Neo-taphonomic analysis of the Misiam leopard lair from Olduvai Gorge (Tanzania): understanding leopard–hyena interactions in open settings

Misiam is a modern wildebeest-dominated accumulation situated in a steep ravine covered with dense vegetation at Olduvai Gorge (Tanzania). It is interpreted here as a leopard lair to which carcasses have been transported for several years. Felid-specific bone damage patterns, felid-typical skeletal part profiles, taxonomic specialization and the physical presence of leopards observed by the authors show that leopards at Misiam can be specialized medium-sized carcass accumulators. Hyenas also intervened at intervals in the modification of the retrieved faunal assemblage. This makes Misiam a carnivore palimpsest. Here, we additionally show that leopards only transport and accumulate carcasses on occasions, that they can seem highly specialized despite being dietary generalists, and that such a behaviour may be prompted by seasonal competition or during the breeding season or both. Misiam is the first open-air leopard lair with a dense bone accumulation reported. There, leopards engaged in intensive accumulation of carcasses during the wet season, when the southern Serengeti short-grass plains undergo the effect of the famous wildebeest migration and this migratory species reaches the gorge. The ecological importance of this behaviour and its relevance as a proxy for reconstructing prehistoric carnivore behaviours are discussed

Early Pleistocene faunivorous hominins were not kleptoparasitic, and this impacted the evolution of human anatomy and socio-ecology

Humans are unique in their diet, physiology and socio-reproductive behavior compared to other primates. They are also unique in the ubiquitous adaptation to all biomes and habitats. From an evolutionary perspective, these trends seem to have started about two million years ago, coinciding with the emergence of encephalization, the reduction of the dental apparatus, the adoption of a fully terrestrial lifestyle, resulting in the emergence of the modern anatomical bauplan, the focalization of certain activities in the landscape, the use of stone tools, and the exit from Africa. It is in this period that clear taphonomic evidence of a switch in diet with respect to Pliocene hominins occurred, with the adoption of carnivory. Until now, the degree of carnivorism in early humans remained controversial. A persistent hypothesis is that hominins acquired meat irregularly (potentially as fallback food) and opportunistically through klepto-foraging. Here, we test this hypothesis and show, in contrast, that the butchery practices of early Pleistocene hominins (unveiled through systematic study of the patterning and intensity of cut marks on their prey) could not have resulted from having frequent secondary access to carcasses. We provide evidence of hominin primary access to animal resources and emphasize the role that meat played in their diets, their ecology and their anatomical evolution, ultimately resulting in the ecologically unrestricted terrestrial adaptation of our species. This has major implications to the evolution of human physiology and potentially for the evolution of the human brain

A deep learning-based taphonomical approach to distinguish the modifying agent in the late pleistocene site of toll cave (Barcelona, Spain)

One of the most widely used methods to associate lithic tools and bone assemblage in archaeological sites is the identification of cut-marks. However, the identification of these marks is still problematic in some localities on account of the similarities with the modifications generated by non-human processes, including biostratinomic and post-depositional bone surface modifications. Toll Cave (Barcelona, Spain), with chronologies between 47.310 BP and 69.800 BP, is one of the case studies where the cut-marks could easily be confused with abundant grooves generated by the dragging of sedimentary particles (e.g. trampling), but also with the scores produced by carnivores. In this work, we present the results obtained from applying Deep Learning (DL) models to the taphonomic analysis of the site. This methodological approach has allowed us to distinguish the bone surface modifications with 97.5% reliability. We show the usefulness of this technique to help solve many taphonomic equifinality problems in the archaeological assemblages, as well as the need to implement new approaches to eliminate subjectivity in the descriptions of bone damage and make more accurate inferences about the past.PID2019-103987GB-C31; PID2022-138590NB-C41; CLT009/22/000045, 2021 SGR 01238 and 2021 SGR 01239 ; RYC2019-026386-I; PID2020-114462GB-I00; CEX2019-000945-Minfo:eu-repo/semantics/publishedVersio

Determining the diagenetic paths of archaeofaunal assemblages and their palaeoecology through artificial intelligence: an application to Oldowan sites from Olduvai Gorge (Tanzania)

The implementation of deep-learning methods to the taphonomic analysis of the microscopic modification of bone-surface modifications exposed to different chemical diagenetic pathways can effectively discriminate between acidic and alkaline soil properties, indirectly reflecting different ecological conditions. Here we use this novel method to assess the sedimentary conditions of two of the oldest Oldowan archaeofaunal records (DS and PTK, Bed I) from Olduvai Gorge Bed I in Tanzania. We show how the results support different diagenetic conditions for both penecontemporaneous sites, which are appropriate for their respective locations on the palaeolandscape to which they belonged. We also show how geochemical analyses of the clay deposit that embedded both sites indicate a similar soil pH divergence. PTK was formed on an alluvial sloping surface affected by rills but draining efficiently, which resulted in alkaline soil conditions, that optimised bone-surface preservation. DS occurred in a more depressed area that underwent intermittent flooding, affecting soil chemistry by creating more acidic conditions. This impacted on bone surfaces by dynamically modifying mark morphology. This deep-learning approach has relevance for the interpretation of the local palaeoecological conditions of both assemblages and their respective depositional loci. The results presented here open a new window to the incremental information gain through the use of artificial intelligence methods in taphonomic and palaeoecological research

Computer vision enables taxon-specific identification of African carnivore tooth marks on bone

Abstract Taphonomic works aim at discovering how paleontological and archaeofaunal assemblages were formed. They also aim at determining how hominin fossils were preserved or destroyed. Hominins and other mammal carnivores have been co-evolving, at least during the past two million years, and their potential interactions determined the evolution of human behavior. In order to understand all this, taxon-specific carnivore agency must be effectively identified in the fossil record. Until now, taphonomists have been able to determine, to some degree, hominin and carnivore inputs in site formation, and their interactions in the modification of part of those assemblages. However, the inability to determine agency more specifically has hampered the development of taphonomic research, whose methods are virtually identical to those used several decades ago (lagged by a high degree of subjectivity). A call for more objective and agent-specific methods would be a major contribution to the advancement of taphonomic research. Here, we present one of these advances. The use of computer vision (CV) on a large data set of images of tooth marks has enabled the objective discrimination of taxon-specific carnivore agency up to 88% of the testing sample. We highlight the significance of this method in an interdisciplinary interplay between traditional taphonomic-paleontological analysis and artificial intelligence-based computer science. The new questions that can be addressed with this will certainly bring important changes to several ideas on important aspects of the human evolutionary process

Deep learning identification of anthropogenic modifications on a carnivore remain suggests use of hyena pelts by Neanderthals in the Navalmaíllo rock shelter (Pinilla del Valle, Spain)

The identification of anthropogenically-modified carnivoran bones in archaeological sites is rare in Pleistocene contexts, especially in the most ancient periods. Neanderthal groups have clearly shown a great variety of subsistence activities and the use of carnivoran resources, until rare, is also present in some archaeological sites. However, the identification of the bone surface modifications (BSM) that allow us to infer the presence of anthropogenic marks in faunal remains are usually difficult to be differentiate among other BSM. Recently, several statistical and computing techniques have been developed to differentiate among different types of BSM in an objective way. To date, the most powerful approach is the use of Convolutional Neural Networks, which are the essential part of what is referred to as Deep Learning. In this work, ResNet50 and Inception V3 models are used through transfer learning. The algorithm architecture reaches an accuracy of >96.3% when differentiating among experimental trampling, cut and tooth marks. Once the transfer models were re-trained with the experimental BSM, they were used to classify several archaeological BSM previously identified as cut marks by human analysts. These BSM have been found on a bear ulna and on a hyena phalanx, both recovered at the Navalmaíllo Rock Shelter (Madrid, Spain). The BSM located on the hyaena phalanx have been identified as cut marks with a high probability while marks on the bear ulna are non-anthropogenic. This bone adds to the existing sample of anthropogenically-modified carnivoran elements by Neanderthal populations and hint to use of carnivore pelts by Neanderthals.Ministerio de Ciencia, Innovación y UniversidadesMinisterio de Ciencia e InnovaciónAGAURComunidad de MadridEuropean Social FundMuseo Arqueológico y Paleontológico de la Comunidad de MadridCanal de Isabel II-GestióDepto. de Geodinámica, Estratigrafía y PaleontologíaFac. de Ciencias GeológicasTRUEpu

Computer vision supports primary access to meat by early Homo 1.84 million years ago

Human carnivory is atypical among primates. Unlike chimpanzees and bonobos, who are known to hunt smaller monkeys and eat them immediately, human foragers often cooperate to kill large animals and transport them to a safe location to be shared. While it is known that meat became an important part of the hominin diet around 2.6-2 Mya, whether intense cooperation and food sharing developed in conjunction with the regular intake of meat remains unresolved. A widespread assumption is that early hominins acquired animal protein through klepto-parasitism at felid kills. This should be testable by detecting felid-specific bone modifications and tooth marks on carcasses consumed by hominins. Here, deep learning (DL) computer vision was used to identify agency through the analysis of tooth pits and scores on bones recovered from the Early Pleistocene site of DS (Bed I, Olduvai Gorge). We present the first objective evidence of primary access to meat by hominins 1.8 Mya by showing that the most common securely detectable bone-modifying fissipeds at the site were hyenas. The absence of felid modifications in most of the carcasses analyzed indicates that hominins were the primary consumers of most animals accumulated at the site, with hyenas intervening at the post-depositional stage. This underscores the role of hominins as a prominent part of the early Pleistocene African carnivore guild. It also stresses the major (and potentially regular) role that meat played in the diet that configured the emergence of early Homo