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A 3D taphonomic model of long bone modification by lions in medium-sized ungulate carcasses.

Manuel Domínguez-RodrigoAgness GidnaEnrique BaquedanoLucía Cobo-SánchezRocio MoraLloyd A CourtenayDiego Gonzalez-AguileraMiguel Ángel Maté-GonzálezDiego Prieto-Herráez
Published in: Scientific reports (2021)
Here, we present the first three-dimensional taphonomic analysis of a carnivore-modified assemblage at the anatomical scale of the appendicular skeleton. A sample of ten carcasses composed of two taxa (zebra and wildebeest) consumed by wild lions in the Tarangire National Park (Tanzania) has been used to determine element-specific lion damage patterns. This study presents a novel software for the 3D spatial documentation of bone surface modifications at the anatomical level. Combined with spatial statistics, the present analysis has been able to conclude that despite variable degrees of competition during carcass consumption, lions generate bilateral patterning consisting of substantial damage of proximal ends of stylopodials and zeugopodials, moderate damage of the distal ends of femora and marginal damage of distal ends of humeri and zeugopodials. Of special interest is, specifically, the patterning of tooth marks on shafts according to element, since these are crucial to determine not only the type of carnivore involved in any given bone assemblage, but also the interaction with other agents (namely, hominins, in the past). Lions leave few tooth marks on mid-shaft sections, mostly concentrated on certain sections and orientations of stylopodials and, to a lesser extent, of the proximal tibia. Redundant occurrence of tooth marks on certain bone sections renders them as crucial to attest lion agency in carcass initial consumption. Indirectly, this can also be used to determine whether hominins ever acquired carcasses at lion kills.
Keyphrases
  • bone mineral density
  • oxidative stress
  • soft tissue
  • bone loss
  • bone regeneration
  • risk assessment
  • minimally invasive
  • body composition
  • electronic health record
  • data analysis