Walking in mud: Remarkable Pleistocene human trackways from White Sands National Park (New Mexico)
| Autor: | Tommy Urban, Marcin Budka, Daniel Odess, Patrick Martinez, Matthew R. Bennett, Ashleigh L. A. Wiseman, Vincent L. Santucci, David Bustos, Sally C. Reynolds, Jens N. Lallensack |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010506 paleontology
Archeology Global and Planetary Change 010504 meteorology & atmospheric sciences biology Pleistocene National park Geology Trackway Columbian mammoth Sloth biology.organism_classification 01 natural sciences Predation Footprint Geography biology.animal Physical geography Ecology Evolution Behavior and Systematics 0105 earth and related environmental sciences Mammoth |
| ISSN: | 0277-3791 |
| Popis: | Human tracks at White Sands National Park record more than one and a half kilometres of an out‐ and‐back journey and form the longest Late Pleistocene‐age double human trackway in the world. An\ud adolescent or small adult female made two trips separated by at least several hours, carrying a young child in at least one direction. Despite giant ground sloth and Columbian Mammoth transecting them\ud between the outbound and return journeys, the human tracks show no changes indicative of predator/prey awareness. In contrast, the giant ground sloth tracks show behaviour consistent with human predator awareness, while mammoth tracks show no such apparent concern. The human footprints are morphologically variable and exhibit left‐right asymmetry, which might be due to child carrying. We explore this morphological variability using methods based on the analysis of objective track outlines, which add to the analytical toolkit available for use at other human footprint sites. The sheer number of tracks and their remarkable morphological variability have implications for the reliability of inferences made using much smaller samples as are more common at typical footprint sites. One conclusion is that the number of footprints required to make reliable biometric inferences is larger than often assumed. |
| Databáze: | OpenAIRE |
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