978 resultados para Alcott, Amos Bronson, 1799-1888.
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Pós-graduação em História - FCLAS
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A reassessment of the taxonomic status of Amblyomma cajennense based on the morphological analyses of ticks from the whole distribution area of the species resulted in the redescription of A. cajennense, the validation of 2 species which had been reduced to synonymy in the past, Amblyomma mixtum and Amblyomma sculptum, and the description and definition of 3 new species, Amblyomma tonelliae n. sp., Amblyomma interandinum n. sp., and Amblyomma patinoi n. sp. This study provides descriptions and redescriptions, scanning electron microscopic and stereomicroscopic images, updated synonymies, information on geographical distributions, and host associations for each of the 6 species. Amblyomma cajennense s.s. is found in the Amazonian region of South America, A. interandinum is reported from the northern part of the Inter-Andean valley of Peru, A. mixtum is present from Texas (U.S.A.) to western Ecuador, A. patinoi occurs in the Eastern Cordillera of Colombia, A. tonelliae is associated with the dry areas of the Chaco region which spans from central-northern Argentina to Bolivia and Paraguay, whereas A. sculptum is distributed from the humid areas of northern Argentina, to the contiguous regions of Bolivia and Paraguay and the coastal and central-western states of Brazil.
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The meteorological circumstances that led to the Blizzard of March 1888 that hit New York are analysed in Version 2 of the “Twentieth Century Reanalysis” (20CR). The potential of this data set for studying historical extreme events has not yet been fully explored. A detailed analysis of 20CR data alongside other data sources (including historical instrumental data and weather maps) for historical extremes such as the March 1888 blizzard may give insights into the limitations of 20CR. We find that 20CR reproduces the circulation pattern as well as the temperature development very well. Regarding the absolute values of variables such as snow fall or minimum and maximum surface pressure, there is anunderestimation of the observed extremes, which may be due to the low spatial resolution of 20CR and the fact that only the ensemble mean is considered. Despite this drawback, the dataset allows us to gain new information due to its complete spatial and temporal coverage.