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SECTION 3. EARLY- STUDY: METHODS, STATUS, AND FRONTIERS

Chapter 10 Methods of Studying Early Theropod Flight

MICHAEL PITTMAN,1 ASHLEY M. HEERS,2 FRANCISCO J. SERRANO,3 DANIEL J. FIELD,4 MICHAEL B. HABIB,5 T. ALEXANDER DECECCHI,6 THOMAS G. KAYE,7 AND HANS C.E. LARSSON8

ABSTRACT The study of early theropod flight involves avialans as well as other pennaraptorans. It requires the study of that is familiar to the modern ornithologist, but also very different and alien. Early theropod flight therefore necessitates study methods that can incorporate what we know about sophisticated powered and unpowered flight in living while being mindful of the differences between them and the earliest theropod flyers. In this chapter we will survey key methods and approaches, covering their best-practice applications along the timeline of early theropod flight and priorities for future method development.

INTRODUCTION When trying to decipher early theropod flight, researchers are faced with substantial anatomi- Locomotion plays a central role in the lives of cal differences between modern flying birds like most vertebrates, and reconstructing locomotor pigeons and early birds like as well as behaviors of extinct taxa is key to understanding their closely related nonavialan relatives. In particu- some major evolutionary transitions—for exam- lar, extant volant birds have a large on the ster- ple, the origin of walking or swimming num, which anchors two main flight muscles, the whales. But how do we reconstruct locomotion pectoralis for downstroke and the supracoracoideus in extinct taxa when it is very difficult to com- for upstroke (George and Berger, 1966). Though pare them to modern forms? the supracoracoideus is in a ventral position, it is

1 Vertebrate Palaeontology Laboratory, Division of Earth and Planetary Science, the University of Hong Kong, Hong Kong. 2 College of Natural and Social Sciences, California State University, Los Angeles. 3 Institute, Natural History Museum of Los Angeles County, Los Angeles; and Real Academia Ciencias Exactas, Físicas y Naturales, Madrid. 4 Department of Earth Sciences, University of Cambridge, Cambridge. 5 Dinosaur Institute, Natural History Museum of Los Angeles County, Los Angeles. 6 Division of Natural Sciences, Mount Marty College, Yankton, SD. 7 Foundation for Scientific Advancement, Sierra Vista, AZ. 8 Redpath Museum, McGill University, Montreal. 278 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440 able to elevate and supinate (Poore et al., 1997a; few anatomical features, such as and/or Tobalske and Biewener, 2008) the because (e.g., Burgers and Chiappe, 1999; Nudds it loops through a donut-shaped triosseal canal and Dyke, 2010; Chiappe et al. 2019), (e.g., and attaches to the dorsal surface of the , Gatesy and Dial, 1996; Gatesy, 2001; Pittman et al., similar to a pulley. Archaeopteryx, in contrast, has 2013), the shoulder (e.g., Jenkins, 1993; Baier et no triosseal canal and no ossified sternum, but al., 2007; Navalón et al., 2018), or the supracora- some early avialans and possibly volant nonavialan coideus muscle (e.g., Poore et al., 1997b). Recent pennaraptorans have either feature or both in an efforts to leverage the locomotor variation among incipient form (Zhou and Zhang, 2002; Xu et al., nearly 11,000 living species (Prum et al., 2015; Gill 2003; Baier et al., 2007; Dyke et al., 2013; Zheng et and Donsker, 2017) using large-scale datasets to al., 2014; Pei et al., in press). Consequently, at least characterize aspects of the avian flight apparatus some of the flight muscles of many early avialans have begun to bear fruit. New analytical tech- and suspected volant nonavialan pennaraptorans niques are showing that yet more high-fidelity were probably not very large, and would have had flight-related soft-tissue details are hidden in the different configurations compared with extant very best preserved pennaraptorans, especially birds. What does that mean in terms of the loco- those from China (Falk et al., 2016; Wang et al., motor capacity of early birds and some nonavialan 2017; see Serrano et al., chap. 13). Advancements pennaraptorans? in early flight studies have greatly benefited from The study of early theropod flight engages tai- the evolutionary context provided by a range of lored methodologies with their own emphases to detailed phylogenetic analyses, the details of address the spectrum of form-function differences which are provided by Pittman et al. in chapter 2. along the line of descent from the first theropod Large-scale Avian Anatomical Datasets: flyers to modern living ones. Theropod aerial Seminal datasets like those by Greenewalt (1975) locomotion seems to have multiple origins, the or Hartman (1961) have been extremely helpful study of which involves anatomy that is very dif- in informing our understanding of early thero- ferent to modern birds. At the other end of the pod flight (e.g., Dececchi et al., 2016; Pei et al., in theropod flight timeline, the press), but their use has generally fallen out of involves looking at a much more refined set of favor in recent times. The reason for this may be flight-related avian features that allowed birds to that these datasets are often created from amal- adopt different flight styles, but not the sophisti- gamations of other datasets or sources, so that cated powered flight of living birds. In this chapter specific specimens are rarely scored for all rele- we will survey key methods and approaches vant measurements (Hartman, 1961; Greenewalt, adopted in studying early theropod flight, detail- 1975). A new generation of studies has begun to ing their best practice applications to the facets of broach this data gap to quantify anatomical vari- this iconic field of pennaraptoran . ation for key modules of the flight apparatus by using large comparative samples that draw on the majority of avian higher-order subclades. FORM-FUNCTION RELATIONSHIPS These studies have begun to yield form-function Substantial efforts to characterize the morphol- relationships that may provide new lines of ogy of early pennaraptoran theropods and inves- investigation into early flight. This includes work tigate their relationship with flight function on the furcula (Close and Rayfield, 2012) as well continue to greatly advance our knowledge of as on flight feathers (Feo et al., 2015) and skeletal early theropod flight. This ranges from numerous proportions (Field et al., 2013; Serrano et al., studies assessing the functional morphology of 2015). single taxa (Navalón et al., 2015; Xu et al., 2015; Feathers are among the most characteristic Wang et al., 2017) to work focusing on one or a avian specializations, but quantitative compari- 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 279

Microraptor Archaeopteryx Eopengornis Aves

*

Ornithothoraces

FLIGHT BARB ATTACHMENT noncrownlike

crownlike

FIG. 1. morphology across paravian phylogeny (modified from Feo et al., 2015). Early-diverging taxa (indicated by dashed pink lines) exhibit flight feather trailing edges characterized by narrow angles of barb-to-rachis attachment. The crownlike condition (broad angles of barb-to-rachis trailing edge attachment; blue dashed lines) arose on the internode subtending Ornithothoraces, and may have conferred a more flexible trailing edge of the wing during flight in order to increase feather-to-feather contact and maintenance of a coherent wing surface in flight during active downstrokes. Silhouettes from phylopic.org. sons between flight-feather morphology in living air during flight connect to the rachis at narrow and extinct total- birds are hampered by the attachment angles, providing a relatively inflexi- rarity of intact fossil feathers and the preserva- ble for stability during flight, whereas tion difficulty posed by their flexible feather barbs on the trailing edge of flight feathers con- vanes. A large comparative dataset examining nect to the rachis at broad angles of attachment, feather-barb geometry was successfully gener- providing a more flexible vane in order to main- ated and used to characterize macroevolutionary tain a coherent wing surface through feather-to- patterns in barb arrangement across the crown feather contact. These patterns are generally tree of life (Feo et al., 2015). Among other conserved across crown birds. In contrast to this observations, this study observed that crown pattern, deinonychosaurians, like , birds exhibit characteristic barb-to-rachis attach- and early-diverging volant avialans, like Archae- ment angles on the leading and trailing edges of opteryx, Confuciusornis, and Sapeornis, exhibit flight feathers (Feo et al., 2015). Primary feather trailing edge barbs with angles of attachment barbs on a wing’s leading edge that cut into the indistinguishable from the narrow angles of 280 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440 attachment of leading-edge barbs (fig. 1), sug- Used with caution, these constraints can poten- gesting that the trailing-edge vane flexibility— tially have comparable benefits in more mor- and associated benefits for maintaining a phologically disparate nonavialan paravians. An coherent trailing edge of the wing during flight— encouraging development to emerge from such did not exist in these taxa (Feo et al., 2015). By scaling studies is that relatively robust estimates contrast, more crownward avialans (e.g., Enan- of body mass can be reconstructed from the tiornithes) appear to have exhibited the crown- mostly fragmentary, isolated elements typically like trailing-edge condition, suggesting that preserved in the avialan fossil record (fig. 2) broad angles of trailing-edge barb-to-rachis (Louchart et al., 2009; Longrich et al., 2011; attachment arose on the internode-subtending Brocklehurst et al., 2012; Field, 2017). Of 13 Ornithothoraces and were inherited by the skeletal measurements investigated, 11 yielded ancestors of crown birds (fig. 1). This work sug- especially high correlations with body size (R2 gests that despite an early origin of flight-feather >0.9). Moreover, scaling equations for several asymmetry (Feduccia and Tordoff, 1979), “mod- elements (e.g., femur length; fig. 3) scale uni- ern” flight feathers arose at a later-diverging formly for both flying and flightless extant birds, point in paravian evolutionary history than pre- suggesting that these measurements are particu- viously recognized. Other aspects of feather larly appropriate for estimating body size in morphology, such as emargination and its ability extinct taxa for which flying potential is uncer- to offset the cost of slow flight also appear to tain (e.g., nonavian avialans). However, it is have been later developments in avian evolution important to be mindful of how anatomical dif- (van Oorschot et al., 2017), further stressing how ferences between extant and extinct taxa may the feathers of extant taxa are not identical to affect results. Beyond the obvious relationship those of the earliest avialans. between body mass and flying potential, body Body mass is one of the most critical param- mass is strongly associated with a host of impor- eters in flight studies (Norberg, 2002; Videler, tant physiological, ecological, and biomechani- 2005; Pennycuick, 2008; Tennekes, 2009). In cal parameters (Schmidt-Nielsen, 1984; Rayner, light of differing body mass estimates, inferences 1988; Pollock and Shadwick, 1994; Brown, 1995; of a particular fossil taxon’s flight potential could Ahlborn, 2000; Gillooly et al., 2001; Gillooly et differ radically. The dependence of functional al., 2002; Campione and Evans, 2012; Smith, inferences on body mass places a premium on 2012; Berv and Field, 2018), parameters that the attainment of accurate and precise estimates underscore the importance of robustly estimat- of fossil body size in paravians. Recent work ing body size in paleobiological studies of aimed at improving methods for paravian body extinct fossil taxa. size estimation has focused on the development Hidden flight-Informative Fossilized of multivariate and bivariate equations for body Soft Tissue Data: Newly available analytical size estimation based on avian skeletal propor- techniques in modern paleontology have enabled tions (Field et al., 2013; Serrano et al., 2015). In more attention to be given to the discovery of fos- addition to providing scaling equations for the sil soft tissues, including soft tissues directly estimation of mean body size in crown birds and related to flight capability and performance. The nonavian avialans from skeletal measurements, feather impressions found in Archaeopteryx was these studies represent the first avian skeletal the key evidence used to suggest that early birds studies to explicitly provide equations for 95% were flight capable (Wellnhofer, 2009). Raking prediction intervals on body mass estimates, light for Archaeopteryx feather impressions has providing better-informed constraints on uncer- now given way to direct microscopic analysis of tainty in fossil avialan body size estimates and feathers, such as the Chinese feathered . their resulting functional hypotheses (fig. 2). Barbs are easily visualized with white light but 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 281 3 ) + 3.05 2 ) + 1.93 2 er t width 1 1 c oid sha f 0 ln(BM) = 2.55(ln H D ln(BM) = 2.26(ln CS W a c 0 = 0.9344 = 0.9316 o r 2 2 ln ( shaft width) ln (humerus diameter) R C R Humerus diame t

6 4 2 0 8 6 4 2 8 ln (body mass) (body ln ln (body mass) (body ln 10 10 4 e 3 ) + 0.38 ) - 0.83 C e a en c T 3 e r en c e r 2 data OLS t interval 95% con dence 95% prediction interval cum f 2 cum f 1 ln(BM) = 2.35(ln ln(BM) = 2.52(ln H C = 0.9209 1 = 0.9581 2 arsus ci r 2 R ln (tarsus circumberence) T Humerus ci r R ln (humerus circumference)

8 6 4 2 0 8 6 4 2 0 mass) (body ln ln (body mass) (body ln 10 10 5 6 5 aL) - 3.15 5 T iL) - 5.88 4 T 4 4 3 3 ln(BM) = 2.31(ln ln (tarsus length) ln (femur length) ln(BM) = 2.85(ln FL) - 4.84 3 ln(BM) = 2.72(ln 2 ln (tibia length) = 0.9004 = 0.6485 = 0.8593 2 2 emur length 2 arsus length ibia length R F R T R T 2 <0.9 are highlighted in pink. in pink. highlighted <0.9 are

2

8 6 4 2 0 5 0

ln (body mass) (body ln 10 mass) (body ln 10 8 6 4 2 0

10 ln (body mass) (body ln 4 2 2 ) - 3.12 ) + 2.60 a D T 3 1 1 er er 2 0 0 oid max length ln(BM) = 2.40(ln ln(BM) = 2.53(ln F D ln(BM) = 3.08(ln CLL) - 5.19 a c ln (tarsus diameter) ln (femur diameter) = 0.9344 = 0.9304 = 0.9301 2 2 2 emur diame t o r arsus diame t F R R R C ln (coracoid lateral length) T

8 6 4 2 0

ln (body mass) (body ln 8 6 4 2 10 ln (body mass) (body ln 8 6 4 2 0 10 mass) (body ln 10 4 3 5 ) - 0.15 3 2 e 4 en c >0.9 are highlighted in blue; equations with R with equations in blue; highlighted >0.9 are 2 e r 2 1 oid HAF length) 3 cum f a c o r ln(BM) = 2.41(ln F C ln(BM) = 2.09(ln HL) - 2.84 oid HAF length 1 c 2 ln(BM) = 2.45(ln HAF) + 1.99 0 a c ln (humerus length) = 0.9399 = 0.9525 2 = 0.9892 ln ( 2 emur ci r ln (femur circumference) o r 2 R Humerus length Bivariate scaling equations for crown birds for 13 skeletal measurements, including 95% prediction intervals (modified from Field et al., 2013). et Field al., intervals (modified 95% prediction from including measurements, 13 skeletal for birds crown for scaling equations Bivariate F R R C

2.

6 4 2 0 8 6 4 2 0 8

ln (body mass) (body ln 10 mass) (body ln 10 8 6 4 2 ln (body mass) (body ln FIG. FIG. Equations with R with Equations 282 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440

12

10

8

6 FL Ln(Mass [g]) 4

2

0 1 2 3 4 5 6 Ln(FL [mm]) FIG. 3. Example of a bivariate scaling equation for femur length (D.J. Field, unpublished data) illustrating virtually invariant scalingSupp. equations Fig. 2A for flying (blue) and flightless (pink) extant bird taxa. Datasets such as this will be useful for estimating live body mass for extinct avialans with unknown flying potential. laser-stimulated fluorescence (LSF) is now capable first quantifiable body outline of the early-diverg- of bringing out barbule structure by fluorescing ing paravian (Wang et al., 2017) (see sediment matrix to backlight nonfluorescent car- Pittman et al., chapters 1 and 2). The latter study bon films comprising fossil feathers (Kaye et al., revealed the wing’s leading edge shape as well as 2015, 2019; Wang et al., 2017; to a lesser extent arrangement of the feathers from the leading to under UV: Hone et al., 2010). This application of trailing edge, providing the refined direct data of LSF has important potential in reappraising wing span and (= wing) surface (Wang et al., known fossil feather diversity (Lefèvre, 2020; Xu 2017). In chapter 13 of this volume, Serrano et al. 2020) and testing ideas of the evolution of feather used direct nonfeather-based soft-tissue data to rigidity and integrity that directly impact recon- refine calculations of flight performance using structions of early flight. Neutron imaging also mechanically informed morphospace analysis for has the potential to contribute meaningful new the first time. data in the study of fossil feathers. While synchro- The increasingly common use of nondestruc- tron elemental analysis has trouble with atomic tive imaging in the study of the mostly skeletal numbers below silicon (Brown and Waychunas, portions of fossil birds provides an opportunity to 2004), neutrons work best on carbon and other develop augmented imaging protocols that can lower atomic number elements. This makes it a visualize and document preserved soft tissues, unique elemental technique compared to alterna- even before preparation (sensu Abel et al., 2012. tives for imaging soft tissues. and Schilling et al., 2014). Alternative imaging The UV lamp has now advanced to high power approaches like neutron imaging and proven soft- near UV wavelength lasers capable of fluorescing tissue imaging methods like LSF all have a role to virtually all minerals. This allows clarifying osteol- play in this area. However, new analytical tech- ogy (Tischlinger and Unwin, 2004; Foth et al., niques also have a role in further curating existing 2014; Rauhut et al., 2018) and has produced the specimens, such as by clarifying the integrity of 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 283 suspect fossils. For example, the extent of prior tion in well-preserved feathered fossils (Welln- repair work can be clarified using regular and syn- hofer, 2009; Chiappe et al., 2014). chrotron x-rays (Rowe et al., 2001; Cau et al., Morphospaces relating Mb with B and/or the 2017) and fluorescence imaging like LSF and UV length of the deltopectoral crest of the humerus (Kaye et al., 2015; Eklund et al., 2018). (DPC) allow the flapping pattern of early birds to be approximated (Serrano and Chiappe, 2017). For a given M and B, modern birds that fly with alter- Theropod Early Flight Performance b nating flapping and periods have shorter In-depth functional morphology knowledge DPCs than birds with a stricter flapping pattern. of many of the earliest flying theropods as well as Based on lever theory (Alexander, 2003), the latter evolutionary context afforded by an impressive birds have higher mechanical advantage for moving legacy of phylogenetic analyses (see chapter 1) the wing faster—hence flapping it more fre- has provided the basis for efforts to estimate quently—than the former ones. This approach pro- early theropod flight performance. Our knowl- vided support for a flight pattern less dominated by edge of flight performance of early birds has dra- wing flapping in the early-diverging pygostylian matically increased in recent years, including the Sapeornis (Serrano and Chiappe, 2017). In a similar reconstruction of flight styles that we are familiar way, estimations showed that enantiornithines Con- with today, such as thermal soaring (Serrano and cornis and had short wings in relation to Chiappe, 2017), as well as support for powered their body mass and DPC, suggesting that they flew flight potential in a number of nonavialan thero- strictly using flapping flight with no gliding phases pod taxa (Pei et al., in press). Herein we cover in steady flight (Serrano et al., 2018). In such a three of the most powerful approaches available: study, a combined analysis of the three basic vari- mechanically informed morphospace analysis, ables allowed bounding flight to be specifically first-principles-based modeling and interactive inferred in and Eoalulavis. musculoskeletal modeling and simulation. Valuable information about flying behavior of Mechanically Informed Morphospace extinct birds also can be obtained from the cal- Analysis: In the previous section, body mass culation of the (i.e., WL = Mb/SL) 2 (Mb) was mentioned as a key variable known to and the aspect ratio (AR = B /SL). While AR pro- influence flight in living birds and this is also vides information relative to and thrust true of wing span (B) and lift (= wing) surface (Rayner, 1993; Swaddle and Lockwood, 2003; (SL) (Norberg, 2002; Videler, 2005; Pennycuick, Meseguer and Sanz-Andres, 2007; Shyy et al., 2008; Tennekes, 2009). Using a conservative 2008), the WL provides information about the approach that recognizes the statistical, phyloge- flight speed and turn radius (Von Mises, 1945; netic, ecological, and taphonomic sources of Norberg, 2002; Tennekes, 2009). In the case of error associated with early bird fossils, these key Sapeornis, the relatively low AR of its wings indi- flight variables can be used to infer flight perfor- cated a continental (= thermal) soaring capacity mance in early birds. By carefully selecting fore- instead of (Serrano and Chi- and hind-limb measurements for each appe, 2017). In other cases, the low values of AR early-diverging taxon, multiple regressions can and WL estimated for Junornis and Orienantius be obtained that minimize these sources of error suggested that these enantiornithines may have as well as predictive error (Serrano et al., 2015, been capable of rapid takeoff and tight turns (Liu 2017). Reliable estimates of Mb, B, and SL from et al., 2017, 2019). this approach enable direct comparisons between In many cases the aerial inferences obtained early and modern birds in morphospaces that from morphospaces can be validated by con- include these variables. Fine estimates of B and structing aerodynamic models based on the esti- SL can also be obtained from outline reconstruc- mates of Mb, B, and SL. Such models allow the 284 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440 checking of the power margin during flapping takeoff is a universal trait of flying . The flight and gliding patterns. This type of analysis second assumption is conservative because it supported conclusions that early birds like requires only that there be at least one motion Sapeornis and Gretcheniao were incapable of gen- set that provides sufficient wing amplitude for erating sufficient power for sustaining prolonged flight. This is therefore more conservative than flapping flight (Serrano and Chiappe, 2017; Chi- specifying a particular flight stroke. Lift from appe et al. 2019), and also that Concornis and the hindwings, in this configuration, potentially Eoalulavis could improve their efficiency of contributes to stability and control during transport switching from continuous flapping to flight, as the lift would be oriented laterally, bounding (Serrano et al., 2018). rather than upward. It would not contribute to First-Principles-Based Modeling: These weight support or thrust, which we assume approaches to estimating flight performance comes only from the (and potentially rely on fundamental properties of aerodynam- the , but only for pitch authority). ics and morphology that apply to all flying sys- Modeling approaches of this kind are particu- tems. They typically utilize a comparative larly useful for determining those variables that framework, because calculations of exact per- have a particularly large effect on the perfor- formance values in fossil taxa are difficult to mance outcome of interest. In the case of our make with precision without a very large num- microraptorine flight performance work, we ber of variables that are often not directly found that maximal wing loading and specific lift observable in fossils. The relative differences in capacity are strong criteria for evaluating flight performance, however, can often be robustly performance in a comparative dataset of fossil inferred using first principles approaches. taxa. These two criteria were devised from theo- In the context of flight origins and evolution, retical and in vivo work on extant avians and modeling is often best approached from a present easily testable benchmarks that accu- dynamics perspective. Reconstructing kinemat- rately model the minimal thresholds needed to ics with confidence requires a more species- discern volant from flightless taxa (Meunier, specific approach, such as simulation or 1951; Marden, 1987; Livezey, 1992; Guillemette range-of-motion analysis from analogous living and Ouellet, 2005) taxa (see Interactive Musculoskeletal Modeling For example, for taxa without complete pri- and Simulation Method below). Typically, mary feathers preserved, feather length was dynamics models must still make some kine- modeled on closely related taxa and wing area matic assumptions. More conservative kine- was calculated based on the methods presented matic assumptions will yield more robust in Dececchi et al. (2016). Geometric measure- conclusions regarding dynamics. As an exam- ments were all taken using standard digital cali- ple, in our recent work on microraptorine flight pers. was taken as 2.1× the summation dynamics (see Dececchi et al., chapter 11), we of the lengths of the humerus, ulna and metacar- made only two kinematic assumptions: (1) the pal II, and the longest distal primary (Dececchi hind limbs generated the launch prior to the et al., 2016). Wing was taken as 65% of the wing being engaged, (2) there was a sufficient longest distal primary length (Dececchi et al., range of motion to generate a viable flight 2016). Wing loading is based on body weight stroke for climb out. For all taxa, we used only estimated as per above (kg) over wing area (cm2). configurations in which the hind limbs (and Specific lift, here used as the lift force generated therefore hind wings, where present) were held in the vertical plane is based on Marden’s model under the body in a vertical configuration. The (Marden, 1987). This model has been suggested first of these assumptions is conservative to underestimate maximum vertical force pro- because the use of the stance limbs to engage duced (Buchwald and Dudley, 2010), thus these 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 285 values may represent a conservative estimate of To improve optimization of the data we force produced in these taxa. Specific lift = FMR screened the coelurosaurians based on their × Po,m × (L/P) where FMR is the flight muscle presence of vaned feathers, which are integral to ratio, which is assigned at a constant value of the production of aerodynamic forces; terminals 10% of body weight across all taxa examined. for which feather condition is unknown were This is at the lower range of the values seen in considered to have the same state as their ances- volant birds and is likely a significant overestima- tor, which is the condition predicted by our tion for all nonparavian taxa based on recent 3D recent phylogenetic hypothesis (Pei et al., in modeling work (Allen et al., 2013). The methods press). If a taxon showed both wing-loading val- used here will help us to refine these estimates by ues below 2.5 gcm-2 (which has been estimated producing more accurate body-outline recon- to be the upper limit for flight in extant birds: structions that place quantitative constraints on Meunier, 1951; Guillemette and Ouellet, 2005) as musculature. Po,m is the maximum muscle well as the potential to generate lift values more mass-specific power output based on values from than 9.8 Nkg-1, we suggest that this taxon has the extant birds. As Po,m is unknown for nonavialan potential to achieve takeoff and powered flight. theropods, three separate calculations were made We use linear parsimony to reconstruct wing that span the range of Po,m values that could loading and specific lift values over our tree have reasonably been expected (225, 250, and topology. In this project we use the upper and 287 Wkg-1). However, we use the two extremes lower limits recovered for Microraptor to see (225 and 287 Wkg-1) to reconstruct minimum whether this affects the results of surrounding and maximum flying ability. We assume that all nodes, if at all. We will also consider tail area and thrust is lift generated, and so the estimates of shape, mostly for its role in determining the cen- required power for flight essentially relate to the ter of lift and providing pitch stability, adopting power that must be exerted against drag to gen- the approach previously utilized by one of the erate sufficient lift for flight. Drag can contribute authors (MBH – see Han et al., 2015). In chapter to thrust, but this is a relatively sophisticated 11, Dececchi et al. develop this approach further dynamic, and lift-generated thrust dominates in by presenting the first ontogenetic trajectory of living flying animals in the size range relevant to flight and flapping-related behaviors in the non- our study. The value of 225 Wkg-1 was suggested avialan theropod Microraptor, which are directly by Marden (1994) as the mean value for burst compared to similar curves produced for extant flight in birds. Work by Guillemette and Ouellet birds (Heers and Dial, 2012). (2005) suggested that a range between 225 and Interactive Musculoskeletal Modeling 250 Wkg-1 more accurately mimics values seen and Simulation: This method has been widely in the Common Eider, a bird with short wings used to study human locomotion, and adapted for that displays some of the highest wing-loading use with extant animals such as chimpanzees values seen in extant birds, two features that (O’Neill et al., 2013) and extinct animals such as resemble the condition seen in the extinct taxa Tyrannosaurus rex (Hutchinson et al., 2005) and examined here. The value of 287 Wkg-1 was Mussaurus (Otero et al., 2017). Musculoskeletal based on the values calculated for Chukar par- modeling and simulation use programs like SIMM tridges (Askew et al., 2001), a short burst flight (Software for Interactive Musculoskeletal Model- taxon previously used as a model for early flight ing; Musculographics, Inc., http://www.musculo- in theropods. Our work here will help refine graphics.com/) and OpenSim (http://opensim. these estimates and help us constrain these val- stanford.edu/) (Delp et al., 2007) to construct ues even further. L/P is calculated from: digital, musculoskeletal models and then simulate log10 (L/P) = −0.440 log10 muscle mass + different behaviors to analyze muscle function or 0.845 log10 (wingspan/2) − 2.239 determine, for example, whether muscles would 286 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440

High-speed video and/or propeller model CT scanning, Mimics, Meshlab, Maya: Muscle forces Skeletal puppet Static Optimization

Net joint moments

Inverse Force plate dynamics Aerodynamic force Ground reaction force

Kinematics XROMM

Mimics, Matlab: Distribution of mass SIMM, OpenSim

FIG. 4. Interactive musculoskeletal modeling and simulation involves 4 steps: (1) Computed tomography (CT) scanning, (2) dissection, (3) measurement of kinematics, and (4) measurement of all external forces. Modified from Heers, et al., 2016, 2018. be strong enough to perform a particular behav- dinate systems (Grood and Suntay, 1983) are typi- ior. For extant animals, musculoskeletal modeling cally defined anatomically, either based on the involves four steps (fig. 4): anatomy of the bones articulating at the joint or 1. Computed Tomography Scanning: CT based on the morphology of the joint itself, though scanning of the in question, to construct they can also be defined kinematically (i.e., joint a skeletal “puppet.” This three-step process location and axes of rotation can be calculated involves: based on how bones are translated and rotated Isolating Skeletal Elements: Importing CT about each other during locomotion). slices into programs such as Mimics (Materialise, Determining Mass Distribution: Once the Inc., Leuven, Belgium) or Osirix/Horos (Rosset skeletal “puppet” is constructed, the distribu- et al., 2004), and using a density threshold to iso- tion of mass must be quantified for each move- late skeletal elements (e.g., wing bones in a bird), able body segment. Mimics, for example, can which are then saved as three-dimensional be used to digitally segment the animal into objects (e.g., .obj files). hind limb, trunk, brachial, antebrachial, and Constructing a Hierarchical Joint Coordinate Sys- manual segments, depending on the animal tem: This is often done by importing the skeletal and behavior in question. Each segment elements into Maya (Autodesk; http://autodesk. includes all tissues associated with that seg- com/) to align and link bones together through ment (bones, muscles, skin, fat, etc.). Assuming joints. A “zero” or resting position and coordinate a tissue density of 1060 kgm-3, a custom script systems for each joint must be defined. Joint-coor- (Allen et al. 2013) can then calculate the mass, 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 287 centre of mass, and inertial tensor for each reaction forces are recorded by force plates, body segment, based on its volume. These val- whereas fluid dynamic forces may be calculated ues determine the inertial properties of each using techniques like PIV (particle image velo- moveable segment. cimetry) (Tobalske and Dial, 2007) and “pro- 2. Dissection: This is done to add represen- peller models” (Heers et al., 2011; Dial et al., tations of muscles to the skeletal model. Model 2012), or measured using newly developed muscles, added in SIMM, are specified by: Aerodynamic Force Platforms (Lentink et al., Muscle Geometry: Origin(s), insertion(s), and 2015). For each force, a magnitude, direction, path(s) between them. “Via points” or “wrapping and location must be provided. Magnitude, objects” can be added to prevent the muscle from direction, and sometimes location vary through passing through bone. a stroke or stride cycle. Muscle Architecture: Optimal fibre length In short, steps 1 and 2 result in the construc- (typically taken as the length of muscle fascicles tion of an anatomical (musculoskeletal) model, at rest: Zajac, 1989) and average pennation angle, and steps 3 and 4 involve collecting kinematic which are important determinants of muscle and kinetic data, which are required for simula- strain (changes in length) and stress (force per tion. Once a musculoskeletal model is con- unit physiological cross-sectional area). structed and the necessary experimental data are Maximum Isometric Muscle Force: This is collected, various types of simulations can be calculated from the physiological cross-sec- performed in OpenSim: tional area of the muscle (area perpendicular Muscle Moment Arms: At the most basic to muscle fibres). level, the musculoskeletal model and joint kine- Tendon Slack Length: This is the length beyond matics can be used to calculate muscle moment which a muscle’s tendons begin resisting stretch arms through a stroke or stride cycle. The and producing force; this essentially specifies moment arm of a muscle indicates (a) what how much force is produced actively, by muscle action it would perform if it were activated, and fibers contracting, versus passively, by tendon(s) (b) how effective it would be at performing that being stretched. Tendon slack length is calcu- action, because a muscle’s ability to transform lated using an algorithm (Manal and Buchanan, force into bone movement depends both on 2004) that analyzes the shortening and lengthen- muscle force (which is proportional to muscle ing behavior of muscle-tendon units over a large size) and the length of the muscle’s moment arm. range of motion. Thus, musculoskeletal models are useful tools for For more complex (dynamic) simulations, predicting muscle function(s). physiological properties such as maximal con- Static Simulations: These take simulations tractile velocity, force-velocity relationships, one step further by calculating the timing and level and activation-deactivation dynamics are of muscle activations during the movement of included as well. interest. First, inverse dynamics uses the musculo- 3. Measurement of Joint Kinematics: For skeletal model, kinematics, and external loads pro- some animals and behaviors, this is accom- vided to calculate the net joint moments that would plished with high-speed visible light video. For be required to produce the simulated motion. A birds and/or behaviors involving rapid move- static optimization routine then resolves the net ment, this may require X-ray Reconstruction of moments into individual muscle moments (muscle Moving Morphology (www.xromm.org). force times muscle moment arm) at each time step 4. Measurement of All External Forces by minimizing the sum of squared muscle activa- Acting on the Animal: In addition to grav- tions. This type of simulation can be used for a vari- ity, this may include ground reaction, aerody- ety of purposes—for example, to compare simulated namic, and/or hydrodynamic forces. Ground muscle activations with activations recorded in vivo 288 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440 and thereby validate a model, to more explicitly kinematic (i.e., the wing stroke) and/or kinetic determine muscle function (which depends not (i.e., aerodynamic force production) properties only on muscle moment arms, but also on muscle can be altered to assess their effects on locomo- activation and joint kinematics), or to determine tion or muscle performance. Musculoskeletal whether the modeled muscles are strong enough to modeling and simulation thus allow for a more drive various behaviors. One disadvantage of static explicit examination of form-function relation- simulations is that they consider each time step ships, by allowing anatomical, kinematic, kinetic, independently, and cannot account for time-depen- and/or physiological features to be individually dent physiological properties such as force-velocity adjusted and their effects on locomotion deter- relationships or activation-deactivation dynamics. mined. Consequently, this approach is also one At this point in time, OpenSim’s static optimization of the most quantitative methods for recon- routine also assumes that tendons are rigid, and structing locomotion in extinct animals. thus does not account for the storage and release of For extinct animals, modeling and simulation elastic energy. These two limitations must be procedures are similar but require more assump- addressed for behaviors involving rapid limb move- tions. These assumptions must be analyzed ments, such as flapping or jumping (see Heers et al., through sensitivity analyses and validated by com- 2018). parison with models of living homologs or ana- Dynamic Simulations: Unlike static simula- logs (Hutchinson, 2011). For example, step 1 tions, dynamic simulations account for time- requires assumptions about the distribution of dependent properties but require extensive mass and about joint anatomy, because the soft- knowledge of muscle physiology and can be diffi- tissue components of joints are usually not pre- cult to work with. One type of dynamic simulation served. For step 2, although the geometry of some is forward dynamics. When muscle activations are muscles can be reconstructed based on muscle known (e.g., previously measured using electromy- scars and phylogenetic bracketing, muscle size, ography), they can be used to predict what type of architecture, and physiology must always be locomotor behavior would result, given the animal’s extrapolated based on knowledge of living coun- musculoskeletal anatomy and the muscle activa- terparts. Joint kinematics (step 3) and external tions. Forward dynamics can thus be used to vali- forces (step 4) must also be inferred, potentially by date a model (does the behavior I’m trying to phylogenetic bracketing coupled with analyses of model actually occur with the given inputs?), and joint range of motion and body size scaling. For to compare or predict how muscle anatomy and all such inferences, it is probably best to analyze a activation affect locomotion (does locomotor range of possible anatomical, kinematic, and behavior/performance differ because muscle anat- kinetic inputs (i.e., conduct a sensitivity analysis), omy and/or activations differ?). which results in a range of “answers” to questions Together, musculoskeletal modeling and sim- but reflects the uncertainty in these types of analy- ulation provide a dynamic, three-dimensional, ses and can highlight results that are robust to whole-body perspective on locomotion in living modeling or simulation assumptions. Regardless animals, by analyzing how the skeleton, muscles, of how many models or simulations are consid- and feathers (which produce external, i.e., aero- ered, the modeling and simulation procedure dynamic, forces) all work together during loco- must be validated by comparison with similar motion. Once a modeling and simulation models and simulations of living animals. Loco- approach has been worked out, additional ques- motor capabilities are known in living animals, tions that would be impossible to answer work- and the degree to which a musculoskeletal model ing solely with live animals can be explored. For and simulation can mimic those capabilities indi- example, anatomical features (e.g., bony pro- cates our level of confidence in the modeling and cesses, joint morphology, muscle size), as well as simulation of locomotion in extinct animals. 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 289

Musculoskeletal modeling and simulation have approaches by a coauthor (A.M.H.) (Heers et been used to study posture and locomotor capacity al., 2018). Such validation is welcome and (i.e., running speed) of theropods such as Tyran- underscores the complementary nature of these nosaurus rex (Hutchinson et al., 2005), and efforts two methods. For example, while musculoskel- are currently underway to apply this approach to etal modeling and simulations offer a vital the evolution of avian flight (Heers and Carney, dynamic, three-dimensional, whole-body per- 2017). For example, by simulating a range of poten- spective, first-principles-based modeling is tial flapping kinematics in key taxa like Archaeop- readily scalable and applicable to large, com- teryx and in earlier and later diverging forms, we parative datasets allowing it to identify macro- can assess which behaviors were potentially possi- evolution patterns and trends more easily (e.g., ble at different evolutionary stages and examine in chapter 11 by Dececchi et al.). Such a “pros- how evolutionary changes in morphology might pect and then mine” relationship between these have facilitated the origins of . two methods is synergistic and should be fur- In summary, when used in conjunction with ther developed and coordinated moving studies on live animals, musculoskeletal modeling forward. and simulation are extremely useful tools for Estimating flight performance requires sig- exploring how different anatomical features nificant time to set up, particularly musculoskel- (bones, muscles, feathers) work together during etal modeling and simulation, but their analytical locomotion. In addition, this technique allows products (i.e., spreadsheet equations, aerody- anatomical, kinematic, and/or kinetic properties namics software, 3D interactive computer mod- to be systematically adjusted to explicitly examine els) can often be reasonably easily modified if form-function relationships in ways that cannot subsequent analyses involve similar subjects. In be done empirically. Once a modeling and simula- the case of mechanically informed morphospace tion approach has been tested using an extant analysis, functional morphology of structures analog or homolog, similar procedures can be (e.g., deltopectoral crest of the humerus) or other applied to fossils to assess locomotor potential. estimated variables (e.g., wing span and wing Uncertainties in the musculoskeletal anatomy, surface) can be compared with a large dataset of kinematics, and kinetics of extinct animals are modern birds. Based on physics principles, this accounted for by using multiple models and simu- comparison has provided relevant information lations, resulting in a range of “answers” but high- on the flight performance of a few early-diverg- lighting results that are robust to modeling or ing birds (Liu et al 2017, 2019; Serrano and Chi- simulation assumptions. Because of this, muscu- appe 2017; Serrano et al 2018; Chiappe et al. loskeletal modeling and simulation is one of the 2019). In addition, this approach can be comple- most rigorous tools available for assessing loco- mented and validated through the construction motor potential in extinct animals, including the- of aerodynamic models of early birds using, for ropods with feathered forelimbs. example, the software Flight v. 1.24 developed for modern birds (www.bio.bristol.ac.uk/people/ pennycuick.htm; Pennycuick, 2008), which DISCUSSION reduces the time needed to set up new analyses. The methods surveyed here have all had sig- The publication of several landmark studies in nificant impact on our understanding of early recent years (Dececchi et al., 2016; Heers et al., theropod flight and have been validated. This 2016; Serrano and Chiappe, 2017; Serrano et al., includes the example of first-principles-based 2017; Heers et al., 2018; Serrano et al., 2018; Pei modeling for the ultimate origins of theropod et al., in press) therefore promises a potentially flight, which aligns with recent results of rapid expansion in flight-performance studies in extremely detailed, single-species simulation the not too distant future. 290 BULLETIN AMERICAN MUSEUM OF NATURAL HISTORY NO. 440

All methods of flight-performance estimation al., 2018). First-principles-based modeling require assumptions with many needing parame- remains the most readily adaptable method for ters obtained from living birds because they are studying flight performance across the breadth of simply unknown in fossil taxa, e.g., the power out- , but as better fossil data help to put of flight muscle. However, with thousands of minimize potential sources of error in key param- fossil birds available, it is understandable that eters in particular (i.e., body mass, wing space, specimens that might provide direct estimates of and lift surface), this situation could change and certain parameters may be overlooked. The lead- potentially present an opportunity for consensus ing-edge wing shape of the early-diverging para- results across multiple methods in the future. vians Anchiornis and Microraptor—as revealed by LSF (Wang et al., 2017; co-author MP & TGK, unpublished data)—are good examples of other- ACKNOWLEDGMENTS wise unknown information that directly affects We would like to thank the attendees of the estimations. In this case this information improves International Pennaraptoran Dinosaur Sympo- our estimation of wing area, which has since been sium and our reviewers for their comments considered in subsequent studies (Pei et al., in and suggestions, which helped to improve the press), including in chapter 11 of this volume. quality of this manuscript. The symposium was Also in this volume, Serrano, et al. (chapter 13) held at the University of Hong Kong and was use the lateral body outline of the early diverging supported by Kenneth HC Fung and First Ini- avialan Sapeornis—as observed under LSF—to tiative Foundation. This study was also sup- directly estimate the body’s disc surface generat- ported by the Research Grant Council of Hong ing drag during flight S( b). This surface and the Kong’s General Research Fund (17103315 to body drag coefficient—which is better estimated M.P.) and the RAE Improvement Fund of the knowing Sb—are influential parameters in model- Faculty of Science, the University of Hong ing flight dynamics. New analytical techniques Kong (to M.P. and T.G.K.). The participation of like LSF offer improved characterization of feath- D.J.F. was also supported by UK Research and ering, mass distribution, joint geometries, and Innovation Future Leaders Fellowship MR/ other key modeling parameters, particularly con- S032177/1. tentious ones like feather structure as related to rigidity in flight, thereby increasing the accuracy of our understanding of early theropod flight. REFERENCES However, at least a portion of the missing data is Abel, R.L., C.R. Laurini, and M. Richter. 2012. A pal- probably available from existing specimens even aeobiologist’s guide to ‘virtual’ micro-CT prepara- using standard microscopy methods, such is the tion. Palaeontologica Electronica 15: 6T. bounty of fossil specimens currently available. For Ahlborn, B.K. 2000. Thermodynamic limits of body example, some fossil taxa like Confuciusornis and dimension of warm blooded animals. Journal of Anchiornis are known from large sample sizes that Non-Equilibrium Thermodynamics 25: 87–102. are yet to be fully examined (Wang et al., 2017; Alexander, R.M. 2003. Principles of , Navalón et al., 2018) and the rate of new taxon Princeton: Princeton University Press. discovery remains high (see Pittman et al., chapter Allen, V., K.T. Bates, Z.H. Li, and J.R. Hutchinson. 2013. Linking the evolution of body shape and loco- 2). While it is easy to take this advice as a need to motor in bird-line archosaurs. Nature ramp up the number of specimens studied, past 497: 104–107. work and that by Serrano et al. (chapter 13) show Askew, G.N., R.L. Marsh, and C.P. Ellington. 2001. The that even a handful of feathered well-preserved mechanicalpower output of the flight muscles of specimens can provide accurate estimates (Liu et Blue-breasted Quail (Coturnix chinensis) during take- al., 2017; Serrano and Chiappe, 2017; Serrano et off. Journal of Experimental Biology 204: 3601–3619. 2020 PITTMAN ET AL.: METHODS OF STUDYING EARLY THEROPOD FLIGHT 291

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