Search Results (3)

We studied the microbial diversity colonizing limestone rock pools at a Neolithic Monument (Arbor Low, Derbyshire, England). Five pools were analyzed: four located at the megaliths of the stone circle and one pool placed at the megalith at the Gib Hill burial mound 300 m distant. Samples were taken from rock pool walls and sediments, and investigated through molecular metabarcoding. The microbiome consisted of 23 phyla of bacteria (831 OTUs), 4 phyla of archaea (19 OTUs), and 27 phyla of microbial eukarya (596 OTUs). For bacteria, there were statistically significant differences in wall versus sediment populations, but not between pools. For archaea and eukarya, significant differences were found only between pools. The most abundant bacterial phylum in walls was Cyanobacteriota, and Pseudomonadota in sediments. For archaea and microbial eukarya, the dominant phyla were Euryarcheota and Chlorophyta, respectively, in both wall and sediments. The distant pool (P5) showed a markedly different community structure in phyla and species, habitat discrimination, and CHN content. Species sorting and dispersal limitation are discussed as mechanisms structuring the microbiome assemblages and their spatial connectivity. The Arbor Low microbiome is composed of terrestrial representatives common in extreme environments. The high presence of Cyanobacteriota and Chlorophyta in the Arbor Low stones is troubling, as these microorganisms can induce mechanical disruption by penetrating the limestone matrix through endolithic/chasmoendolithic growth. Future research should focus on the metabolic traits of strains to ascertain their implication in bioweathering and/or biomineralization. Full article

Airborne LiDAR technology is widely used in archaeology and over the past decade has emerged as an accurate tool to describe anthropomorphic landforms. Archaeological features are traditionally emphasised on a LiDAR-derived Digital Terrain Model (DTM) using multiple Visualisation Techniques (VTs), and occasionally aided by automated feature detection or classification techniques. Such an approach offers limited results when applied to heterogeneous structures (different sizes, morphologies), which is often the case for archaeological remains that have been altered throughout the ages. This study proposes to overcome these limitations by developing a multi-scale analysis of topographic position combined with supervised machine learning algorithms (Random Forest). Rather than highlighting individual topographic anomalies, the multi-scalar approach allows archaeological features to be examined not only as individual objects, but within their broader spatial context. This innovative and straightforward method provides two levels of results: a composite image of topographic surface structure and a probability map of the presence of archaeological structures. The method was developed to detect and characterise megalithic funeral structures in the region of Carnac, the Bay of Quiberon, and the Gulf of Morbihan (France), which is currently considered for inclusion on the UNESCO World Heritage List. As a result, known archaeological sites have successfully been geo-referenced with a greater accuracy than before (even when located under dense vegetation) and a ground-check confirmed the identification of a previously unknown Neolithic burial mound in the commune of Carnac. Full article

A combination of geophysical methods could be very a useful and a practical way of verifying the origin and precise localisation of archaeological situations identified by different remote sensing techniques. The results of different methods (and scales) of monitoring these fully non-destructive methods provide distinct data and often complement each other. The presented examples of combinations of these methods/techniques in this study (aerial survey, LIDAR-ALS and surface magnetometer or resistivity survey) could provide information on some specifics and may also be limitations in surveying different archaeological terrains, types of archaeological situations and activities. The archaeological site in this contribution is considered to be a material of this study. In case of Neolithic ditch enclosure near Kolín were compared aerial prospection data, magnetometer survey and aerial photo-documentation of excavated site. In the case of hillforts near Levousy we compared LIDAR data with aerial photography and large-scale magnetometer survey. In the case of the medieval castle Liběhrad we compared LIDAR data with geoelectric resistivity measurement. In case of a burial mound cemetery we combined LIDAR data with magnetometer survey. In the case of the production area near Rynartice we combined LIDAR data with magnetometer and resistivity measurements and result of archaeological excavation. Fortunately for successful combination of geophysical and remote sensing results, their conditions and factors for efficient use in archaeology are not the same. On the other hand, the quality and state of many prehistoric, early medieval, medieval and also modern archaeological sites is rapidly changing over time and both groups of techniques represent important support for their comprehensive and precise documentation and protection. Full article