded as pathology. This conceptualisation of variability has shaped theoretical and scientific understanding, adhering to the philosophy of ancient Greece, informed by Plato, Aristotle and Socrates. To exemplify, Plato's dialogue, The Meno, seeks to explain knowledge, experience and understanding in humans with reference to internalisation of universals, kinds, types and templates which are used to organise meaning in the world. This philosophical approach has led to the dominance of the ‘covering-law’ model in theory and science, which emphasises the labelling and generic categorisation of phenomena in groups, overlooking the relevance and pertinence of contextually driven variability. Criticisms of the way that the covering law model neglected and mis-represented variability in complex systems are relevant and influential because they tend to ‘dump context in favour of universals’ (Riley & Turvey, Reference Riley and Turvey2004, p. 164). Riley and Turvey (Reference Riley and Turvey2004) correctly criticised this, because it neglects emergence in nonlinear phenomena (such as evolving limbs and bone structures) whose trajectories are historically dependent on initial conditions, context and discontinuities arising from constraints on their flow (as information constraining system dynamics of long timescales).

To exemplify the dominant influence of the covering law model, in 1935, a ‘classic’ study by Elftman and Manter claimed that there was a clear distinction between the feet of humans and those of other apes (represented only by a chimpanzee), with only the latter declared to have clear ground contact in the lateral midfoot (now termed a ‘mid-tarsal break’), and so, a more posterior push-off than humans. This led to the Root model (Root et al., Reference Root, Orien and Weed1977) of an ideal ‘pes normalis’ with a strongly expressed and largely permanent arch, stiff lateral midfoot and predominant hallucal toe-off. This model was later elaborated by Bojsen-Møller (Reference Bojsen-Møller1979), who identified an interlocking mechanism of the cuboid peg matching a groove on the plantar calcaneus in humans, supporting a bony lateral arch. Neither hypothesis was tested in vivo, but both became embedded in podiatric, orthopaedic, anatomical and palaeoanthropological training, whereby performance departures from that ‘ideal’ were long assumed to be dysfunctional.

Disambiguating the Root model

Over the last 10 years the weight of evidence from experimental biomechanics has convinced many academics working with feet that the Root model is largely incorrect, and the vast variability in biomechanical parameters when testing the foot is relevant and significant to understanding of how functionality is driven by contextual constraints. This omission is now being addressed slowly but surely (see e.g. Nester et al., Reference Nester, Jones, Liu, Howard, Lundberg, Arndt and Wolf2007a, Reference Nester, Liu, Ward, Howard, Cocheba, Derrick and Pattersonb; Lundgren et al., Reference Lundgren, Nester, Liu, Arndt, Jones, Stacoff and Lundberg2008, McClymont et al., Reference McClymont, Pataky, Crompton, Savage and Bates2016; Morrison et al., Reference Morrison, McClymont, Price and Nester2017, Reference Morrison, Price, McClymont and Nester2018; Price et al., Reference Price, McClymont, Hashmi, Morrison and Nester2018). In vivo invasive kinematics and cadaver studies of foot bone motion have captured high variability in the range of motion in midfoot joints. Lundgren et al. (Reference Lundgren, Nester, Liu, Arndt, Jones, Stacoff and Lundberg2008) found so much functional variability in a sample of just six individuals that some had higher mobility proximal to the cuboid, while in others, higher mobility was distal to it. This level of inter-individual variability in movement coordination has increasingly been observed and conceptualised in the movement sciences and biomechanics (see Glazier & Davids, Reference Glazier and Davids2009a, Reference Glazier and Davidsb). Midfoot flexibility in humans has been discussed in the orthopaedic literature, noting high flexion in the sagittal plane (Ouzounian & Shereff, Reference Ouzounian and Shereff1989; Whittaker et al., Reference Whittaker, Aubin and Ledoux2011), while substantial midfoot dorsi-flexion, indicating internal variation in midfoot mobility, is widely accepted in biomechanics (see e.g. Lundberg et al., Reference Lundberg, Goldie, Kalin and Selvik1989aReference Lundberg, Svensson, Bylund, Goldie and Selvikc; Stacoff et al., Reference Stacoff, Nigg, Reinschmidt, van den Bogert and Lundberg2000; Arndt et al., Reference Arndt, Westblad, Winson, Hashimoto and Lundberg2004; Arndt et al., Reference Arndt, Wolf, Liu, Nester, Stacoff, Jones and Lundberg2007; Lundgren et al., Reference Lundgren, Nester, Liu, Arndt, Jones, Stacoff and Lundberg2008). Caravaggi et al. (Reference Caravaggi, Leardini and Giacomozzi2016) extended this concept further, towards foot–ground interaction, by demonstrating a statistical link between internal foot bone motion and plantar pressure (that is the pressure exerted externally against the substrate) and identified a high, but unexplained variance in plantar pressure.

While the Root model is now largely discredited in podiatric medicine, it has persisted within palaeoanthropology along with the treatment of variation as an unexplainable obstacle. For example, citing the Elftman–Manter/Bojsen–Møller/Root model, Jungers et al. (Reference Jungers, Harcourt-Smith, Wunderlich, Tocheri, Larson, Sutikna and Morwood2009) claim that limited saliency in the cuboid peg from the LB2 Homo floriesiensis skeleton implies bipedal gait distinct from our own. Meldrum et al. (Reference Meldrum, Lockley, Lucas and Musiba2011) claim that a line in a single footprint in the Laetoli G-1 trail (G-1/26) is evidence of a mid-tarsal break in Australopithecus afarensis. Contrarily, Ward et al. (Reference Ward, Kimbel and Johanson2011) interpreted features of a single fossil fourth metatarsal element of A. afarensis and the orientation of the proximal and distal ends, easily overlapping the human range, but not that of Pan or Gorilla, as showing proximo-distal torsion along the diaphysis. Furthermore, they interpreted its deep flat base and cuboid facets as demonstrating that the foot was functionally unable to produce a ‘midtarsal break’. Again, DeSilva et al. (Reference DeSilva2010) studied the cuboid facets of StW 485 and StW 596 (two isolated MT4 elements from Sterkfontein), and described them as flat and distinctly different from the convex facet of African apes. From this comparison, they claim that this feature reflects a lack of midfoot compliance (as seen in chimpanzees).

Before the recent increase in fossil discoveries, McHenry and Jones (Reference McHenry and Jones2006) quantified the variability of great toe adduction via analysis of the encroachment of the metatarsal 1 facet on the medial cuneiform, both in extant hominoids and in two fossil hominins. Despite a hominin sample size of 2, the authors concluded that hominins were specialised for bipedalism based on their highly adducted and unopposable great toe. However, Zipfel et al. (Reference Zipfel, DeSilva, Kidd, Carlson, Churchill and Berger2011) compared the calcaneal morphology of the foot and ankle of A. sediba with five other great apes (their figure 4B), which latter formed loosely overlapping clusters, and found A. sediba to be grouped with the gorillas. The same is the case for a more recent study of the subtalar joint of A. sediba compared with eastern and western Gorilla, Pan, Hylobates, Pongo and modern Homo (Prang, Reference Prang2016), where a canonical variates analysis of nine talar and calcaneal variables shows a clear overlap in the standard deviations between species. An excellent study by Dunn et al. (Reference Dunn, Tocheri, Orr and Jungers2014) documents high variation in western (Gorilla beringei) and eastern (Gorilla gorilla) talar morphology, suggesting a link between their morphology and their environment. With this notable exception, awareness of variation has otherwise not often been accompanied by a serious attempt to explain and interpret its role in movement, most likely because of a lack of a grounding theory upon which to hang such interpretations.

Caravaggi et al. (Reference Caravaggi, Leardini and Giacomozzi2016) demonstrated a direct statistical link between foot pressure topology and foot bone mobility. Mobile foot joints enable the exchange of force between the foot and ground in a smooth ‘roll-over’ motion (Caravaggi et al., Reference Caravaggi, Leardini and Giacomozzi2016). This roll-over has been observed in all great apes studied to date (Bates et al., Reference Bates, Collins, Savage, McClymont, Webster, Pataky and Crompton2013a). Inter-species comparison of pressure patterns of human, bonobo and orang-utan subjects revealed a clear overlap in the distribution and magnitude of pressure between these hominoid taxa (Vereecke et al., Reference Vereecke, D'Août, De Clercq, Van Elsacker and Aerts2003; Crompton et al., Reference Crompton, Sellers and Thorpe2010; Bates et al., Reference Bates, Collins, Savage, McClymont, Webster, Pataky and Crompton2013a). Humans, bonobos and orang-utans can all display either a so-called ‘mid-tarsal break’ or very low lateral midfoot pressure, owing to the high range of motion and variability between the tarsals, and between tarsal and metatarsal elements in great ape feet. While the habitual mean tendency of modern human midfoot mechanics is certainly one of a rigid lateral midfoot, compared with a more compliant midfoot in the other African apes, recent datasets have revealed consistently high variability in arch compliance (exhibited by high peak pressure) in the lateral midfoot of humans (Bates et al., Reference Bates, Collins, Savage, McClymont, Webster, Pataky and Crompton2013a; DeSilva et al., Reference DeSilva, Holt, Churchill, Carlson, Walker, Zipfel and Berger2013). Bates et al. (Reference Bates, Collins, Savage, McClymont, Webster, Pataky and Crompton2013a) report high lateral midfoot pressures in their human sample, reporting observed overlap in relative midfoot pressure with other species of great ape (Pan paniscus and Pongo pygmaeus), as previously reported by Vereecke et al. (Reference Vereecke, D'Août, De Clercq, Van Elsacker and Aerts2003) and Crompton et al. (Reference Crompton, Sellers and Thorpe2010).

Fossil footprint trails have offered some hope of reconstructing the external function of the early hominid locomotor system. A recent contribution by Hatala et al. (Reference Hatala, Demes and Richmond2016) based on five of the intact 11 Laetoli G-1 prints (attributed to A. afarensis) claimed to identify functionally meaningful differences between the gait of the Laetoli G-1 trackmaker and that of modern humans. Their interpretation is focussed on supposed similarities to footprints made by chimpanzees during bipedal locomotion and they argue that the Laetoli G-1 track maker walked with a more flexed knee posture than modern humans. Crucially, however, as pointed out by Bennett et al. (Reference Bennett, Reynolds, Morse and Budka2016), they did not register the Laetoli, chimpanzee and human footprints to each other, which involves the stacking and alignment of each of the footprints’ topological surfaces, enabling direct, statistically robust, topological comparisons (Pataky & Goulermas, Reference Pataky and Goulermas2008; Pataky et al., Reference Pataky, Caravaggi, Savage, Parker, Goulermas, Sellers and Crompton2008; Crompton et al., Reference Crompton, Pataky, Savage, D'août, Bennett, Day and Sellers2012; Bates et al., Reference Bates, Savage, Pataky, Morse, Webster, Falkingham and Crompton2013b; McClymont et al., Reference McClymont, Pataky, Crompton, Savage and Bates2016). In line with previous studies, Hatala et al. (Reference Hatala, Demes and Richmond2016) subjectively selected 14 ‘functional’ points on each plantar surface based on anatomical markers for comparison. Such ‘region of interest’ comparisons are common in the literature (see, e.g. Hughes et al., Reference Hughes, Pratt, Linge, Clark and Klenerman1991; Rosenbaum et al., Reference Rosenbaum, Hautmann, Gold and Claes1994; Zhu et al., Reference Zhu, Wertsch, Harris and Alba1995; Kernozek et al., Reference Kernozek, LaMott and Dancisak1996; Brown & Mueller, Reference Brown and Mueller1998; Drerup et al., Reference Drerup, Hafkemeyer, Möller and Wetz2001; Burnfield et al., Reference Burnfield, Few, Mohamed and Perry2004; Segal et al., Reference Segal, Rohr, Orendurff, Shofer, O'Brien and Sangeorzan2004; Taylor et al., Reference Taylor, Menz and Keenan2004; Warren et al., Reference Warren, Maher and Higbie2004; Yang et al., Reference Yang, Chiu, Lin and Chen2005; Shu et al., Reference Shu, Hua, Wang, Li, Feng and Tao2010; Paton et al., Reference Paton, Bruce, Jones and Stenhouse2011; Barn et al., Reference Barn, Waaijman, Nollet, Woodburn and Bus2015; Howcroft et al., Reference Howcroft, Lemaire, Kofman and Kendell2016; Wallace et al., Reference Wallace, White, Augsburger and Walker2021), and while Hatala et al. (Reference Hatala, Demes and Richmond2016) chose to compare 14 points rather than the three to 10 units compared in the above-cited studies, we suggest that the two methods can lead to similar inaccuracies in results. Anatomical masking breaks the plantar surface into subjectively defined regions, reducing the naturally occurring functional appearance of pressure patterns, and fails to account for the plantar surface as it exists in reality, i.e. a single functional unit. Research has shown that masking can conflate or even reverse statistical interpretations when compared with pixel-by-pixel analyses (Pataky et al., Reference Pataky, Caravaggi, Savage, Parker, Goulermas, Sellers and Crompton2008). Furthermore, it has been shown that longer walking sequences provide more stable measures of variability (Gök et al., Reference Gök, Ergin and Yavuzer2002; Barker, Reference Baker2006) and that a high number of data points or steps is needed in order to capture the naturally occurring levels of habitual variation. McClymont and Crompton (Reference McClymont and Crompton2021) recently demonstrated that some 200 consecutive pressure records, collected from a pressure-sensitive treadmill, are necessary to statistically characterise an individual's habitual plantar pressure pattern. We accept that this requirement is not achievable in many cases given differing access to equipment, age and pathology.

In a recent comparative analysis, we reported a comparative pedobarographic statistical parametric mapping analysis of the footprint trails from the following sites: Laetoli (probably made by A. afarensis), Ileret (probably made by early Homo), Walvis Bay, Namibia (made by subrecent Homo sapiens) and a modern human sample (McClymont et al., Reference McClymont, Savage, Pataky, Crompton, Charles and Bates2021). Both the Laetoli and Ileret footprint trails show a significant difference from the modern human sample, evidenced by a deeper impression under the region of the medial arch. Yet when the Laetoli and Ileret prints are compared with the anatomically modern human footprints from Namibia, the Ileret prints show a small area of statistically significant difference in the medial mid-foot, i.e. a deeper impression. However, there are no statistically significant differences when compared with the mid-foot of footprints made by habitually unshod (Namibian) recent humans and our 11-print Laetoli dataset. That differences in relative midfoot footprint depth are greatly reduced (and in the case of Laetoli, eliminated) when early Homo (Ileret) and Australopithecus (Laetoli) are compared can be understood in the context of a previous study of foot pressures in habitually unshod modern populations. This observation revealed such individuals to have functionally lower medial longitudinal arches on average than modern, Western individuals (Willems et al., Reference Willems, Stassijns, Cornelis and D'Août2017). In other words, it appears that habitual shoe-wearing artificially induces a higher medial arch, more similar to the ideal ‘pes normalis’ of the Root model.

Bates et al. (Reference Bates, Savage, Pataky, Morse, Webster, Falkingham and Crompton2013b) reported that experimental and modelling studies of the relationship of footprint depth to footprint morphology show a clear tendency for deeper prints to have relatively deeper impressions under the forefoot. It is, therefore, likely that the statistically significant differences between the Laetoli G-1 and Ileret prints are attributable to the greater overall footprint depth at Ileret, where moisture content is likely to have been higher and the sediment correspondingly weaker in strength (Bennett et al., Reference Bennett, Harris, Richmond, Braun, Mbua, Kiura and Gonzalez2009). Similarly, the relatively greater number of deep prints from Namibia (i.e. those from wetter substrate contexts) could readily account for a deeper hallux impression than Laetoli. Based on the nature of footprint formation, and the relative depths from each site, we argue that there is no evidence of detectable functional differences in foot (and hence upper body) biomechanics between the Laetoli G-1, Ileret and Namibian footprint trails.

The pixel-level statistical analysis presented here agrees with the finding of Bennett et al. (Reference Bennett, Reynolds, Morse and Budka2016) based on the depth profiling of registered prints. Here, we interpret the lack of any statistically significant differences between fossil footprint sites as evidence of high redundancy and locomotor plasticity in the hominins, driven by neurobiological degeneracy and substrate effects (Bates et al., Reference Bates, Savage, Pataky, Morse, Webster, Falkingham and Crompton2013b; McClymont et al., Reference McClymont, Savage, Pataky, Crompton, Charles and Bates2021). The classic interpretation of fossil footprints claims that differences (or invariance) in morphologies between species creates different internal loading patterns, producing a different print topology. Given the overlap between great apes we have noted above in foot pressure and that substrate texture is the prime formative influence in footprint creation, we argue that the functional differences gleaned and extrapolated to lower and upper body posture and locomotor practice (Hatala et al., Reference Hatala, Demes and Richmond2016) are a false positive, i.e. inferring an experimental effect when none actually exists (Pataky et al., Reference Pataky, Vanrenterghem and Robinson2016), in this case, the error of inferring internal and external mechanical differences from external topology alone.

Given that some 200 walking cycles on a pressure-sensitive treadmill are necessary to characterise an individual's habitual foot pressure (McClymont & Crompton, Reference McClymont and Crompton2021) and the substrate effects of making footprints noted by Bates et al. (Reference Bates, Savage, Pataky, Morse, Webster, Falkingham and Crompton2013b) and Bennett et al. (Reference Bennett, Reynolds, Morse and Budka2016), we regret that there seems little hope of correctly interpreting fine functional details such as midfoot characteristics, or the extent of lateral-to-medial force transfer from early hominin footprints. Only the most unambiguous features of trails are likely to yield high-quality biomechanical signals, e.g. the relatively greater depth of impressions under the heel than the metatarsal heads (forefoot) in Laetoli G-1 does indeed provide a signal of upright locomotion rather than ‘bent-hip–bent-knee’ gait (Crompton et al., Reference Crompton, Pataky, Savage, D'août, Bennett, Day and Sellers2012). Otherwise, the Laetoli prints can only be taken as reflecting the locomotor plasticity available to the track maker at 3.3 Ma.

A recent review article by Wood and Boyle (Reference Wood and Boyle2016) suggests clear evidence for species-level distinctions in morphology between, e.g., Australopithecus anamensis and A. afarensis, but simply calls for palaeontologists not to be ‘over-confident’ in interpretations of fossil remains. Similarly, Ward and Middleton (2016) report more substantial variation in thoracic shape in anthropoids (including humans) than previously expected. They found that the upper rib cage shows only a weak link to locomotion, and the lower rib cage shows a closer link to pelvic morphology than to upper rib cage morphology, and simply conclude that variability needs to be taken into consideration more seriously in studies of locomotor evolution. Again, Marigó et al. (Reference Marigó, Roig, Seiffert, Moyà-Solà and Boyer2016) quantified inter-subject variability in the morphology of the calcanei and astragali of a middle Eocene primate, Anchomomys frontanyensis, to assess its phylogenetic position compared with other crown strepsirrhines. They demonstrate a large statistical overlap in linear metrics of morphology within crown strepsirrhines, both living and fossil; however, this was not explained further. Similarly, Boyle et al. (Reference Boyle, McNutt, Sasaki, Suwa, Zipfel and DeSilva2018) showed extreme variability in the lateral plantar process of the calcaneus, overlapping with G. gorilla, P. troglodytes, A. sediba and A. afarensis (A.L.333-8), concluding that the variability might signal normal variation, locomotor diversity or two independently evolving adaptations for heel strike in two different hominin lineages. More recently, Marigó's team report high variability in humeri of Adapiformes (Eocene primates), concluding that high morphological variability suggests that 14 different locomotor repertoires were used by different species (Marigó et al., Reference Marigó, Minwer-Barakat, Moyà-Solà and Boyer2020). Similarly, Drapeau and Harmon (Reference Drapeau and Harmon2013) plot, but do not explain, the considerable overlap of metatarsal head torsion in their dataset of monkeys, non-human apes, humans and australopiths, rather simply attributing variation to differences in locomotion. Tsegai et al. (Reference Tsegai, Skinner, Pahr, Hublin and Kivell2018a, Reference Tsegai, Skinner, Pahr, Hublin and Kivellb) compared trabecular patterns in humans and chimpanzees, and found that while trabecular bone volume fraction shows differences between forelimb and hindlimb in humans and chimpanzees, this parameter did not clearly reflect locomotor loading, whilst degree of anisotropy was more likely to reflect locomotor loading than species. Care is thus required in interpreting what otherwise appears to be a promising measure by which to relate locomotor activity to species in isolated fossil bones. While in the above studies, variation has at least been acknowledged, the observed variation can be explained by plasticity and degeneracy.

5. Locomotor variation

As observed by Bock (Reference Bock1994), robust interpretations of evolutionary adaptations should be ‘nomological’, that is, regardless of system structure or composition, underlying phenomena should be explained by similar abstract principles. For example, the natural laws of physics underlie a system's capacity to maintain stability during dynamic movement. During locomotory activity, natural selection drives the adaptation of interactive hard and soft tissue configurations that enhance performance relative to the constraints of a specific environment, and each may be studied and distinguished between species (Laland et al., Reference Laland, Uller, Feldman, Sterelny, Müller, Moczek and Odling-Smee2015). This is one of the core assumptions of the Extended Evolutionary Synthesis, termed ‘reciprocal causation’, whereby: ‘organisms shape, and are shaped’ equally (p. 2, Laland et al., Reference Laland, Uller, Feldman, Sterelny, Müller, Moczek and Odling-Smee2015) by selective and developmental environments. Thus, developmental and niche diversification works with natural selection in determining the rate and direction of adaptations (Laland et al., Reference Laland, Uller, Feldman, Sterelny, Müller, Moczek and Odling-Smee2015). In particular, the relatively new field of ecomorphology seeks to explain the covariation of ecology and morphology (Winkler, Reference Winkler1988; Wainwright, Reference Wainwright1991). This field has particularly clear applications to Primates, since they are typically large-bodied and predominantly arboreal, thus, ensuring stability and fall avoidance during locomotion is likely to be naturally selected for in arboreal apes. Vertebrate gait is characterised by variable fluctuations in stride index parameters that functionally stimulate stability during locomotion (Grillner, Reference Grillner1985; Arutyunyan et al., Reference Arutyunyan, Gurfinkel and Mirskii1968; Davids et al., Reference Davids, Kingsbury, George, O'Connell and Stock1999; Dingwell et al., Reference Dingwell, Cusumano, Cavanagh and Sternad2001; Jordan et al., Reference Jordan, Challis and Newell2007a, Reference Jordan, Challis and Newellb). The rhythmic, alternating activity of the inverted pendulum, for example, becomes a major factor in stability of both bipeds and quadrupeds. Local dynamic stability measured by variability in human walking parameters has been revealed as a predictor of the likelihood of fall injury (Calandre & Conde, Reference Calandre and Conde2005; Lockhart & Liu, Reference Lockhart and Liu2008). It may, thus, reasonably be assumed to be naturally selected for in humans as well. A stable gait is defined as one during which the individual does not fall over, despite perturbations (Dingwell et al., Reference Dingwell, Cusumano, Cavanagh and Sternad2001; Bruijn et al., Reference Bruijn, Meijer, Beek and van Dieen2013). In primates and other arboreal species, stability of branch support itself is an important parameter to contend with.

Bernstein (Reference Bernstein1967, p. 234) referred to the importance of movement organisation describing it as ‘repetition without repetition’, in order to enhance the functionality of behaviour. A seminal insight of Bernstein (Reference Bernstein1967) was that movement organisation is ‘function specific’, not ‘muscle specific’, the latter being a dominant idea in the neuroanatomically dominated Russian movement science theory for many years. According to his insights, movement (re)organisation is temporarily assembled from system degrees of freedom to adaptively (re)produce a specific, intended task outcome, under varying task constraints (Bernstein, Reference Bernstein1967; Latash et al., Reference Latash, Scholz and Schöner2002). In all animal locomotion, the coefficients of variation of step-length and step-width change with time, and relative to external and internal constraints (Bernstein, Reference Bernstein1967; Alexander, Reference Alexander1984; Bock, Reference Bock1994), naturally facilitating adaptative stepping. This, step-to-step strategy varies to allow for anticipated or unexpected perturbations and changes in speed, slope, surface and substrate compliance. Thus, each step is uniquely organised to resist internal (Su & Dingwell Reference Su and Dingwell2007; Byl & Tedrake Reference Byl and Tedrake2009) and external perturbations (Harris & Wolpert Reference Harris and Wolpert1998; Faisal et al., Reference Faisal, Selen and Wolpert2008). The standard coefficient of variation equation (CV =α/μ), however, is not a measure of functional stability in a moving system (Dingwell et al., Reference Dingwell, Cusumano, Cavanagh and Sternad2001; Bruijn et al., Reference Bruijn, Meijer, Beek and van Dieen2013; van Emmerik et al., Reference Van Emmerik, Ducharme, Amado and Hamill2016), rather, the distribution (or range) of a parameter about the mean. Differences in the coefficient of variation of step kinematics are relatively small: for example, only a few per cent increase or decrease in parameter change will occur, signifying the finely tuned nature of motor control mechanisms that regulate the basis of an uninterrupted, continuous gait pattern (Gabell & Nayak, Reference Gabell and Nayak1984; Hausdorff et al., Reference Hausdorff, Edelberg, Mitchell, Goldberger and Wei1997; Alexander, Reference Alexander2013; Terrier and Schutz, Reference Terrier and Schutz2005; Jordan et al., Reference Jordan, Challis and Newell2007a, Reference Jordan, Challis and Newellb; Vaillancourt et al., Reference Vaillancourt, Sosnoff and Newell2004).

We have noted that in palaeoanthropology a change in midfoot function is often regarded as the hallmark of human evolution: the transition to terrestrial bipedality (e.g. Ward et al., Reference Ward, Kimbel and Johanson2011). As humans walk faster, approaching the walk–run transition at some 1.88 m s−1, the plantar aponeurosis (apparently a derived feature in hominins, see e.g. Crompton et al., Reference Crompton, Sellers and Thorpe2010), pre-tenses prior to heel strike, collapsing through mid-stance and reaching maximum tension through to late stance phase (Caravaggi et al., Reference Caravaggi, Leardini and Giacomozzi2016). The arch-stiffening mechanism is speed dependent, but this feature does not appear to be reflected by variability in plantar pressure, which has been shown to be independent of speed (McClymont et al., Reference McClymont, Pataky, Crompton, Savage and Bates2016).

6. Degeneracy and evolution

When degeneracy is low in a complex adaptive system, many different elements can affect output in a similar way, but do not have independent effects. In highly degenerate systems, many different elements can affect output in a similar way, but also have independent effects, and may be recruited by different systems, to achieve different tasks. Edelman and Gally (Reference Edelman and Gally2001) showed that degeneracy is expressed at many different levels of biological organisation, from the genetic code itself, through levels including protein folding, metabolism, diet, cell signalling, synaptic plasticity, body motion, skill acquisition, motor learning and language. Thus, they argued, degeneracy is both necessary for, and an inevitable outcome of, natural selection. Based on Complex Adaptive Systems modelling, Whitaker and Bender (Reference Whitaker and Bender2009) argued that at all levels from the genome to locomotor behaviour, degeneracy is a source of robusticity, positively correlated with complexity, and yet increases adaptability and evolvability. In turn, evolvability is a requirement for complexity, and increased complexity enhances robustness (Figure 1). Whitaker shows that this relationship is demonstrated by cryptic genetic variation, which is made possible by system robusticity in natural selection, as well as by genetic regulatory networks and thus evolution itself. In simulation experiments, Whitaker and Bender (Reference Whitaker and Bender2009) showed that purely redundant systems have very low evolvability. In contrast, degenerate, and thus only partially redundant, systems display orders-of-magnitude-higher evolvability.

Figure 1. An example of the functional relationships between degeneracy, complexity, robustness and evolvability, after Whitaker and Bender Reference Whitaker and Bender2009.

Thus, the feet of primates, by retaining a highly degenerate structure, optimise both robustness in complex environments (such as the mixed woodland/grassland environments occupied by early hominins) and evolvability in cases of climatic and environmental change, which characterised much of East and South Africa since the late Miocene. We argue that rather than interpreting the structure of early hominin feet as a mosaic of human-like and nonhuman-ape-like characteristics, degeneracy allows us to conceptualise how feet, such as those of A. sediba, are admirably adapted to unstable environmental conditions, while able to sustain capability within the range of immediately available habitats.

Similarly, the degeneracy equally evident in the hand would have allowed early hominins to use the hand both in a support role, in arboreal contexts, and in manipulation, in terrestrial contexts. When performing in complex, dynamic performance environments, Rein et al. (Reference Rein, Davids and Button2010) showed that skilled basketball players, for example, can exploit two to six distinct patterns of joint coordination to shoot at the same target from different distances. Seifert et al. (Reference Seifert, Wattebled, Herault, Poizat, Adé, Gal-Petitfaux and Davids2014) demonstrated that expert ice climbers also show higher levels of system degeneracy, namely a greater range of coordination patterns, than novices, allowing them to exploit grip opportunities in the ice much more effectively. Similar phenomena have been observed when expert musicians are compared with novices (Verrel et al., Reference Verrel, Pologe, Manselle, Lindenberger and Woollacott2013; Slater Reference Slater2020). Such studies have substantial relevance to the skills involved in stone tool manufacture. Bardo et al. (Reference Bardo, Vigouroux, Kivell and Pouydebat2018) used modelling approaches to assess biomechanical potential for tool-related behaviours, observing that the orang-utan hand performed poorly compared with that of humans and gorillas, requiring higher muscle forces for a similar range of motion. They found that the hand of A. sediba, however, would have had the potential for stone tool use, and perhaps manufacture, suggesting that prehensive capability had become more important to these individuals than stable grasping of larger vines and branches, consistent with the suggestion of Bardo et al. (Reference Bardo, Vigouroux, Kivell and Pouydebat2018). Unspecialised hands appear to have higher capacity for fine prehension, but, by analogy to the above, we suggest also for development of expertise, in individual tool-making hominins. Thus, humans who begin to knap tools would have low degeneracy in terms of joint coordination, only enhancing degeneracy progressively as their expertise improves.

High variability in morphology is an in-built mechanism of natural selection, which, in hominoids, with their unspecialised extremities, facilitated a sustained capacity to use affordances of both arboreal and terrestrial terrains in the changing environments of the late Miocene and Pliocene. Even for late Plio-Pleistocene environments, where substantial savannah had appeared, Anton et al. (Reference Antón, Potts and Aiello2014) noted the potential role of highly diverse habitats, affecting speciation opportunities favouring hominin adaptive versatility. Local habitat mosaicism, which would also offer high biodiversity, is typical of protohominins and early hominin environments, as in the palaeoenvironments attributed to Sahalanthropus tchadensis (Brunet et al., Reference Brunet, Guy, Pilbeam, Mackaye, Likius, Ahounta and Zollikofer2002; Brunet, Reference Brunet2002), 7 Ma, from Chad, which are described as being akin to the Okavango Delta (Central Kalahari, Botswana; Brunet, Reference Brunet2010). Such complex environments would also be expected to exert selective pressure for ‘adaptive versatility’, or as we refer to it, locomotor plasticity, driven by inherent system degeneracy.

7. Conclusions

Our analysis and commentary suggest that variability and variance in the fossil record present a history in bone of the different kinematic solutions available in highly degenerate, complex and adaptive, primate postcranial systems. In this paper we have suggested how the concept of degeneracy could underpin a new interpretive paradigm for explaining observed variability in fossil elements, fortifying interpretations of possible locomotor behaviours. We also suggest that using a degeneracy framework to conceptualise human movement systems as complex adaptive systems encourages a move away from a reductionist perspective in studying neuroanatomical components in isolation of the affordances available in the surrounding environment. The current frequency of use of the term ‘mosaicism’ demonstrates the unfamiliarity that palaeoanthropologists have with the concept of variability, at many levels of analysis. This is understandable, considering the small sample sizes available, and the historically negative connotations of variability. Nevertheless, given the complexity of the foot, we find it essential to anchor locomotor and functional interpretations of the observed variability in systems biology, specifically harnessing the framework of neurobiological degeneracy. The observed variability in foot bone morphology across great apes and in early hominin feet should similarly be interpreted in terms of high levels of degeneracy in the foot complex, selecting for locomotor plasticity.

We have provided evidence from the foot – one of only two structures in the body that can interact directly in contact with the environment during locomotory movement – that variability is inherent to functional biological movement, enabling adaptable and flexible locomotor behaviours in rich and varied terrains.

We have argued that the observed variability in the fossil record can be understood more completely when using the theory of neurobiological degeneracy. Degeneracy can explain not only the observed variability in biomechanical parameters, but also the observed morphological overlap in hominin fossil and primate species. Functional variability in the foot has been a selective target in hominoids as a whole, and in hominins in particular, as a key component of overall locomotor plasticity and degeneracy.

The main implications for the palaeontological literature are that using the theory of degeneracy provides a cohesive, interpretive framework that may be beneficial in: (a) (re)interpreting the observed variability and overlap between hominoid fossil and extant species, and (b) providing a more robust understanding of evolutionary pressures that shaped structurally complex organs, such as the hominoid and hominin foot, and the mechanisms which retain both evolvability and robusticity, than those currently conceptualised as mosaicism.

Acknowledgements

We thank Christine Janis for a critical review of an early version of this paper.

Funding

RHC's contribution to this study was made under an Emeritus Fellowship from the Leverhulme Trust: EM-2017-010\2. Otherwise, this research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing interests

The authors report no competing interests.

Data availability statement

This is a review paper and does not rely on primary data

Author contributions

JMcC conceived the idea resulting from discussion with the second author and authored and reviewed the manuscript. RHC authored and reviewed manuscript drafts, KD reviewed manuscript drafts.

References

Alexander, R. M. (1984). Stride length and speed for adults, children, and fossil hominids. American Journal of Physical Anthropology, 63(1), 2327.CrossRefGoogle ScholarPubMed
Alexander, R. M. (2013). Principles of animal locomotion. Princeton University Press.Google Scholar
Antón, S. C, Potts, R., & Aiello, L. C. (2014). Evolution of early Homo: An integrated biological perspective. Science, 345(6192), 4557.CrossRefGoogle ScholarPubMed
Arndt, A., Westblad, P., Winson, I., Hashimoto, T., & Lundberg, A. (2004). Ankle and subtalar kinematics measured with intracortical pins during the stance phase of walking. Foot and Ankle International, 25(5), 357364.CrossRefGoogle ScholarPubMed
Arndt, A., Wolf, P., Liu, A., Nester, C., Stacoff, A., Jones, R., …, Lundberg, A. (2007). Intrinsic foot kinematics measured in vivo during the stance phase of slow running. Journal of biomechanics, 40(12), 26722678.CrossRefGoogle ScholarPubMed
Arutyunyan, G. A., Gurfinkel, V. S., & Mirskii, M. L. (1968). Investigation of aiming at a target. Biophysics, 13(3), 642645.Google Scholar
Baker, R. (2006). Gait analysis methods in rehabilitation. Journal of Neuroengineering and Rehabilitation, 3(1), 110.CrossRefGoogle ScholarPubMed
Bardo, A., Vigouroux, L., Kivell, T. L., & Pouydebat, E. (2018). The impact of hand proportions on tool grip abilities in humans, great apes and fossil hominins: A biomechanical analysis using musculoskeletal simulation. Journal of Human Evolution, 125, 106121.CrossRefGoogle ScholarPubMed
Barn, R., Waaijman, R., Nollet, F., Woodburn, J., & Bus, S. A. (2015). Predictors of barefoot plantar pressure during walking in patients with diabetes, peripheral neuropathy and a history of ulceration. PloS One, 10(2), e0117443.CrossRefGoogle Scholar
Bates, K. T., Collins, D., Savage, R., McClymont, J., Webster, E., Pataky, T. C., …, Crompton, R. H. (2013a). The evolution of compliance in the human lateral mid-foot. Proceedings of the Royal Society B: Biological Sciences, 280(1769), 20131818.CrossRefGoogle Scholar
Bates, K. T., Savage, R., Pataky, T. C., Morse, S. A., Webster, E., Falkingham, P. L., …, Crompton, R. H. (2013b). Does footprint depth correlate with foot motion and pressure? Journal of the Royal Society Interface, 10(83), 20130009.CrossRefGoogle Scholar
Bennett, M. R., Harris, J. W., Richmond, B. G., Braun, D. R., Mbua, E., Kiura, P., …, Gonzalez, S. (2009). Early hominin foot morphology based on 1.5-million-year-old footprints from Ileret, Kenya. Science, 323(5918), 11971201.CrossRefGoogle ScholarPubMed
Bennett, M. R., Reynolds, S. C., Morse, S. A., & Budka, M. (2016). Footprints and human evolution: Homeostasis in foot function? Palaeogeography, Palaeoclimatology, Palaeoecology, 461, 214223.CrossRefGoogle Scholar
Bernstein, N. A. (1967). The co-ordination and regulation of movements. Oxford: Pergamon.Google Scholar
Bock, W. J. (1965). The role of adaptive mechanisms in the origin of higher levels of organization. Systematic Zoology, 14(4), 272287.CrossRefGoogle ScholarPubMed
Bock, W. J. (1994). Concepts and methods in ecomorphology Journal of Biosciences, 19(4), 403413.CrossRefGoogle Scholar
Bojsen-Møller, F. (1979). Calcaneocuboid joint and stability of the longitudinal arch of the foot at high and low gear push off. Journal of Anatomy, 129(Pt 1), 165.Google ScholarPubMed
Boyle, E. K., McNutt, E. J., Sasaki, T., Suwa, G., Zipfel, B., & DeSilva, J. M. (2018). A quantification of calcaneal lateral plantar process position with implications for bipedal locomotion in Australopithecus. Journal of Human Evolution, 123, 2434.CrossRefGoogle ScholarPubMed
Brown, H. E., & Mueller, M. J. (1998). A ‘step-to’ gait decreases pressures on the forefoot. Journal of Orthopaedic & Sports Physical Therapy, 28(3), 139145.CrossRefGoogle ScholarPubMed
Bruijn, S. M., Meijer, O. G., Beek, P. J., & van Dieen, J. H. (2013). Assessing the stability of human locomotion: A review of current measures. Journal of the Royal Society Interface, 10(83), 20120999.CrossRefGoogle ScholarPubMed
Brunet, M. (2002). Sahelanthropus or ‘Sahelpithecus’? Nature, 419(6907), 582582.CrossRefGoogle Scholar
Brunet, M. (2010). Short note: The track of a new cradle of mankind in Sahelo-Saharan Africa (Chad, Libya, Egypt, Cameroon). Journal of African Earth Sciences, 58(4), 680683.CrossRefGoogle Scholar
Brunet, M., Guy, F., Pilbeam, D., Mackaye, H. T., Likius, A., Ahounta, D., …, Zollikofer, C. (2002). A new hominid from the Upper Miocene of Chad, Central Africa. Nature, 418(6894), 145151.CrossRefGoogle ScholarPubMed
Burnfield, J. M., Few, C. D., Mohamed, O. S., & Perry, J. (2004). The influence of walking speed and footwear on plantar pressures in older adults. Clinical Biomechanics, 19(1), 7884.CrossRefGoogle ScholarPubMed
Byl, K., & Tedrake, R. (2009). Metastable walking machines. The International Journal of Robotics Research, 28(8), 10401064.CrossRefGoogle Scholar
Calandre, L., & Conde, I. (2005). Gait and stability disorders of the elderly. Clinical analysis of a series of 259 patients older than 70 years. Neurologia 20(5), 232239.Google ScholarPubMed
Caravaggi, P., Leardini, A., & Giacomozzi, C. (2016). Multiple linear regression approach for the analysis of the relationships between joints mobility and regional pressure-based parameters in the normal-arched foot. Journal of Biomechanics, 49(14), 34853491.CrossRefGoogle ScholarPubMed
Carlson, K. J., Stout, D., Jashashvili, T., De Ruiter, D. J., Tafforeau, P., Carlson, K., & Berger, L. R. (2011). The endocast of MH1, Australopithecus sediba. Science, 333(6048), 14021407.CrossRefGoogle ScholarPubMed
Chow, J. Y., Davids, K., Button, C., Rein, R., Hristovski, R., & Koh, M. (2009). Dynamics of multi-articular coordination in neurobiological systems. Nonlinear Dynamics, Psychology, and Life Sciences, 13(1), 27.Google Scholar
Cornwallis, C. K., & Uller, T. (2010). Dynamic affairs – Could be if we let it! American Naturalist 172, S 49S62.Google Scholar
Crispo, E., & Chapman, L. J. (2008). Population genetic structure across dissolved oxygen regimes in an African cichlid fish. Molecular Ecology, 17(9), 21342148.CrossRefGoogle Scholar
Crompton, R. H., Li, Y., Thorpe, S. K., Wang, W. J., Savage, R., Payne, R., … Declerq, D. (2003). The biomechanical evolution of erect bipedality. Courier Forschuungsinstitut Senckenberg, 243, 115126.Google Scholar
Crompton, R. H., McClymont, J., Elton, S., Thorpe, S., Sellers, W., Heaton, J., Pickering, T. R., …, Clarke, R. (2021). A possible locomotor bauplan for Australopithecus informed by an ecomorphology perspective applied to StW 573 A. prometheus, Sterkfontein Member 2, ~3.67 Ma. Folia Primatologica, in press.Google Scholar
Crompton, R. H., Pataky, T. C., Savage, R., D'août, K., Bennett, M. R., Day, M. H., …, Sellers, W. I. (2012). Human-like external function of the foot, and fully upright gait, confirmed in the 3.66 million year old Laetoli hominin footprints by topographic statistics, experimental footprint-formation and computer simulation. Journal of the Royal Society Interface, 9 (69), 707719.CrossRefGoogle ScholarPubMed
Crompton, R. H., Sellers, W. I., & Thorpe, S. K. (2010). Arboreality, terrestriality and bipedalism. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1556), 33013314.CrossRefGoogle ScholarPubMed
Danchin, É., Charmantier, A., Champagne, F. A., Mesoudi, A., Pujol, B., & Blanchet, S. (2011). Beyond DNA: Integrating inclusive inheritance into an extended theory of evolution. Nature Reviews Genetics, 12(7), 475486.CrossRefGoogle ScholarPubMed
D'Août, K., & Aerts, P. (2008). The evolutionary history of the human foot. Advances in plantar pressure measurements in clinical and scientific research (pp. 4468). Shaker.Google Scholar
Darwin, C. (1871). The descent of man and selection in relation to sex. Murray.Google Scholar
Davids, K., & Glazier, P. (2010). Deconstructing neurobiological coordination: The role of the biomechanics–motor control nexus. Exercise and Sport Sciences Reviews, 38(2), 8690.CrossRefGoogle ScholarPubMed
Davids, K., Glazier, P., Araujo, D., & Bartlett, R. (2003). Movement systems as dynamical systems. Sports Medicine, 33(4), 245260.CrossRefGoogle ScholarPubMed
Davids, K., Kingsbury, D., George, K., O'Connell, M., & Stock, D. (1999). Interacting constraints and the emergence of postural behavior in ACL-deficient subjects. Journal of Motor Behavior, 31(4), 358366.CrossRefGoogle ScholarPubMed
Day, M. H., & Napier, J. R. (1964). Fossil foot bones. Nature, 201, 969970.CrossRefGoogle ScholarPubMed
Day, M. H., & Wood, B. A. (1968). Functional affinities of the Olduvai Hominid 8 talus. Man, 3(3), 440455.CrossRefGoogle Scholar
de Beer, G. R. (1954). Archaeopteryx and evolution. Advances in Science, 11(12), 160.Google Scholar
DeSilva, J. M. (2009). Functional morphology of the ankle and the likelihood of climbing in early hominins. Proceedings of the National Academy of Sciences, 106(16), 65676572.CrossRefGoogle ScholarPubMed
DeSilva, J. M. (2010). Revisiting the ‘midtarsal break’. American Journal of Physical Anthropology, 141(2), 245258.Google Scholar
DeSilva, J. M., Carlson, K. J., Claxton, A. G., Harcourt-Smith, W. E., McNutt, E. J., Sylvester, A. D., …, Berger, L. R. (2018). Australopithecus sediba – The anatomy of the lower limb skeleton of Australopithecus sediba. PaleoAnthropology, 2018, 357405.Google Scholar
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(6129).CrossRefGoogle ScholarPubMed
Dingwell, J. B., Cusumano, J. P., Cavanagh, P. R., & Sternad, D. (2001). Local dynamic stability versus kinematic variability of continuous overground and treadmill walking. Journal of Biomechanical Engineering, 123(1), 2732.CrossRefGoogle ScholarPubMed
Drapeau, M. S., & Harmon, E. H. (2013). Metatarsal torsion in monkeys, apes, humans and australopiths. Journal of Human Evolution, 64(1), 93108.CrossRefGoogle ScholarPubMed
Drerup, B., Hafkemeyer, U., Möller, M., & Wetz, H. H. (2001). Effect of walking speed on pressure distribution of orthopedic shoe technology. Der Orthopade, 30(3), 169175.CrossRefGoogle ScholarPubMed
Duckworth, R. A. (2009). The role of behavior in evolution: A search for mechanism. Evolutionary Ecology, 23(4), 513531.CrossRefGoogle Scholar
Dudkiewicz, M., Mackiewicz, P., Nowicka, A., Kowalczuk, M., Mackiewicz, D., Polak, N., …, Cebrat, S. (2005). Correspondence between mutation and selection pressure and the genetic code degeneracy in the gene evolution. Future Generation Computer Systems, 21(7), 10331039.CrossRefGoogle Scholar
Dunn, R. H., Tocheri, M. W., Orr, C. M., & Jungers, W. L. (2014). Ecological divergence and talar morphology in gorillas. American Journal of Physical Anthropology, 153(4), 526541.CrossRefGoogle ScholarPubMed
Edelman, G. M. (1974). The problem of molecular recognition by a selective system. In Studies in the philosophy of biology (pp. 4556). Palgrave.CrossRefGoogle Scholar
Edelman, G. M., & Gally, J. A. (2001). Degeneracy and complexity in biological systems. Proceedings of the National Academy of Sciences, 98(24), 1376313768.CrossRefGoogle ScholarPubMed
Faisal, A. A., Selen, L. P., & Wolpert, D. M. (2008). Noise in the nervous system. Nature Reviews Neuroscience, 9(4), 292303.CrossRefGoogle ScholarPubMed
Gabell, A., & Nayak, U. S. L. (1984). The effect of age on variability in gait. Journal of Gerontology, 39(6), 662666.CrossRefGoogle Scholar
Glazier, P. S., & Davids, K. (2009a). The problem of measurement indeterminacy in complex neurobiological movement systems. Journal of Biomechanics, 42(16), 26942696.CrossRefGoogle Scholar
Glazier, P. S., & Davids, K. (2009b). Constraints on the complete optimization of human motion. Sports Medicine, 39(1), 1528.CrossRefGoogle Scholar
Gök, H., Ergin, S., & Yavuzer, G. (2002). Kinetic and kinematic characteristics of gait in patients with medial knee arthrosis. Acta Orthopaedica Scandinavica, 73(6), 647652.CrossRefGoogle ScholarPubMed
Gould, S. J. (1977). Ontogeny and Phylogeny. Harvard University PressGoogle Scholar
Griffin, D., & Tversky, A. (1992). The weighing of evidence and the determinants of confidence. Cognitive Psychology, 24(3), 411435.CrossRefGoogle Scholar
Grillner, S. (1985). Neurobiological bases of rhythmic motor acts in vertebrates. Science, 228(4696), 143149.CrossRefGoogle ScholarPubMed
Haile-Selassie, Y., Saylor, B. Z., Deino, A., Levin, N. E., Alene, M., & Latimer, B. M. (2012). A new hominin foot from Ethiopia shows multiple Pliocene bipedal adaptations. Nature, 483(7391), 565569.CrossRefGoogle ScholarPubMed
Harcourt-Smith, W. E., Throckmorton, Z., Congdon, K. A., Zipfel, B., Deane, A. S., Drapeau, M. S., …, DeSilva, J. M. (2015). The foot of Homo naledi. Nature Communications, 6(1), 18.CrossRefGoogle ScholarPubMed
Harris, C. M., & Wolpert, D. M. (1998). Signal-dependent noise determines motor planning. Nature, 394(6695), 780784.CrossRefGoogle ScholarPubMed
Hatala, K. G., Demes, B., & Richmond, B. G. (2016). Laetoli footprints reveal bipedal gait biomechanics different from those of modern humans and chimpanzees. Proceedings of the Royal Society B: Biological Sciences, 283(1836), 20160235.CrossRefGoogle ScholarPubMed
Hausdorff, J. M., Edelberg, H. K., Mitchell, S. L., Goldberger, A. L., & Wei, J. Y. (1997). Increased gait unsteadiness in community-dwelling elderly fallers. Archives of Physical Medicine and Rehabilitation, 78(3), 278283.CrossRefGoogle ScholarPubMed
Howcroft, J., Lemaire, E. D., Kofman, J., & Kendell, C. (2016). Understanding responses to gait instability from plantar pressure measurement and the relationship to balance and mobility in lower-limb amputees. Clinical Biomechanics, 32, 241248.CrossRefGoogle ScholarPubMed
Huey, R. B., Hertz, P. E., & Sinervo, B. (2003). Behavioral drive versus behavioral inertia in evolution: A null model approach. The American Naturalist, 161(3), 357366.CrossRefGoogle ScholarPubMed
Hughes, J., Pratt, L., Linge, K., Clark, P., & Klenerman, L. (1991). Reliability of pressure measurements: The EM ED F system. Clinical Biomechanics, 6(1), 1418.CrossRefGoogle ScholarPubMed
Jensen-Seaman, M. I., & Hooper-Boyd, K. A. (2008). Molecular clocks: Determining the age of the human-chimpanzee divergence. In Encyclopedia of Life Sciences (ELS) online (pp. 16). New York: Wiley.Google Scholar
Ji, Q., Wu, W., Ji, Y., Li, Q., & Ni, X. (2021). Late Middle Pleistocene Harbin cranium represents a new Homo species. The Innovation, 2(3).CrossRefGoogle ScholarPubMed
Jordan, K., Challis, J. H., & Newell, K. M. (2007a). Walking speed influences on gait cycle variability. Gait & Posture, 26(1), 128134.CrossRefGoogle Scholar
Jordan, K., Challis, J. H., & Newell, K. M. (2007b). Speed influences on the scaling behavior of gait cycle fluctuations during treadmill running. Human Movement Science, 26(1), 87102.CrossRefGoogle Scholar
Jungers, W. L., Harcourt-Smith, W. E., Wunderlich, R. E., Tocheri, M. W., Larson, S. G., Sutikna, T., … Morwood, M. J. (2009). The foot of Homo floresiensis. Nature, 459(7243), 8184.CrossRefGoogle ScholarPubMed
Jungers, W. L., & Minns, R. J. (1979). Computed tomography and biomechanical analysis of fossil long bones. American Journal of Physical Anthropology, 50(2), 285290.CrossRefGoogle ScholarPubMed
Kernozek, T. W., LaMott, E. E., & Dancisak, M. J. (1996). Reliability of an in-shoe pressure measurement system during treadmill walking. Foot & Ankle International, 17(4), 204209.CrossRefGoogle ScholarPubMed
Kidd, R. S., O'Higgins, P., & Oxnard, C. E. (1996). The OH8 foot: A reappraisal of the functional morphology of the hindfoot utilizing a multivariate analysis. Journal of Human Evolution, 31(3), 269291.CrossRefGoogle Scholar
Kivell, T. L. (2015). Evidence in hand: Recent discoveries and the early evolution of human manual manipulation. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1682), 20150105.CrossRefGoogle ScholarPubMed
Kivell, T. L., Kibii, J. M., Churchill, S. E., Schmid, P., & Berger, L. R. (2011). Australopithecus sediba hand demonstrates mosaic evolution of locomotor and manipulative abilities. Science, 333(6048), 14111417.CrossRefGoogle ScholarPubMed
Klenerman, L., & Wood, B. (2006). The human foot: A companion to clinical studies. Springer Science & Business Media.CrossRefGoogle Scholar
Komar, J., Chow, J. Y., Chollet, D., & Seifert, L. (2015). Neurobiological degeneracy: Supporting stability, flexibility and pluripotentiality in complex motor skill. Acta Psychologica, 154, 2635.CrossRefGoogle ScholarPubMed
Kuzawa, C. W., & Bragg, J. M. (2012). Plasticity in human life history strategy: Implications for contemporary human variation and the evolution of genus Homo. Current Anthropology, 53(S6), S369S382.CrossRefGoogle Scholar
Laland, K. N., & Sterelny, K. (2006). Perspective: Seven reasons (not) to neglect niche construction. Evolution, 60(9), 17511762.CrossRefGoogle ScholarPubMed
Laland, K. N., Uller, T., Feldman, M. W., Sterelny, K., Müller, G. B., Moczek, A., …, Odling-Smee, J. (2015). The extended evolutionary synthesis: Its structure, assumptions and predictions. Proceedings of the Royal Society B: Biological Sciences, 282(1813), 20151019.CrossRefGoogle ScholarPubMed
Lande, R. (2009). Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation. Journal of Evolutionary Biology, 22(7), 14351446.CrossRefGoogle Scholar
Latash, M. L., Scholz, J. P., & Schöner, G. (2002). Motor control strategies revealed in the structure of motor variability. Exercise and sport sciences reviews, 30(1), 2631.Google Scholar
Lewontin, R. C. (2001). It ain‘t necessarily so: The dream of the human genome and other illusions. New York Review of Books.Google Scholar
Lockhart, T. E., & Liu, J. (2008). Differentiating fall-prone and healthy adults using local dynamic stability. Ergonomics, 51(12), 18601872.CrossRefGoogle ScholarPubMed
Lovejoy, C. O., Latimer, B., Suwa, G., Asfaw, B., & White, T. D. (2009a). Combining prehension and propulsion: The foot of Ardipithecus ramidus. Science, 326(5949), 7272e8.CrossRefGoogle Scholar
Lovejoy, C. O., Suwa, G., Simpson, S. W., Matternes, J. H., & White, T. D. (2009b). The great divides: Ardipithecus ramidus reveals the postcrania of our last common ancestors with African apes. Science, 326(5949), 73106.CrossRefGoogle Scholar
Lundberg, A., Goldie, I., Kalin, B. O., & Selvik, G. (1989a). Kinematics of the ankle/foot complex: Plantarflexion and dorsiflexion. Foot & Ankle, 9(4), 194200.CrossRefGoogle Scholar
Lundberg, A., Svensson, O. K., Bylund, C., Goldie, I., & Selvik, G. (1989b). Kinematics of the ankle/foot complex – Part 2: Pronation and supination. Foot & Ankle, 9(5), 248253.CrossRefGoogle Scholar
Lundberg, A., Svensson, O. K., Bylund, C., Goldie, I., & Selvik, G. (1989c). Kinematics of the ankle/foot complex – Part 3: Influence of leg rotation. Foot & Ankle, 9(6), 304309.CrossRefGoogle Scholar
Lundgren, P., Nester, C., Liu, A., Arndt, A., Jones, R., Stacoff, A., …, Lundberg, A. (2008). Invasive in vivo measurement of rear-, mid-and forefoot motion during walking. Gait & Posture, 28(1), 93100.CrossRefGoogle ScholarPubMed
MacLatchy, L., Gebo, D., Kityo, R., & Pilbeam, D. (2000). Postcranial functional morphology of Morotopithecus bishopi, with implications for the evolution of modern ape locomotion. Journal of Human Evolution, 39(2), 159183.CrossRefGoogle ScholarPubMed
Madar, S. I., Rose, M. D., Kelley, J., MacLatchy, L., & Pilbeam, D. (2002). New Sivapithecus postcranial specimens from the Siwaliks of Pakistan. Journal of Human Evolution, 42(6), 705752.CrossRefGoogle ScholarPubMed
Marigó, J., Minwer-Barakat, R., Moyà-Solà, S., & Boyer, D. M. (2020). First navicular remains of a European adapiform (Anchomomys frontanyensis) from the Middle Eocene of the Eastern Pyrenees (Catalonia, Spain): Implications for early primate locomotor behaviour and navicular evolution. Journal of Human Evolution, 139, 102708.CrossRefGoogle Scholar
Marigó, J., Roig, I., Seiffert, E. R., Moyà-Solà, S., & Boyer, D. M. (2016). Astragalar and calcaneal morphology of the middle Eocene primate Anchomomys frontanyensis (Anchomomyini): Implications for early primate evolution. Journal of Human Evolution, 91, 122143.CrossRefGoogle ScholarPubMed
Mason, P. H. (2010). Degeneracy at multiple levels of complexity. Biological Theory, 5(3), 277288.CrossRefGoogle Scholar
McClellan, D. A. (2000). The codon-degeneracy model of molecular evolution. Journal of Molecular Evolution, 50(2), 131140.CrossRefGoogle ScholarPubMed
McClymont, J., & Crompton, R. H. (2021). Repetition without repetition: A comparison of the Laetoli G1, Ileret, Namibian Holocene and modern human footprints using pedobarographic statistical parametric mapping. In Reading prehistoric human tracks (pp. 4166) Springer.CrossRefGoogle Scholar
McClymont, J., Pataky, T. C., Crompton, R. H., Savage, R., & Bates, K. T. (2016). The nature of functional variability in plantar pressure during a range of controlled walking speeds. Royal Society Open Science, 3(8), 160369.CrossRefGoogle ScholarPubMed
McClymont, J., Savage, R., Pataky, T. C., Crompton, R., Charles, J., & Bates, K. T. (2021). Intra-subject sample size effects in plantar pressure analyses. PeerJ, 9, e11660.CrossRefGoogle ScholarPubMed
McHenry, H. M., & Jones, A. L. (2006). Hallucial convergence in early hominids. Journal of Human Evolution, 50(5), 534539.CrossRefGoogle ScholarPubMed
Meldrum, D. J., Lockley, M. G., Lucas, S. G., & Musiba, C. (2011). Ichnotaxonomy of the Laetoli trackways: The earliest hominin footprints. Journal of African Earth Sciences, 60(1–2), 112.CrossRefGoogle Scholar
Moczek, A. P., Sultan, S., Foster, S., Ledón-Rettig, C., Dworkin, I., Nijhout, H. F., …, Pfennig, D. W. (2011). The role of developmental plasticity in evolutionary innovation. Proceedings of the Royal Society B: Biological Sciences, 278(1719), 27052713.CrossRefGoogle ScholarPubMed
Morrison, S. C., McClymont, J., Price, C., & Nester, C. (2017). Time to revise our dialogue: How flat is the paediatric flatfoot? Journal of Foot and Ankle Research, 10(1), 12.CrossRefGoogle ScholarPubMed
Morrison, S. C., Price, C., McClymont, J., & Nester, C. (2018). Big issues for small feet: Developmental, biomechanical and clinical narratives on children's footwear. Journal of Foot and Ankle Research, 11(1), 15.CrossRefGoogle ScholarPubMed
Myatt, J. P., Crompton, R. H., Payne-Davis, R. C., Vereecke, E. E., Isler, K., Savage, R., …, Thorpe, S. K. (2012). Functional adaptations in the forelimb muscles of non-human great apes. Journal of Anatomy, 220(1), 1328.CrossRefGoogle ScholarPubMed
Myatt, J. P., Crompton, R. H., & Thorpe, S. K. (2011). Hindlimb muscle architecture in non-human great apes and a comparison of methods for analysing inter-species variation. Journal of Anatomy, 219(2), 150166.CrossRefGoogle Scholar
Nester, C., Jones, R. K., Liu, A., Howard, D., Lundberg, A., Arndt, A., …, Wolf, P. (2007a). Foot kinematics during walking measured using bone and surface mounted markers. Journal of Biomechanics, 40(15), 34123423.CrossRefGoogle Scholar
Nester, C. J., Liu, A. M., Ward, E., Howard, D., Cocheba, J., Derrick, T., & Patterson, P. (2007b). In vitro study of foot kinematics using a dynamic walking cadaver model. Journal of Biomechanics, 40(9), 19271937.CrossRefGoogle Scholar
Neufuss, J., Hesse, B., Thorpe, S. K. S., Vereecke, E. E., D'Aout, K., Fischer, M. S., & Schilling, N. (2014). Fibre type composition in the lumbar perivertebral muscles of primates: Implications for the evolution of orthogrady in hominoids. Journal of Anatomy, 224(2), 113131.CrossRefGoogle ScholarPubMed
Odling-Smee, L., & Braithwaite, V. A. (2003). The role of learning in fish orientation. Fish and Fisheries, 4(3), 235246.CrossRefGoogle Scholar
Ouzounian, T. J., & Shereff, M. J. (1989). In vitro determination of midfoot motion. Foot & Ankle, 10(3), 140146.CrossRefGoogle ScholarPubMed
Oxnard, C. E., & Lisowski, F. P. (1980). Functional articulation of some hominoid foot bones: Implications for the Olduvai (Hominid 8) foot. American Journal of Physical Anthropology, 52(1), 107117.CrossRefGoogle ScholarPubMed
Parravicini, A., & Pievani, T. (2018). Continuity and discontinuity in human language evolution: Putting an old-fashioned debate in its historical perspective. Topoi, 37(2), 279287.CrossRefGoogle Scholar
Parravicini, A., & Pievani, T. (2019). Mosaic evolution in hominin phylogeny: Meanings, implications, and explanations. Journal of Anthropological Sciences, 97, 124.Google Scholar
Pataky, T. C., Caravaggi, P., Savage, R., Parker, D., Goulermas, J. Y., Sellers, W. I., & Crompton, R. H. (2008). New insights into the plantar pressure correlates of walking speed using pedobarographic statistical parametric mapping (pSPM). Journal of Biomechanics, 41(9), 19871994.CrossRefGoogle Scholar
Pataky, T. C., & Goulermas, J. Y. (2008). Pedobarographic statistical parametric mapping (pSPM): A pixel-level approach to foot pressure image analysis. Journal of Biomechanics, 41(10), 21362143.CrossRefGoogle ScholarPubMed
Pataky, T. C., Vanrenterghem, J., & Robinson, M. A. (2016). The probability of false positives in zero-dimensional analyses of onedimensional kinematic, force and EMG trajectories. Journal of Biomechanics, 49(9), 14681476.CrossRefGoogle Scholar
Paton, J., Bruce, G., Jones, R., & Stenhouse, E. (2011). Effectiveness of insoles used for the prevention of ulceration in the neuropathic diabetic foot: A systematic review. Journal of Diabetes and its Complications, 25(1), 5262.CrossRefGoogle ScholarPubMed
Pfennig, D. W., & McGee, M. (2010). Resource polyphenism increases species richness: A test of the hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1540), 577591.CrossRefGoogle ScholarPubMed
Pigliucci, M. (2009). An extended synthesis for evolutionary biology. Annals of the New York Academy of Sciences, 1168(1), 218228.CrossRefGoogle ScholarPubMed
Pigliucci, M., & Müller, G. B. (2010). Elements of an extended evolutionary synthesis. Evolution: The extended synthesis (pp. 317) MIT Press.Google Scholar
Prang, T. C. (2016). The subtalar joint complex of Australopithecus sediba. Journal of Human Evolution, 90, 105119.CrossRefGoogle ScholarPubMed
Price, C., McClymont, J., Hashmi, F., Morrison, S. C., & Nester, C. (2018). Development of the infant foot as a load bearing structure: Study protocol for a longitudinal evaluation (the Small Steps study). Journal of Foot and Ankle Research, 11(1), 19.CrossRefGoogle Scholar
Price, C. J., & Friston, K. J. (2002). Degeneracy and cognitive anatomy. Trends in Cognitive Sciences, 6(10), 416421.CrossRefGoogle ScholarPubMed
Price, P. W. (2005). Adaptive radiation of gall-inducing insects. Basic and Applied Ecology, 6(5), 413421.Google Scholar
Rein, R., Davids, K., & Button, C. (2010). Adaptive and phase transition behavior in performance of discrete multi-articular actions by degenerate neurobiological systems. Experimental Brain Research, 201(2), 307322.CrossRefGoogle ScholarPubMed
Riley, M. A & Turvey, M. T. (2004). The self-organizing dynamics of intentions and actions. American Journal of Psychology, 114, 160169.CrossRefGoogle Scholar
Root, M. L., Orien, W. P., & Weed, J. H. (1977). Normal and abnormal function of the foot. Clinical Biomechanics Corporation.Google Scholar
Rosenbaum, D., Hautmann, S., Gold, M., & Claes, L. (1994). Effects of walking speed on plantar pressure patterns and hindfoot angular motion. Gait & Posture, 2(3), 191197.CrossRefGoogle Scholar
Ruff, C. (2002). Variation in human body size and shape. Annual Review of Anthropology, 31, 211232.CrossRefGoogle Scholar
Ruff, C., Holt, B., & Trinkaus, E. (2006). Who's afraid of the big bad Wolff?:‘Wolff's law’ and bone functional adaptation. American Journal of Physical Anthropology 129(4), 484498.CrossRefGoogle Scholar
Ruth, A. A., Raghanti, M. A., Meindl, R. S., & Lovejoy, C. O. (2016). Locomotor pattern fails to predict foramen magnum angle in rodents, strepsirrhine primates, and marsupials. Journal of Human Evolution, 94, 4552.CrossRefGoogle ScholarPubMed
Schlichting, C. D., & Pigliucci, M. (1993). Control of phenotypic plasticity via regulatory genes. The American Naturalist, 142(2), 366370.CrossRefGoogle ScholarPubMed
Segal, A., Rohr, E., Orendurff, M., Shofer, J., O'Brien, M., & Sangeorzan, B. (2004). The effect of walking speed on peak plantar pressure. Foot & Ankle International, 25(12), 926933.CrossRefGoogle ScholarPubMed
Seifert, L., Komar, J., Araujo, D. & Davids, K. (2016). Neurobiological degeneracy: A key property for adaptations of perception and action to constraints. Neuroscience & Biobehavioral Reviews, 69, 159165.CrossRefGoogle ScholarPubMed
Seifert, L., Wattebled, L., Herault, R., Poizat, G., Adé, D., Gal-Petitfaux, N., & Davids, K. (2014). Neurobiological degeneracy and affordance perception support functional intra-individual variability of inter-limb coordination during ice climbing. PloS One, 9(2), e89865.CrossRefGoogle ScholarPubMed
Senut, B., Pickford, M., Gommery, D., Mein, P., Cheboi, K., & Coppens, Y. (2001). First hominid from the Miocene (Lukeino formation, Kenya). Comptes Rendus de lAcadémie des Sciences – Series IIA – Earth and Planetary Science, 332(2), 137144.Google Scholar
Shu, L., Hua, T., Wang, Y., Li, Q., Feng, D. D., & Tao, X. (2010). In-shoe plantar pressure measurement and analysis system based on fabric pressure sensing array. IEEE Transactions on Information Technology in Biomedicine, 14(3), 767775.Google ScholarPubMed
Slater, P. J (2020). The Dark Pattern: Towards a constraints-led approach to jazz trumpet. PhD thesis, Sydney Conservatorium of Music, University of Sydney, Australia.Google Scholar
Spoor, F., Leakey, M. G., & Leakey, L. N. (2010). Hominin diversity in the Middle Pliocene of eastern Africa: The maxilla of KNM-WT 40000. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1556), 33773388.CrossRefGoogle ScholarPubMed
Stacoff, A., Nigg, B., Reinschmidt, C., van den Bogert, A. J., & Lundberg, A. (2000). Tibiocalcaneal kinematics of barefoot versus shod running. Journal of Biomechanics, 33, 13871395.CrossRefGoogle ScholarPubMed
Stearns, S. C. (1989). The evolutionary significance of phenotypic plasticity. Bioscience, 39(7), 436445.CrossRefGoogle Scholar
Stolwijk, N. M., Duysens, J., Louwerens, J. W. K., van de Ven, Y. H., & Keijsers, N. L. (2013). Flat feet, happy feet? Comparison of the dynamic plantar pressure distribution and static medial foot geometry between Malawian and Dutch adults. PLoS One, 8(2), e57209.CrossRefGoogle ScholarPubMed
Su, J. L. S., & Dingwell, J. B. (2007). Dynamic stability of passive dynamic walking on an irregular surface. Journal of Biomechanical Engineering, 129(6), 802810.CrossRefGoogle Scholar
Taylor, A. J., Menz, H. B., & Keenan, A. M. (2004). The influence of walking speed on plantar pressure measurements using the two-step gait initiation protocol. The Foot, 14(1), 4955.CrossRefGoogle Scholar
Terrier, P., & Schutz, Y. (2005). How useful is satellite positioning system (GPS) to track gait parameters? A review. Journal of Neuroengineering and Rehabilitation, 2(1), 111.CrossRefGoogle ScholarPubMed
Tononi, G., Sporns, O., & Edelman, G. M. (1999). Measures of degeneracy and redundancy in biological networks. Proceedings of the National Academy of Sciences, 96(6), 32573262.CrossRefGoogle ScholarPubMed
Trinkaus, E., & Ruff, C. B. (1999). Diaphyseal cross-sectional geometry of Near Eastern Middle Palaeolithic humans: The femur. Journal of Archaeological Science, 26(4), 409424.CrossRefGoogle Scholar
Tsegai, Z. J., Skinner, M. M., Pahr, D. H., Hublin, J. J., & Kivell, T. L. (2018a). Systemic patterns of trabecular bone across the human and chimpanzee skeleton. Journal of Anatomy 232, 641656.CrossRefGoogle Scholar
Tsegai, Z. J., Skinner, M. M., Pahr, D. H., Hublin, J. J., & Kivell, T. L. (2018b). Ontogeny and variability of trabecular bone in the chimpanzee humerus, femur and tibia. American Journal of Physical Anthropology, 167(4), 713736.CrossRefGoogle Scholar
Vaillancourt, D. E., Sosnoff, J. J., & Newell, K. M. (2004). Age-related changes in complexity depend on task dynamics. Journal of Applied Physiology, 97(1), 454455.CrossRefGoogle ScholarPubMed
Van Emmerik, R. E., Ducharme, S. W., Amado, A. C., & Hamill, J. (2016). Comparing dynamical systems concepts and techniques for biomechanical analysis. Journal of Sport and Health Science, 5(1), 313.CrossRefGoogle ScholarPubMed
Venkataraman, V. V., Kraft, T. S., DeSilva, J. M., & Dominy, N. J. (2013a). Phenotypic plasticity of climbing-related traits in the ankle joint of great apes and rainforest hunter–gatherers. Human Biology, 85, 309328.CrossRefGoogle Scholar
Venkataraman, V. V., Kraft, T. S., & Dominy, N. J. (2013b). Tree climbing and human evolution. Proceedings of the National Academy of Sciencejs of the United States of America, 110(4), 12371242.CrossRefGoogle Scholar
Vereecke, E., D'Août, K., De Clercq, D., Van Elsacker, L., & Aerts, P. (2003). Dynamic plantar pressure distribution during terrestrial locomotion of bonobos (Pan paniscus). American Journal of Physical Anthropology, 120(4), 373383.CrossRefGoogle Scholar
Vereecke, E., Van Sint Jan, S., D'Août, K., Lescrenier, K., Van Gheluwe, B., & De Clercq, D. (2008). Functional anatomy of the foot. Part B: The ape foot. In D'Aout, K. (Ed.), Advances in plantar pressure measurements in clinical and scientific research (pp. 92109). Braunschweig: Shaker Publishing B.V.Google Scholar
Verrel, J., Pologe, S., Manselle, W., Lindenberger, U., & Woollacott, M. (2013). Exploiting biomechanical degrees of freedom for fast and accurate changes in movement direction: Coordination underline quick bow reversals during continuous cello bowing. Frontiers in Human Neuroscience, 7(157), 111.CrossRefGoogle Scholar
Via, S., & Lande, R. (1985). Genotype–environment interaction and the evolution of phenotypic plasticity. Evolution, 39(3), 505522.CrossRefGoogle ScholarPubMed
Wainwright, P. (1991). Ecomorphology: Experimental functional anatomy for ecological problems. American Zoologist, 31, 680693.CrossRefGoogle Scholar
Wallace, J., White, H., Augsburger, S., & Walker, J. (2021). Development of a method to produce a valid and reliable foot mask for plantar pressure evaluation in children with clubfoot. Journal of Pediatric Orthopaedics B, 30(3), 287295.CrossRefGoogle ScholarPubMed
Ward, C. V., Kimbel, W. H., & Johanson, D. C. (2011). Complete fourth metatarsal and arches in the foot of Australopithecus afarensis. Science, 331(6018), 750753.CrossRefGoogle ScholarPubMed
Warren, G. L., Maher, R. M., & Higbie, E. J. (2004). Temporal patterns of plantar pressures and lower-leg muscle activity during walking: Effect of speed. Gait & Posture, 19(1), 91100.CrossRefGoogle ScholarPubMed
Whitaker, J., & Bender, A. (2009). Degeneracy: A design principle for achieving robustness and evolvability. Journal of Theoretical Biology, 263(1), 143153.CrossRefGoogle Scholar
White, T. (2003). Early hominids – Diversity or distortion? Science, 299(5615), 19941997.CrossRefGoogle ScholarPubMed
Whittaker, E. C., Aubin, P. M., & Ledoux, W. R. (2011). Foot bone kinematics as measured in a cadaveric robotic gait simulator. Gait & Posture, 33(4), 645650.CrossRefGoogle Scholar
Willems, C., Stassijns, G., Cornelis, W., & D'Août, K. (2017). Biomechanical implications of walking with indigenous footwear. American Journal of Physical Anthropology, 162(4), 782793.CrossRefGoogle ScholarPubMed
Winkler, H. (1988). An examination of concepts and methods in ecomorphology. Proceedings of the International Orthopaedics Congress, 19, 22462253.Google Scholar
Wood, B., & Boyle, K., E. (2016). Hominin taxic diversity: Fact or fantasy? American Journal of Physical Anthropology, 159, 3778.CrossRefGoogle ScholarPubMed
Yang, S., Chiu, Y. L., Lin, C. C., & Chen, Y. H. (2005). Influence of walking speed to the peak plantar pressure response. In Seventh Symposium on Footwear Biomechanics, Cleveland, OH (unpublished abstract).Google Scholar
Zhu, H., Wertsch, J., Harris, G. & Alba, H., 1995. Walking cadence effect on plantar pressures. Archives of Physical Medicine and Rehabilitation, 76, 10001005.CrossRefGoogle ScholarPubMed
Zipfel, B., DeSilva, J. M., Kidd, R. S., Carlson, C. J., Churchill, S. E., & Berger, L. R. (2011). The foot and ankle of Australopithecus sediba. Science, 333(9) 14171421.CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. An example of the functional relationships between degeneracy, complexity, robustness and evolvability, after Whitaker and Bender 2009.