Archaeologists identify a Palaeolithic bone tool workshop in Spanish cave
A study of a partition made from rocks in the El Mirón Cave has led to archaeologists identifying it as a Palaeolithic bone tool workshop.
El Mirón Cave is a cave system in the upper Asón River valley, located in the Cantabria region of northern Spain.
The cave was first discovered in 1903, leading to a series of excavations over the century revealing evidence of Palaeolithic hunter-gatherer activity, and the discovery of the “Red Lady of El Mirón”, a skeleton from the Upper Palaeolithic which was found coated with ochre, a red iron-based pigment.
In a paper published in the journal Antiquity, researchers from the University of New Mexico (UNM) have suggested that a partition made from rocks in the rear of the cave was actually used for bone tool manufacturing around 20,000-years-ago.
The cave contains hearths, pits, and other small structures, that provide evidence of Palaeolithic home-making, with the partition indicating that is was used for the working of animal bones and of stones to make tools based on the discarded bone material found around the rock feature.
Associate Professor of Archaeology at UNM, Emily Lena Jones, said: “Our hypothesis was that if this feature was used by the inhabitants, the discard around it should show clear patterning. Our analysis showed that this was the case. The stone alignment does seem to have been used in some way, and probably not just to isolate a trash heap.
It seems more likely that it is associated with a bone-working area. While probably most of the bones were from animals that initially did provide food for people, by the time the bone fragments were discarded in Level 115 of the cave, they’d also have been broken in ways that suggest people were making tools out of them,” added Jones.
According to the researchers, this discovery adds to the small list of known examples of Palaeolithic hunter-gatherer structures in caves, which are often associated with religious or ceremonial activities, but the area in El Mirón looks like it demarcates a working area for a bone tool workshop.
Header Image Credit : Antiquity
Nazca geoglyphs discovered used AI deep learning
Archaeologists from the Yamagata University have used AI deep learning to discover new geoglyphs in the northern part of the Nazca Pampa in the arid Peruvian coastal plain.
Geoglyphs in the Nazca Pampa were first identified during the 1920’s, with ongoing studies since the 1940’s revealing various figurative geoglyphs of zoomorphic designs, geometric shapes, and linear lines.
Geoglyphs can be categorised into three main types: figurative, geometric, and lineal. Archaeologists suggest that the lineal geoglyphs were created by the Nazca, a culture that developed during the Early Intermediate Period and is generally divided into the Proto Nazca (phase 1, 100 BC to AD 1), the Early Nazca (phases 2–4, AD 1 to 450), Middle Nazca (phase 5, AD 450 to 550) and the Late Nazca (phases 6–7, AD 550 to 750).
The relief type dates from the Late Formative period (400 to 200 BC), as the iconography of the geoglyphs are similar to that of Formative petroglyphs found on outcrops of rock. During this period, the region was inhabited by the Paracas Culture, an Andean people that emerged around 800 BC until 100 BC.
Since 2004, Yamagata University has been conducting geoglyph distribution surveys using satellite imagery, aerial photography, airborne scanning LiDAR, and drone photography to investigate the vast area of the Nazca Pampa covering more than 390 km2.
In 2016, the researchers used aerial photography with a ground resolution of 0.1 m per pixel to create a detailed survey of the region. Overtime, the team have identified various geoglyphs, however, the process is very time consuming, so they have adopted AI deep learning to analyse the photographs at a much faster rate.
The results of a study, published in the Journal of Archaeological Science, has revealed the discovery of four new Nazca geoglyphs using this new method by creating an approach to labelling training data that identifies a similar partial pattern between the known and new geoglyphs.
The four new geoglyphs depict a humanoid figure, a pair-of-legs, a fish, and a bird. The humanoid geoglyph is shown holding a club in his/her right hand and measures 5 metres in length. The fish geoglyph, shown with a wide-open mouth measures 19 metres, while the bird geoglyph measures 17 metres and the pair-of-legs 78 metres.
According to the study authors: “We have developed a DL pipeline that addresses the challenges that commonly arise in the task of archaeological image object detection. Our approach allows DL to learn representations of images with better generalisation and performance, enabling the discovery of targets that have been difficult to find in the past. Moreover, by accelerating the research process, our method contributes to archaeology by establishing a new paradigm that combines field surveys and AI, leading to more efficient and effective investigations.”
Header Image Credit : Yamagata University
Archaeologists study fortress in southern Georgia to understand community resilience
A team of archaeologists led by Cranfield University is conducting a detailed study of the fortress of Dmanisis Gora in the Kvemo Kartli region of Georgia.
The study is part of a project to understand why communities in the region were more resilient than other parts of the world during the transition from the Bronze to the Iron Age around 1200 BC.
Dmanisis Gora is located at the north-eastern edge of the highland zone between two such gorges. The site consists of a compact defensive core that has two defensive walls with an enclosed area of 3.7 acres.
On the plateau behind the citadel area, a third wall, extending about 1000 m from edge to edge on the plateau, encloses a much larger area of about 138.3 acres that contains numerous circular and linear stone features.
During the so-called ‘12th Century BC crisis’ and its aftermath, the majority of Middle Eastern regions underwent a period of significant turmoil characterised by the disintegration of empires, famine, crop failures, armed conflicts, and mass migration.
In contrast, the Caucasus region (consisting of present-day Georgia, Armenia, and Azerbaijan) appears to have been shielded from this tumultuous period, exhibiting only gradual transformations in material culture and patterns of settlement.
Either the region managed to entirely avoid the widespread disruption, or it did not experience the same cultural, economic, and political repercussions as other areas. This suggests that the communities in the region might have been more resilient, enabling them to withstand and adapt to the challenges in a comparatively effective manner.
Dr Erb-Satullo, from Cranfield University, said: “The key to understanding why the Bronze Age-Iron Age transition is different in the Caucasus is to study the fortress communities that dot the landscape during this period. We’re looking for clues about life in the Late Bronze Age through examining areas such as ceramics, burial rituals, farming practices, tools and social structures.”
“Given the upheaval at that time in other nearby regions, we are intrigued to find out more about one of these sites and determine what underlies their apparent resilience,” added Dr Erb-Satullo.
The project expands upon earlier pilot excavations carried out at the site prior to the pandemic, along with a thorough survey conducted in Autumn 2022 using drone-based photogrammetry. This is done by using the latest forensic technologies including isotopic analysis of animal remains, metallurgy, magnetometry and deploying drones to scan the area.
“What’s really exciting about this site is its size, preservation, and the fact that it has layers dating precisely to the years around the 12th Century BC crisis,” continued Dr Erb-Satullo. “Many fortresses are on hills which are prone to erosion. But this one has relatively flat topography, so the sediment will have built up in layers over time, helping to preserve artefacts and archaeological clues from the Late Bronze age.”
Header Image Credit : BING Maps
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