Search

Fine-resolution soil maps constitute important data for many different environmental studies. Digital soil mapping techniques represent a cost-effective method to obtain detailed information about soil types and soil properties over large areas. The main objective of the study was to extend predictions from 1:25,000 legacy soil surveys (including WRB soil groups, soil depth and soil texture classes) to the larger area of Cyprus. A multiple-trees classification technique, namely Random Forest (RF), was applied. Specific objectives were: (i) to analyze the role and importance of a large data set of environmental predictors, (ii) to investigate the effect of the number of training points, forest size ( ntree ), the numbers of predictors sampled per node ( mtry ) and tree size ( nodesize ) in RF; (iii) to compare RF-derived maps with maps derived with a multinomial logistic regression model, in terms of validation error (test set and independent profiles) and map uncertainty, using the confusion index and a newly developed reliability index. The optimized RF model was run using half of the input points available (over a million) and with ntree equal to 350. The mtry parameter was set to 5 (close to half the number of the environmental variables used) for both soil series and soil properties. The nodesize calibration showed no relevant performance increase and was kept at its default value (1). In terms of environmental variables, the model used 10 predictors, covering all the soil formation factors considered in the scorpan formula, to derive the three maps. Soil properties, derived from geochemistry data, showed a high importance in deriving soil groups, depths and texture. Random Forest constructed a better predictive model than multinomial logistic regression, showing comparable predictive uncertainty but much lower validation error. The RF-derived maps show very low out of bag (OOB) errors (around 10% for both soil groups and soil properties) but relatively high validation error from independent profiles (45% for soil depth, 51% for soil texture). The resulting reliability index was low in the main mountainous area of Cyprus, where predictions were extrapolations as indicated by the multivariate environmental similarity surface, but medium to high in the main agricultural areas of the country. [ABSTRACT FROM AUTHOR]

The antiquity of human dispersal into Mediterranean islands and ensuing coastal adaptation have remained largely unexplored due to the prevailing assumption that the sea was a barrier to movement and that islands were hostile environments to early hunter-gatherers [J. F. Cherry, T. P. Leppard, J. Isl. Coast. Archaeol. 13, 191-205 (2018), 10.1080/15564894.2016.1276489]. Using the latest archaeological data, hindcasted climate projections, and age-structured demographic models, we demonstrate evidence for early arrival (14,257 to 13,182 calendar years ago) to Cyprus and predicted that large groups of people (~1,000 to 1,375) arrived in 2 to 3 main events occurring within <100 y to ensure low extinction risk. These results indicate that the postglacial settlement of Cyprus involved only a few large-scale, organized events requiring advanced watercraft technology. Our spatially debiased and Signor-Lipps-corrected estimates indicate rapid settlement of the island within <200 y, and expansion to a median of 4,000 to 5,000 people (0.36 to 0.46 km-2) in <11 human generations (<300 y). Our results do not support the hypothesis of inaccessible and inhospitable islands in the Mediterranean for pre-agropastoralists, agreeing with analogous conclusions for other parts of the world [M. I. Bird et al., Sci. Rep. 9, 8220 (2019), 10.1038/s41598-019-42946-9]. Our results also highlight the need to revisit these questions in the Mediterranean and test their validity with new technologies, field methods, and data. By applying stochastic models to the Mediterranean region, we can place Cyprus and large islands in general as attractive and favorable destinations for paleolithic peoples. [ABSTRACT FROM AUTHOR]

The Lambousa fishtank, an archaeological structure entirely carved in bedrock, can be easily recognized and measured in the plan on Google Earth (GE). We surveyed in situ this excellent archaeological marker in 2016 through direct measurements using traditional field instruments, such as metric tapes and invar rods, and terrestrial photogrammetry using Structure from Motion (SfM) methods. The bedrock on which the fishtank is founded is an Upper Pleistocene calcarenite also containing Persistrombus latus. The age of the studied fishtank has not been previously published, but on the basis of the construction technique and the interpretation provided by Archaelogist and references therein, we believe that it was built in the period between 2.1 and 1.8 ka BP, like similar fishtanks in the Mediterranean area. Architectural structures consist of evident foot walks (Crepido), a stone base, and a tunnel that allows for seawater exchange during high tides. The tunnel is at the same altitude as the Crepido, which lies around the fishtank. These architectural components allow us to evaluate the palaeo-sea level with significant precision during the time when the fishtank was active. MIS 5.5 coastal deposits that outcrop in the study area are located at a maximum altitude of a few meters, while the inner margin of the MIS 5.5 terrace allows us to hypothesize "quasi-tectonic stability". We have also obtained several predictions of the contribution from Glacial Isostatic Adjustment (GIA) to relative sea level at Lambousa for the past 3.5 kyr, according to models ICE-6G (VM5a), ICE-7G (VM7), and one of the GIA models by the Australian National University ANU) Research group. [ABSTRACT FROM AUTHOR]

Seaborne movement underpins frontier research in prehistoric archaeology, including water-crossings in the context of human dispersals, and island colonisation. Yet, it also controls the degree of interaction between locations, which in turn is essential for investigating the properties of maritime networks. The onset of the Holocene (circa 12,000 years ago) is a critical period for understanding the origins of early visitors/inhabitants to the island of Cyprus in the Eastern Mediterranean in connection with the spread of Neolithic cultures in the region. The research undertaken in this work exemplifies the synergies between archaeology, physical sciences and geomatics, towards providing novel insights on the feasibility of drift-induced seaborne movement and the corresponding trip duration between Cyprus and coastal regions on the surrounding mainland. The overarching objective is to support archaeological inquiry regarding the possible origins of these visitors/inhabitants—Anatolia and/or the Levant being two suggested origins. [ABSTRACT FROM AUTHOR]

Picrolite artefacts comprise some of the most distinctive material remains in the prehistory of the island of Cyprus, in the Eastern Mediterranean. Picrolite exploitation dates from at least 12,000 years ago for the manufacture of personal ornaments and items with a symbolic function. It is commonly assumed that picrolite nodules were collected in secondary deposits on an ad hoc basis. This narrative, however, ignores the fact that picrolite carriers can only be found in very specific locations on the island, discrete from each other. Here we report initial outcomes of the application of handheld portable X-ray fluorescence (HHpXRF) and synchrotron-based X-ray fluorescence spectroscopy (SR-μXRF) to the analysis of picrolite raw materials performed at the newly opened PUMA beamline of the SOLEIL Synchrotron Radiation Facility. Our work refines the basic characteristics of the elemental constituents of the picrolite raw material and highlights key micro-structural differences between two distinct source regions on the Troodos Massif in western Cyprus. Picrolite source characterisation is expected to contribute significant new knowledge to the study of rare raw material consumption, prehistoric social organisation, networking and possible long-distance exchange of this idiosyncratic raw material within and beyond the island's geographic boundaries. [ABSTRACT FROM AUTHOR]

Predictive models have become an integral part of archaeological research, particularly in the discovery of new archaeological sites. In this paper, we apply predictive modeling to map high potential Pleistocene archaeological locales on the island of Cyprus in the Eastern Mediterranean. The model delineates landscape characteristics that denote areas with high potential to unearth Pleistocene archaeology while at the same time highlighting localities that should be excluded. The predictive model was employed in surface surveys to systematically access high probability locales on Cyprus. A number of newly identified localities suggests that the true density of mobile hunter-gatherer sites on Cyprus is seriously underestimated in current narratives. By adding new data to this modest corpus of early insular sites, we are able to contribute to debates regarding island colonisation and the role of coastal environments in human dispersals to new territories. [ABSTRACT FROM AUTHOR]

Abstract: A Project funded by the Research Promotion Foundation of Cyprus was undertaken by the Cyprus University of Technology and other collaborators, to investigate and determine the geothermal parameters of the ground in Cyprus since such information is currently unavailable. The purpose of this paper is to report on the ground temperatures collected by now, at the six representative sites in relation to depth, time of the year, structure of the ground and altitude and report on their impact on the efficiency of Ground Coupled Heat Pumps. Every month since October 2009, the temperature of the ground is being recorded along the depth of the boreholes. It is anticipated that the project will be completed by the end of 2010 and geothermal information will be collected and reported for all six locations. The data collected until now clearly indicate that there is a potential for the efficient use of GCHPs in Cyprus leading to significant savings in power. [Copyright &y& Elsevier]

Abstract: In this paper a neural network is used for the generation of geothermal maps (contours) of temperature at three depths (20, 50 and 100 m) in Cyprus. Archived data of temperature recorded at 41 boreholes is used for training a suitable artificial neural network. The complete data was randomly divided into a training and validation dataset. The neural network is used to predict the temperature at any arbitrary location on the island, which can subsequently be used for drawing geothermal maps. For this purpose, a multiple hidden layer feedforward architecture was chosen after testing a number of architectures. The correlation coefficient obtained between the predicted and training dataset is 0.9889, which is very close to 1, indicating an accurate mapping of the data. The validation of the network was performed using the validation (unknown) dataset. The correlation coefficient for the unknown cases was 0.9253. The prediction error for the temperature was confined to less than 1.74 °C, which is considered quite adequate. In order to broaden the database, the patterns used for the validation of the technique were embedded into the training dataset and a new training of the network was performed. The architecture and the other parameters of the network were kept the same as for the validation phase. The correlation coefficient value for this case was equal to 0.9918. A 10 × 10 km grid is then drawn over a detailed topographic map of Cyprus and the various input parameters were recorded for each grid-point. This information was then supplied to the trained network and by doing so, temperature at the same depths as above was predicted at each grid-point. The x and y coordinates and the estimated temperatures at the three depths for both the original boreholes and at the grid-points were then used as input to a specialized contour drawing software in order to draw the geothermal maps. These maps will be a helpful tool for engineers wanting to apply geothermal heat in Cyprus. [Copyright &y& Elsevier]