Paranaguá, Antonina e Curitiba, início do século XIX: reconstituindo espaços e a lógica de sua organização social

This paper is to develop a methodology to characterize the spatial distribution in the early nineteenth century, the urban residents enrolled in the Décima of Paranaguá, Antonina and Curitiba, three villages in southern province of São Paulo. Here are the problems faced and decisions made, almost always temporary and arbitrary. The result reached hypothetical plants of subdivisions and urban streets of those towns. From a database - developed mainly with the information Lista Nominativa de Habitantes - it was possible to characterize residents enrolled in the books of property tax Décima. Spatialising thematic data in plants, where they lived was possible to perceive the social group, your choices (or lack thereof), or realize their preferred sites, but not exclusive housing.O objetivo desse artigo é desenvolver uma metodologia para caracterizar a espacialização, no início do século XIX, dos moradores arrolados nas décimas urbanas de Paranaguá, Antonina e Curitiba, três vilas do sul da capitania de São Paulo. Apresentamos aqui os problemas enfrentados e decisões tomadas, quase sempre provisórias e arbitrárias. O resultado chegou a plantas hipotéticas dos loteamentos e arruamentos urbanos daquelas vilas. A partir de um banco de dados - elaborado principalmente com informações das Listas Nominativas de Habitantes -, foi possível caracterizar os moradores arrolados nos livros de imposto predial de Décima. Espacializando esses dados em plantas temáticas, foi possível perceber onde moravam os grupo sociais, suas escolhas (ou a falta delas), ou seja, perceber seus locais preferenciais, mas não exclusivos, de habitação

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio