Small-world dynamics drove Phanerozoic divergence of burrowing behaviors

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Small-world dynamics drove Phanerozoic divergence of burrowing behaviors
https://doi.org/10.1130/G48523.1

                                                                                                                                              Manuscript received 21 July 2020
                                                                                                                                   Revised manuscript received 21 October 2020
                                                                                                                                          Manuscript accepted 11 January 2021

          © 2021 Geological Society of America. For permission to copy, contact editing@geosociety.org.

          Small-world dynamics drove Phanerozoic divergence of
          burrowing behaviors
          Andrea Baucon1,2*, Carlos Neto de Carvalho2,3, Fabrizio Felletti4, Gabriele Tosadori5 and Alexandre Antonelli6,7,8
          1
            ipartimento di Scienze della Terra dell’Ambiente e della Vita (DISTAV), Genova University, Corso Europa 52, 16132 Genoa, Italy
           D
          2
           Geology Office of C.M. Idanha-a-Nova, Naturtejo UNESCO Global Geopark, Avenida Zona Nova de Expansão, 6060-101 Idanha-
                  a-Nova, Portugal
          3
            Instituto Dom Luiz, Department of Geology, Lisbon University, Campo Grande, 1749-016 Lisbon, Portugal
          4
             Department of Earth Sciences, Milan University, Via Mangiagalli 34, 20133 Milan, Italy
          5
              Department of Medicine, Verona University, Policlinico GB Rossi, Piazzale L.A. Scuro 10, 37134 Verona, Italy
          6
               Royal Botanic Gardens, Kew, Richmond TW9 3AE, UK
          7
                Gothenburg Global Biodiversity Centre, Department of Biological and Environmental Sciences, University of Gothenburg,
                  Carl Skottsbergs gata 22 B, 413 19 Göteborg, Sweden
          8
                 Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK

          ABSTRACT                                                                                                            (Seilacher, 1953), hydrocarbon exploration (La
              Species of burrowing animals have changed substantially over evolutionary time scales,                          Croix et al., 2013, 2012; Bednarz and McIlroy,
          but, surprisingly, burrows display persisting morphological patterns throughout the Pha-                            2015), scientific drilling, and characterization
          nerozoic. Deep-sea burrows are geometrically patterned, whereas shallow-marine burrows                              of aquifers (Droser and O’Connell, 1992; Cun-
          display simpler morphologies. This divergence between burrow associations is one of the                             ningham et al., 2009). Ethology is central to
          central conundrums of paleontology, but it has never been quantitatively demonstrated, and                          this framework because trace fossils are mani-
          the organizing principles responsible for this structure remain unknown. We show that the di-                       festations of behavior, which is controlled by
          vergence of burrow associations has been shaped by small-world dynamics, which is proposed                          the environment; environmental parameters,
          as a major macroevolutionary force in marine environments. Using network analysis, our                              in turn, are strongly affected by water depth
          study reveals that the association patterns between burrow morphotypes in 45 paleontological                        (Seilacher, 1953; Ekdale, 1988; MacEachern
          sites span ∼500 m.y. Strong statistical support is demonstrated for a surprising association                        et al., 2012).
          pattern, according to which the data set is optimally partitioned into two subgroups of tightly                         Despite its popularity and intuitive recog-
          associated burrow types. These groups correspond to shallow- and deep-marine biomes. Our                            nition, the divergence hypothesis has never
          analysis demonstrates that across the Phanerozoic Eon, burrows did not assemble randomly                            been quantitatively tested, and the organizing
          nor regularly, following instead small-world assembly rules remarkably similar to those that                        principles that underpin it remain unknown.
          shape human social networks. As such, small-world dynamics deeply influenced gene flow                              This issue is addressed here by analysis of as-
          and natural variation in heritable behavior across evolutionary time.                                               sociation patterns of Phanerozoic trace fossils.
                                                                                                                              Our study tests the specific predictions of the
          INTRODUCTION                                                    hypothesis states that deep-sea associations of     divergence hypothesis that (1) association pat-
              Species of burrowing organisms have                         trace fossils have retained their distinctiveness   terns of trace fossils are inhomogeneous, i.e.,
          changed dramatically throughout the Phanero-                    from shallow-marine trace fossils throughout        trace fossils are associated neither randomly nor
          zoic, which comprises the past 541 m.y. of bio-                 most of the Phanerozoic (Seilacher, 1953, 1967,     regularly; and (2) any trace-fossil association is
          logical evolution on Earth. Nevertheless, bur-                  1978, 2007). In other words, the hypothesis as-     related to a specific biome, i.e., shallow or deep
          rows and other traces of organism-substrate                     serts that deep-sea trace fossils are morphologi-   marine. Accordingly, the first null hypothesis
          interactions (e.g., trails, trackways) have main-               cally different from shallow-marine trace fossils   is that trace fossils are randomly associated;
          tained similar morphologies throughout the                      (Fig. 1).                                           the second is that they are regularly associated;
          same time span, with each morphology being                          The quantum leap in the understanding           the third is that there is no correlation between
          associated with a specific environmental setting                of life-substrate interactions imparted by this     groups of associated traces and their environ-
          (Frey and Seilacher, 1980). In fact, one of the                 observation (MacEachern et al., 2012) led to        mental setting.
          fundamental hypotheses of paleontology con-                     the recognition of associations of trace fos-
          cerns the Phanerozoic divergence between shal-                  sils across time and space (i.e., ichnofacies;      METHODS
          low- and deep-sea trace fossil associations. This               Seilacher, 1953, 1967). As a consequence of             The ideal source data for quantitatively testing
                                                                          this recognition, trace fossils became a central    the divergence hypothesis are the data from which
              *E-mail: andrea@tracemaker.com                              tool in the reconstruction of ancient ecosystems    the divergence idea first stemmed ­(Seilacher,

              CITATION: Baucon, A., et al., 2021, Small-world dynamics drove Phanerozoic divergence of burrowing behaviors: Geology, v. 49, p. XXX–XXX, https://doi.
          org/10.1130/G48523.1

          Geological Society of America | GEOLOGY | Volume XX | Number XX | www.gsapubs.org                                                                                        1

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Small-world dynamics drove Phanerozoic divergence of burrowing behaviors
A
                                                                                                      D

                                                                                                                                                     Figure 1. Phanerozoic
                                                                                                                                                     divergence hypothesis.
           B                                     C                                                                                                   It predicts that simple
                                                                                              E                       F                              burrows (A–C) are found
                                                                                                                                                     in shallow-sea deposits,
                                                                                                                                                     and geometrically pat-
                                                                                                                                                     terned burrows (D–F) in
                                                                                                                                                     deep-sea settings. Scale
                                                                                                                                                     bars are 1 cm wide. (A)
                                                                                                                                                     Cruziana (Ordovician). (B)
                                                                                                                                                     Asteriacites (Triassic). (C)
                                                                                                                                                     Diplocraterion (Jurassic).
                                                                                                                                                     (D) Nereites (Cretaceous).
                                                                                                                                                     (E) Paleodictyon (Creta-
                                                                                                                                                     ceous). (F) Spirophycus
                                                                                                                                                     (Cretaceous). See Table
                                                                                                                                                     S1 (see footnote 1) for
                                                                                                                                                     specimen details.

          2007; Table S2 in the Supplemental Material1).                  that are equivalent; i.e., with the same number      ichnofossil network topology. The seafloor was
          This data set includes presence-absence data                    of nodes and average degree. We empirically          simulated by a unidimensional domain across
          of environmental proxies and 32 taxa of trace                   generated 1000 random networks using the             which ichnotaxa are distributed. The spatial
          fossils (ichnotaxa) in 45 sites, ranging from                   Erdős and Rényi (1959) model (Fig. S1A in            range of each taxon can change at discrete points
          Cambrian to Miocene in age. Each assemblage                     the Supplemental Material). To test the third        in time according to a defined set of rules: (1) a
          of the data set represents the work of animals that             hypothesis, subgroups are searched by using only     “specialist rule”, i.e., keeping a narrow spatial
          lived in the same biome, but it is not necessarily              the information encoded in the topology of the       range across time; or (2) a “generalist rule”, i.e.,
          an ichnocoenose. Using the framework of                         ichnofossil network; then the correlation between    keeping a wide range for the entire duration of
          network analysis (Baucon and Felletti, 2013;                    the detected subgroups and environmental             the simulation. At the end of the simulation, a
          Baucon et al., 2014, 2015), the source data table               proxies is tested. To detect subgroups, we applied   network was produced based on co-occurrence
          is translated into a network by representing                    the concept of modularity, which measures the        relationships between taxa, and the network was
          ichnotaxa as nodes and by connecting those taxa                 number of links falling within subgroups minus       compared to the ichnofossil network. Detailed
          that co-occur in at least one paleontological site.             the expected number in a random null model           methods and definitions are provided in the
          The resulting network (Fig. 2), herein named                    (Newman, 2006; Fortunato, 2010). By optimizing       Supplemental Material.
          the ichnofossil network, is made of 32 nodes                    modularity over possible subgroups of the studied
          (ichnotaxa), each of which is linked to 19.8 taxa               network, we determined whether there exist any       RESULTS AND DISCUSSION
          on average (average degree). To test the first                  natural partitions of its nodes (Newman, 2006;       Ichnofossil Network versus Random and
          and second null hypotheses, we compared the                     Blondel et al., 2008). We then evaluated whether     Regular Null Models
          topological properties of the ichnofossil network               ichnotaxa of each subgroup have a higher                 In the ichnofossil network, any two nodes
          with those of random and regular null models                    probability of being associated with shallow-        are connected by a minimum number of links
                                                                          marine proxies versus deep-marine proxies. The       (distance). For instance, the distance between
                                                                          probability of association was quantified using      Cosmorhaphe and Spirophycus is 1 because
              1
                Supplemental Material. Supplemental text,                 the Jaccard similarity and a χ2 test (Hammer and     the corresponding ichnotaxa are found in the
          7 supplemental figures, 3 supplemental tables,                  Harper, 2006).                                       same paleontological site(s) (Fig. 2). This im-
          and 4 files of Python code. Please visit https://
          doi.org/10.1130/GEOL.S.14120408 to access                           We propose a spatial model of ichnotaxa          plies that these ichnotaxa occupied the same
          the supplemental material, and contact editing@                 distribution to understand what biogeograph-         ancient biome because trace fossils cannot
          geosociety.org with any questions.                              ic distribution patterns are responsible for the     be transported; i.e., they represent the in situ

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Small-world dynamics drove Phanerozoic divergence of burrowing behaviors
the small-world measure ω (Telesford et al.,
                                                                                                                                 2011), which also considers clustering of an
                                                                                                                                 equivalent lattice. A network is deemed a “small
                                                                                                                                 world” if S > 1 (Humphries and Gurney, 2008),
                                                                                                                                 whereas values of ω close to zero denote small-
                                                                                                                                 world tendencies (Telesford et al., 2011). Values
                                                                                                                                 of these indices (Sichno = 1.10; ωichno = −0.11)
                                                                                                                                 show that the ichnofossil network falls within
                                                                                                                                 the small-world realm.
                                                                                                                                     Small-world networks are commonly charac-
                                                                                                   Figure 2. Ichnofossil         terized by community structure; i.e., they can be
                                                                                                   network. Nodes repre-         partitioned into subgroups of densely connected
                                                                                                   sent ichnotaxa, and links     nodes (Newman, 2006; Fortunato, 2010). Com-
                                                                                                   connect ichnotaxa that
                                                                                                   co-occur in same pale-        munity structure here does not refer to biological
                                                                                                   ontological site(s). Node     communities. Community structure allows the
                                                                                                   colors indicate modu-         third null hypothesis to be tested: i.e., there is no
                                                                                                   larity-based subgroups.       correlation between ichnoassociations, if pres-
                                                                                                   Refer to Table 1 for taxon
                                                                                                                                 ent, and their environmental setting. Optimiza-
                                                                                                   abbreviations. Trace fossil
                                                                                                   icons are modified from       tion of modularity reveals two natural subgroups
                                                                                                   Seilacher (2007).             in the ichnofossil network (Table 1; Fig. 2).

                                                                                                                                 Paleoenvironmental Significance of
                                                                                                                                 Subgroups
                                                                                                                                     We visualize the probability of association
                                                                                                                                 between subgroups and environmental proxies
                                                                                                                                 as configurations of nodes (Fig. 3). Accordingly,
                                                                                                                                 each node is an ichnotaxon, while its coordinates
                                                                                                                                 represent the probability of association with
                                                                                                                                 shallow-marine (x-coordinate) and deep-marine
                                                                                                                                 (y-coordinate) proxies. The diagonal segment
                                                                                                                                 connecting the upper right to the lower left cor-
          r­ ecord of biogenic activity (Buatois and Mán-                 number of links, i.e., they have equal degrees         ner of the plot contains the points of equal prob-
           gano, 2011). In the ichnofossil network, average               (Caporossi et al., 2003). Consequently, in a regu-     ability; hence, it separates the deep-sea from the
           distance is Lichno = 1.38, which is comparable                 lar network, the difference between the maxi-          shallow-sea realm. Results (Fig. 3) show that
           to the average distance of a random network                    mum and the minimum node degree (degree                (1) the shallow-sea realm contains subgroup A
           (Ler [er—equivalent Erdős-Rényi random net-                    variability) is Vreg = 0. This is not the case of      ichnotaxa only; (2) all taxa of subgroup B fall
           work] = 1.36). The ichnofossil network re-                     the ichnofossil network, the degree variability        into the deep-sea realm; (3) Chondrites is the
           sembles a random network by its short average                  of which is Vichno = 28 (Figs. S1B and S2A; see        only taxon of subgroup A that is placed in the
           distance, but, in parallel to the inadequacy of                Fig. S2B for additional topological differences        deep-sea realm. The results disprove the null
           describing social networks as random networks                  from the regular null model).                          hypothesis by showing that each group of asso-
           (Newman, 2000), there is a notable challenge                                                                          ciated traces pertain to a single biome, shallow
           using the random network as a model of the                     Node Subgroups                                         or deep marine. This supports the Phanerozoic
           ichnofossil network. In a true social network,                      Our results falsify the first and second null     divergence hypothesis. This result is surprising
           one’s friend’s friends are likely to be one’s                  hypotheses by showing that random and regu-            because this divergence persisted in spite of
           friends, but this does not occur in random net-                lar networks do not capture the topology of the        changing trace makers, e.g., the end-Permian
           works (Newman, 2000). This property is termed                  ichnofossil network. The ichnofossil network           extinction wiped out 96% of marine animal spe-
           “clustering” and is quantified by the clustering               displays characteristics from both (high cluster-      cies (Benton and Twitchett, 2003; Twitchett and
           coefficient C (Proulx et al., 2005). The aver-                 ing like regular lattices, and small average dis-      Barras, 2004).
           age clustering coefficient of the ichnofossil net-             tance like random networks). This is typical of            Chondrites cannot be considered a true out-
           work (Cichno = 0.85) is higher than the cluster-               small-world networks; i.e., networks presenting        lier because it is a typical environment-crossing
           ing coefficient of equivalent random networks                  a connection topology that is neither completely       ichnogenus (Baucon et al., 2020). The network
           (0.62), equaling the ratio between the average                 regular nor completely random (Watts and Stro-         subgroups A and B show high correspondence
           number of links and the total number of nodes                  gatz, 1998; Humphries and Gurney, 2008). The           with the shallow-sea Cruziana ichnofacies and
           (Newman, 2000). A similar result is obtained                   network G is said to be a small-world network          the deep-sea Nereites ichnofacies, respectively,
           by averaging the clustering coefficient of the                 if it has a similar average distance length to, but    which had been only qualitatively outlined in the
           1000 empirically generated Erdős-Rényi ran-                    greater clustering of nodes than, an equivalent        original studies (Seilacher, 1967, 1978, 2007).
           dom networks (Cer = 0.64; Fig. S1). The higher                 Erdős-Rényi random graph (Lg ≥ Ler; Cg >>              These results are confirmed by the χ2 test (Fig.
           degree of clustering in the ichnofossil network                Cer) (Humphries and Gurney, 2008). To test             S3) and hold at least from the Ordovician, given
           compared to a random network shows that the                    the small-world nature of the ichnofossil net-         that the source data set does not include any of
           ichnofossil network is not random.                             work, we calculated the small-worldness index          the characteristic Cambrian shallow-sea grapho-
               A regular network is the opposite of a ran-                S, which compares clustering and distance of a         glyptids (Crimes and Fedonkin, 1994; Uch-
           dom network (Newman, 2000); a completely                       given network to those of an equivalent random         man, 2003). Today, the ichnofacies approach
           ordered graph in which all nodes have the same                 network (Humphries and Gurney, 2008), as does          is regarded as a key tool in ­paleoenvironmental

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TABLE 1. NODE SUBGROUPS FOUND BY MODULARITY OPTIMIZATION ALGORITHM                                       and Schreiber, 2008). These results demon-
              Subgroup               Taxon                     Abbreviation                     First appearance datum           strate how the divergent, small-world structure
              A                Actinian burrows                     Ac                     Early Cambrian                        of Phanerozoic trace-fossil associations derives
                               Arthropod tracks                     Ar                     ?Neoproterozoic, Early Cambrian
                               Asteriacites                         As                     Cambrian                              from simple spatial patterns, i.e., most ichno-
                               Chondrites                           Ch                     Neoproterozoic                        taxa maintaining a narrow range (specialists)
                               Scolicids                            Sc                     Early Ordovician
                               Gyrochorte                           Gy                     Ordovician                            and few ichnotaxa with a wide and/or unstable
                               Cruziana                             Cr                     Early Cambrian                        range (generalists).
                               Phycodes                             Ph                     Early Cambrian
                               Diplocraterion                       Dp                     Early Cambrian
                               Asterosoma                           At                     Early Cambrian
                               Rhizocorallium                       Rh                     Early Cambrian                        CONCLUSIONS
                               Teichichnus                          Te                     Early Cambrian                            By integrating network analysis and global
                               Ophiomorpha                          Op                     Permian
                               Lockeia                              Lo                     Early Ordovician                      paleontological data, we quantitatively dem-
                               Curvolithus                          Cu                     Neoproterozoic                        onstrate that deep-sea trace fossils have been
              B                Nereites                             Nr                     Early Cambrian                        morphologically cohesive and distinguish-
                               Dictyodora                           Di                     Cambrian
                               Helminthoida                         He                     Cambrian                              able from shallow-marine ones for most of the
                               Cosmorhaphe                          Co                     Cambrian                              Phanerozoic.
                               Urohelminthoida                      Ur                     Ordovician
                               Paleomeandron                        Pl                     Late Cretaceous                           The divergence reported here has applied
                               Scolicia (meanders)                  Sm                     Early Ordovician                      implications for scientific research and for the
                               Spirophycus                          Sp                     Ordovician
                               Lophoctenium                         Lp                     Early Ordovician                      energy industry, which relies on paleoenviron-
                               Oldhamia                             Ol                     Early Cambrian                        mental analysis for identifying resource-bear-
                               Paleodictyon                         Pa                     Early Cambrian
                               Zoophycos                            Zo                     Cambrian                              ing deposits. This work settles a fundamental
                               Phycosiphon                          Py                     Ordovician                            paleontological hypothesis (Phanerozoic di-
                               Taenidium                            Ta                     Cambrian
                               Fucusopsis                           Fu                     Ordovician                            vergence) and method (ichnofacies approach),
                               Neonereites                          Ne                     Neoproterozoic
                               Spirorhaphe                          Sr                     Silurian                              proposed nearly 50 years ago (Seilacher, 1967,
                Note: Stratigraphic ranges are based on the literature (see references in the Supplemental Material [see text    1978, 2007).
              footnote 1]).                                                                                                          Our model shows that two universal eco-
                                                                                                                                 logical guilds—specialists and generalists—
                                                                                                                                 controlled the spatial distribution of burrow-
                                                                                                                                 ing behaviors across the Phanerozoic. It finds a
                                                                                                                                 parallel in the development of social networks,
                                                                                                                                 with most individuals associating with (making
                                                                                                                                 friends with) individuals who are geographically
                                                                                                                                 close (environment-specific taxa) and few mov-
                                                                                                                                 ing around (environment-crossing taxa) (New-
                                                                                                   Figure 3. Node layout         man, 2000).
                                                                                                   showing co-occurrence
                                                                                                                                     Burrow shape reflects the behavior of its
                                                                                                   probability between ich-
                                                                                                   notaxa and environmental      producer. By demonstrating the persisting di-
                                                                                                   proxies, as quantified by     vergence of burrow shape over evolutionary
                                                                                                   the Jaccard index. Nodes      time scales, this work suggests that small-
                                                                                                   correspond to taxa (see       world dynamics deeply influenced extended
                                                                                                   Table 1 for labels); links
                                                                                                   are not depicted for          phenotypes and ecosystem engineering, thus
                                                                                                   graphical clarity (refer to   controlling gene flow and natural variation
                                                                                                   Fig. 2 for links).            in heritable behavior across the Phanerozoic.
                                                                                                                                 This indicates that small-world dynamics has
                                                                                                                                 been a major, but hitherto neglected, macro-
                                                                                                                                 evolutionary force in marine environments for
                                                                                                                                 the Phanerozoic.

                                                                                                                                 ACKNOWLEDGMENTS
                                                                                                                                 We thank Lavinia Tunini, Øyvind Hammer, and Wolf-
                                                                                                                                 gang Eder for methodological discussions. Baucon is
          a­ nalysis, although some researchers have argued               logical measures of the ichnofossil network (av-       supported by the ALAN-X, CURIOSITY, and CAM-
                                                                                                                                 BIACLIMA projects of the University of Genova
           that it may lead to overgeneralized, low-resolu-               erage path length, clustering coefficient, density,    (Italy). Neto de Carvalho is supported by Naturtejo,
           tion interpretations (Goldring, 1993; MacEach-                 and degree; number of communities) are within          Empresa Inter-Municipal (EIM). Antonelli is sup-
           ern et al., 2007).                                             one standard deviation from the mean of 1000           ported by the Swedish Research Council, the Swedish
                                                                          model-generated networks (Fig. S7). The model          Foundation for Strategic Research, and the Royal
                                                                                                                                 Botanic Gardens, Kew (Richmond, UK). Naturtejo
          Biogeographic Distribution Patterns of                          displays the tendency to generate networks (1)
                                                                                                                                 UNESCO Global Geopark and Câmara Municipal de
          Burrowing Behaviors                                             with the average distance increasing slower than       Idanha-a-Nova provided the financial support to this
              The simple generalist and specialist rules of               the logarithm of the network size (Fig. S5A); (2)      paper. Baucon and Neto de Carvalho dedicate this
          our proposed model result in complex patterns                   with the average degree increasing linearly with       work to the memory of one of the greatest minds in
          of trace fossil association that are comparable                 the number of nodes (Fig. S5B); and (3) with           paleontology, Adolf Seilacher, with whom they had the
                                                                                                                                 privilege of sharing ideas that culminated in the pres-
          to those observed in the real-world ichnofossil                 high clustering (>0.8) and small distance (
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          Geological Society of America | GEOLOGY | Volume XX | Number XX | www.gsapubs.org                                                                                                 5

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