An international team led by scientists from the Max Planck Institute and the University of Oxford, including Professor Susana Carvalho, has developed new methods that are able to detect external and internal damage inflicted on percussive wooden tools used by chimpanzees to crack nuts. This research involved tools collected during decades of field research in Côte d´Ivoire in West Africa where wild chimpanzees use wooden branches to crack open different nut species. The team discovered that nut-cracking leads to permanent modifications in the wood. This damage through pounding produces a behavioural signature that is unique and irreversible.
Tools used to break open hard objects play an important role in the evolution of tool use in the human species. The discovery of tools used by chimpanzees was a critical piece in our understanding that this behavior is not unique to humans. Tools used to crack open hard objects, like nuts, are thought to have been an important stepping-stone to the evolutionary success of humans. Although, we know that many different primate species use wooden tools, we know remarkably little about wooden tool use in ancient human ancestors. Tools made of wood often decompose quickly. The oldest known wooden tool used by early humans is about 400,000 years old. One of the difficulties in identifying tool use in deeper time is our inability to recognize wooden tools from ancient contexts. The research described here uses innovative techniques to document the patterns that chimpanzees leave on wooden tools.
The research team brought together fields of computer science, geography and primatology to develop new methods of tool identification. The results of this research show that the pounding of wooden branches by chimpanzees creates a diagnostic pattern on the surface of the tools, but also in internally by modification of the cell structure of the wood. Externally the surface of the wooden tools shows deep indentations that accumulate over several years. The research team was able to characterize these patterns by making three dimensional models of the surface of the wooden tools. Adopting techniques that geographers usually use to identify valleys and ridges, the team was able to quantify the shape of these damage patterns. The research team also used cutting edge computer vision and machine learning techniques to identify damaged surfaces from images. Their machine learning algorithms can accurately identify chimpanzee tools from undamaged pieces of wood even after substantial modifications of the image. Furthermore, the repeated hammering of these wooden tools breaks the cell walls inside the wooden tools. This leaves a diagnostic pattern that is permanent. Even years after pieces of wood were used as tools these internal structures provide a telltale sign of their previous use as tools.
These new techniques were used to confidently identify tools used by chimpanzee, but importantly, this has implications for finding very ancient tool use. Since these signs of damage last for years, there is a real possibility that similar tools are located in early archaeological sites. The novel methods developed in this study make it possible for the first time to test this hypothesis. The team is currently exploring ancient archaeological sites to see if similar patterns can be found in deep time.
Read the paper published in iScience.