QUANDO A FÁBRICA SE CONVERTEU EM SHOPPING CENTER: : PATRIMÔNIO E MEMÓRIA DOS TRABALHADORES DE SOROCABA/SP

In recent decades, old factory buildings - mostly weaving mills - have been used for other purposes. Thus, the cultural heritage associated with factory work loses not only its original function, but also as a propitiator of the construction of a working class memory and identity. In Sorocaba, a city in the interior of São Paulo state, known in the past as "Manchester Paulista", the buildings of the old weavings, in English architecture, have been converted into shopping malls or hypermarkets. This article seeks to discuss the cultural heritage of the workers and how to produce other articulations for the constitution of an emancipating memory of the working class based on other strategies that encompass, including, the constitution of immaterial heritages.En las últimas décadas, los edificios de las antiguas fábricas, en su mayoría fábricas textiles, se han utilizado para otras funciones. Así, el acervo cultural asociado al trabajo fabril pierde no sólo su función original, sino también como facilitador de la construcción de una memoria e identidad de la clase trabajadora. En Sorocaba, ciudad del interior de São Paulo, conocida en el pasado como “Manchester Paulista”, los edificios de las antiguas fábricas textiles, de arquitectura inglesa, se han convertido en centros comerciales o hipermercados. Este artículo busca discutir el patrimonio cultural de los trabajadores y cómo producir otras articulaciones para la constitución de una memoria emancipadora de la clase trabajadora a partir de otras estrategias que incluyen la constitución del patrimonio intangible.Nas últimas décadas, prédios de antigas fábricas – em sua maioria, tecelagens – têm sido aproveitados para outras funcionalidades. Assim, os patrimônios culturais associados ao trabalho fabril perdem não somente a sua função original, mas, também, como propiciador da construção de uma memória e identidade da classe trabalhadora. Em Sorocaba, cidade do interior paulista, conhecida no passado como “Manchester Paulista”, as construções das antigas tecelagens, em arquitetura inglesa, converteram-se em shopping centers ou hipermercados. O presente artigo procura discorrer sobre o patrimônio cultural dos trabalhadores e como produzir outras articulações para a constituição de uma memória emancipadora da classe operária a partir de estratégias outras que abarcam, inclusive, a constituição de patrimônios imateriais

Parecer sobre a realização de actividades Todo o Terreno nas escombreiras da Mina da Panasqueira

Parecer, elaborado em parceria, apresentado a diversas entidades, na sequência de notícia da SIC sobre actividades denominadas de radicais nas Escombreiras da Mina da Panasqueira

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

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost