68 resultados para Rugaard (Manor) Skovby, Denmark.


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This study compares associations between demographic profiles, long bone lengths, bone mineral content, and frequencies of stress indicators in the preadult populations of two medieval skeletal assemblages from Denmark. One is from a leprosarium, and thus probably represents a disadvantaged group (Naestved). The other comes from a normal, and in comparison rather privileged, medieval community (AEbelholt). Previous studies of the adult population indicated differences between the two skeletal collections with regard to mortality, dental size, and metabolic and specific infectious disease. The two samples were analyzed against the view known as the "osteological paradox" (Wood et al. [1992] Curr. Anthropol. 33:343-370), according to which skeletons displaying pathological modification are likely to represent the healthier individuals of a population, whereas those without lesions would have died without acquiring modifications as a result of a depressed immune response. Results reveal that older age groups among the preadults from Naestved are shorter and have less bone mineral content than their peers from AEbelholt. On average, the Naestved children have a higher prevalence of stress indicators, and in some cases display skeletal signs of leprosy. This is likely a result of the combination of compromised health and social disadvantage, thus supporting a more traditional interpretation. The study provides insights into the health of children from two different biocultural settings of medieval Danish society and illustrates the importance of comparing samples of single age groups.

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Small mammals and stray cats were trapped in two areas of North Zealand, Denmark, and their blood cultured for hemotrophic bacteria. Bacterial isolates were recovered in pure culture and subjected to 16S rDNA gene sequencing. Bartonella species were isolated from five mammalian species: B. grahamii from Microtus agrestis (field vole) and Apodemus flavicollis (yellow-necked field mouse); B. taylorii from M. agrestis, A. flavicollis and A. sylvaticus (long-tailed field mouse); B. tribocorum from A. flavicollis; R vinsonii subsp. vinsonii from M. agrestis and A. sylvaticus; and B. birtlesii from Sorex vulgaris (common shrew). In addition, two variant types of B. henselae were identified: variant I was recovered from three specimens of A. sylvaticus, and B. henselae variant 11 from I I cats; in each case this was the only B. henselae variant found. No Bartonella species was isolated from Clethrionomys glareolus (bank vole) or Micromys minutus (harvest mouse). These results suggest that B. henselae occurs in two animal reservoirs in this region, one of variant I in A. sylvaticus, which may be transmitted between mice by the tick Ixodes ricinus, and another of variant 11 in cats, which may be transmitted by the cat flea (Ctenocephalides felis). To our knowledge, this is the first report of the occurrence of B. henselae and B. tribocorum in Apodemus mice.

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This volume reports on the excavations from 2002 to 2005 designed to investigate this transition, with the focus on the origins of Bishopstone village. Excavations adjacent to St Andrew’s churchyard revealed a dense swathe of later Anglo-Saxon (8th- to late 10th-/early 11th-century) habitation, including a planned complex of ‘timber halls’, and a unique cellared tower. The occupation encroached upon a pre-Conquest cemetery of 43 inhumations. The report provides a comprehensive analysis, interpretation and academic contextualisation of the archaeological discoveries brought to light by these excavations, the first to sample a later Anglo-Saxon rural settlement in East Sussex on an extensive scale. The inter-disciplinary approach appraises the historical and topographical evidence alongside that recovered during the excavations.

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We explore the potential predictability of rapid changes in the Atlantic meridional overturning circulation (MOC) using a coupled global climate model (HadCM3). Rapid changes in the temperature and salinity of surface water in the Nordic Seas, and the flow of dense water through Denmark Strait, are found to be precursors to rapid changes in the model's MOC, with a lead time of around 10 years. The mechanism proposed to explain this potential predictability relies on the development of density anomalies in the Nordic Seas which propagate through Denmark Strait and along the deep western boundary current, affecting the overturning. These rapid changes in the MOC have significant, and widespread, climate impacts which are potentially predictable a few years ahead. Whilst the flow through Denmark Strait is too strong in HadCM3, the presence of such potential predictability motivates the monitoring of water properties in the Nordic Seas and Denmark Strait.

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Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

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Annual total phosphorus (TP) export data from 108 European micro-catchments were analyzed against descriptive catchment data on climate (runoff), soil types, catchment size, and land use. The best possible empirical model developed included runoff, proportion of agricultural land and catchment size as explanatory variables but with a low explanation of the variance in the dataset (R-2 = 0.37). Improved country specific empirical models could be developed in some cases. The best example was from Norway where an analysis of TP-export data from 12 predominantly agricultural micro-catchments revealed a relationship explaining 96% of the variance in TP-export. The explanatory variables were in this case soil-P status (P-AL), proportion of organic soil, and the export of suspended sediment. Another example is from Denmark where an empirical model was established for the basic annual average TP-export from 24 catchments with percentage sandy soils, percentage organic soils, runoff, and application of phosphorus in fertilizer and animal manure as explanatory variables (R-2 = 0.97).