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Evaluating archaeobotanical data from over 3.9 million seeds and 124,300 charcoal fragments across 330 archaeological site phases in Southwest Asia, we reconstruct the history of olive and grape cultivation spanning a period of 6,000 years. Combining charcoal and seed data enables investigation into both the production and consumption of olive and grape. The earliest indication for olive and grape cultivation appears in the southern Levant around ca. 5000 BC and 4th millennium BC respectively, although cultivation may have been practiced prior to these dates. Olive and grape cultivation in Southwest Asia was regionally concentrated within the Levant until 600 BC, although there were periodic pushes to the East. Several indications for climate influencing the history of olive and grape cultivation were found, as well as a correlation between periods of high population density and high proportions of olive and grape remains in archaeological sites. While temporal uncertainty prevents a detailed understanding of the causal mechanisms behind these correlations, we suggest that long distance trade in olives, grapes and their associated products was integral to the economic, social, and demographic trajectories of the region.
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Arqueología , Carbón Orgánico , Olea , Semillas , Vitis , Vitis/crecimiento & desarrollo , Olea/crecimiento & desarrollo , Semillas/crecimiento & desarrollo , Humanos , Historia Antigua , Asia , Agricultura/historiaRESUMEN
Strawberry production in California represents over 38,000 acres with an annual farm value of $1.99 billion. Strawberry dieback was observed in February of 2021 in the Salinas Valley in central California. Disease symptoms included dead and dying 'Maverick' strawberry plants with necrotic lesions and black discoloration of the crown, root cortex, epidermis, and vascular tissues. Disease incidence was estimated to be 60% of a 20-acre field. The causal agent was isolated from five randomly selected symptomatic plants by surface disinfesting symptomatic crowns and roots in 1% sodium hypochlorite for 30 s, rinsed twice in sterile water for 30 s then placed on 3.7% potato dextrose agar (PDA) Petri dishes amended with 100 mg/L streptomycin, and then incubated for 7 days at 24°C under a 12-h photoperiod. Consistent white cottony fungal colonies were hyphal tip transferred to fresh PDA dishes and incubated as above for morphological and genetic comparisons. Black acervuli developed 7 to 9 days after incubation. Conidia were ellipsoidal, measuring 25 to 30 × 7.5 to 10 µm (average 26.8 × 9.2 µm, n = 30), with five cells. Apical and basal cells were hyaline, and the three median cells were versicolorous brown, with a single, straight, centric basal appendage and 3 to 4 flexuous apical appendages. Colony diameter averaged 90 mm in 7 days. Based on colony and conidial characters, the fungus was tentatively identified as a species of Neopestalotiopsis (Maharachchikumbura et al. 2014). Total genomic DNA was extracted from three axenic cultures using the Invitrogen Easy-DNA kit. Three genetic loci were PCR amplified and sequenced: internal transcribed spacer (ITS), beta-tubulin (BT), and translation elongation factor 1-alpha (TEF) utilizing the primer pairs ITS1/ITS4, T1/Bt2a, and EF1-688F/EF1-1251R, respectively (White et al. 1990, O'Donnell and Cigelnik 1997, Glass and Donaldson 1995, and Alves et al. 2008). A BLASTn search of NCBI showed 99.6% identity (495/497 bases; OM942910-OM942912) with the type specimen of Neopestalotiopsis rosae CBS 101057 for the ITS locus. Both BT (765/765 bases, OM964802-OM964804) and TEF (475/475 bases; OM964799-OM964801) sequences were 100% identical to CBS 101057. Conidia of isolate PAR027 were scraped from the surface of 14-day-old PDA Petri dishes and inoculated (1 × 106 spores/mL: 2 mL/plant) to four apparently healthy strawberry transplant roots of the cultivar 'Monterey' in 'sunshine mix' potting soil. Two control plants were inoculated with sterile water. The experiment was conducted twice. Strawberry plants were maintained in a hoop house for four weeks, after which dieback and wilt symptoms resembled the symptoms observed in the field. Control plants remained asymptomatic and no pathogens were isolated. Fungal recovery from inoculated plants morphologically matched the original inoculum; thus, Koch's postulates was satisfied. To our knowledge, this is the first report of N. rosae causing crown and root rot disease of strawberry in California. Previously, N. rosae has been reported to cause serious decline of strawberry plants in Florida and several countries (Baggio et al. 2021, Rebollar-Alviter et al. 2020, Wu et al. 2021, Sun et al. 2021). Correct identification of the causal agent provides a proper foundation to identify control strategies for this emerging disease, which has the potential to become a significant problem for strawberry growers in the Salinas Valley of California.
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Historical maps present a unique depiction of past landscapes, providing evidence for a wide range of information such as settlement distribution, past land use, natural resources, transport networks, toponymy and other natural and cultural data within an explicitly spatial context. Maps produced before the expansion of large-scale mechanized agriculture reflect a landscape that is lost today. Of particular interest to us is the great quantity of archaeologically relevant information that these maps recorded, both deliberately and incidentally. Despite the importance of the information they contain, researchers have only recently begun to automatically digitize and extract data from such maps as coherent information, rather than manually examine a raster image. However, these new approaches have focused on specific types of information that cannot be used directly for archaeological or heritage purposes. This paper provides a proof of concept of the application of deep learning techniques to extract archaeological information from historical maps in an automated manner. Early twentieth century colonial map series have been chosen, as they provide enough time depth to avoid many recent large-scale landscape modifications and cover very large areas (comprising several countries). The use of common symbology and conventions enhance the applicability of the method. The results show deep learning to be an efficient tool for the recovery of georeferenced, archaeologically relevant information that is represented as conventional signs, line-drawings and text in historical maps. The method can provide excellent results when an adequate training dataset has been gathered and is therefore at its best when applied to the large map series that can supply such information. The deep learning approaches described here open up the possibility to map sites and features across entire map series much more quickly and coherently than other available methods, opening up the potential to reconstruct archaeological landscapes at continental scales.
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In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.
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Arqueología , Recursos Naturales , Arabia , Biodiversidad , Clima , Conservación de los Recursos Naturales , Manejo de Datos , Planeta Tierra , Ecosistema , Historia Antigua , Humanos , MesopotamiaRESUMEN
The rise and fall of ancient societies have been attributed to rapid climate change events. One of the most discussed of these is the 4.2kya event, a period of increased aridity and cooling posited as the cause of societal changes across the globe, including the collapse of the Akkadian Empire in Mesopotamia. Studies seeking to correlate social and climatic changes around the 4.2kya event have tended to focus either on highly localized analyses of specific sites or surveys or more synthetic overviews at pan-continental scales, and temporally on the event and its aftermath. Here we take an empirical approach at a large spatial scale to investigate trends in population and settlement organization across the entirety of Northern Fertile Crescent (Northern Mesopotamia and the Northern Levant) from 6,000 to 3,000 cal BP. We use Summed Probability Distributions of radiocarbon dates and data from eighteen archaeological surveys as proxies for population, and a dataset of all settlements over ten hectares in size as a proxy for the degree of urbanization. The goal is to examine the spatial and temporal impact of the 4.2kya event and to contextualize it within longer term patterns of settlement. We find that negative trends are visible during the event horizon in all three proxies. However, these occur against a long-term trend of increased population and urbanization supported through unsustainable overshoot and the exploitation of a drier zone with increased risk of crop failure. We argue that the 4.2kya event occurred during a period of unprecedented urban and rural growth which may have been unsustainable even without an exogenous climate forcing.
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Cambio Climático/estadística & datos numéricos , Ciudades , Dinámica Poblacional , Análisis Espacial , Encuestas y Cuestionarios , Factores de TiempoRESUMEN
Specimen survivability is a primary concern to those who utilize atom probe tomography (APT) for materials analysis. The state-of-the-art in understanding survivability might best be described as common-sense application of basic physics principles to describe failure mechanisms. For example, APT samples are placed under near-failure mechanical-stress conditions, so reduction in the force required to initiate field evaporation must provide for higher survivability-a common sense explanation of survivability. However, the interplay of various analytical conditions (or instrumentation) and how they influence survivability (e.g., decreasing the applied evaporation field improves survivability), and which factors have more impact than others has not been studied. In this paper, we report on the systematic analysis of a material composed of a silicon-dioxide layer surrounded on two sides by silicon. In total, 261 specimens were fabricated and analyzed under a variety of conditions to correlate statistically significant survivability trends with analysis conditions and other specimen characteristics. The primary result suggests that, while applied field/force plays an obvious role in survivability for this material, the applied field alone does not predict survivability trends for silicon/silicon-dioxide interfaces. The rate at which ions are extracted from the specimen (both in terms of ions-per-pulse and pulse-frequency) has similar importance.
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[This corrects the article DOI: 10.1371/journal.pone.0152563.].
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Over the last 8000 years the Fertile Crescent of the Near East has seen the emergence of urban agglomerations, small scale polities and large territorial empires, all of which had profound effects on settlement patterns. Computational approaches, including the use of remote sensing data, allow us to analyse these changes at unprecedented geographical and temporal scales. Here we employ these techniques to examine and compare long term trends in urbanisation, population and climate records. Maximum city size is used as a proxy for the intensity of urbanisation, whilst population trends are modelled from settlement densities in nine archaeological surveys conducted over the last 30 years across the region. These two measures are then compared with atmospheric moisture levels derived from multiple proxy analyses from two locations close to the study area, Soreq Cave in Israel and Lake Van in south-eastern Turkey, as well as wider literature. The earliest urban sites emerged during a period of relatively high atmospheric moisture levels and conform to a series of size thresholds. However, after the Early Bronze Age maximum urban size and population levels increase rapidly whilst atmospheric moisture declines. We argue that although the initial phase of urbanization may have been linked to climate conditions, we can see a definitive decoupling of climate and settlement patterns after 2000 BC. We relate this phenomenon to changes in socio-economic organisation and integration in large territorial empires. The complex relationships sustaining urban growth during this later period resulted in an increase in system fragility and ultimately impacted on the sustainability of cities in the long term.
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Urbanización/historia , Clima , Historia Antigua , Humanos , Israel , TurquíaRESUMEN
An HIE model developed in Florida leverages local and regional networks and offers a flexible, scalable framework that aligns them with national health IT and exchange priorities.