Cultura material y espacios cotidianos: mobiliario y enseres domésticos en la ciudad de Córdoba a fines del siglo XVIII

Dentro del amplio espectro de objetos que conformaron el entrono material cotidiano de los habitantes de la ciudad de Córdoba a fines del siglo XVIII, nos concentraremos en el mobiliario y los enseres domésticos, dejando para otros trabajos el análisis de la vestimenta, los objetos de lujo, los objetos religiosos, la alimentación y la vivienda. Además de ser objetos utilitarios, los muebles reflejan el nivel social de la familia, manifiestan el estilo de vida, valores y personalidad de los dueños de casa. No sólo dejan ver cuestiones de nivel económico, sino también cultural, el ritmo de vida y los hábitos domésticos de los miembros de la familia. El mobiliario y los enseres domésticos están estrechamente ligados con el espacio, es decir, con la vivienda y sus distintas habitaciones, por tal motivo, trataremos de hacernos una imagen de los espacios dentro de la vivienda, los muebles y demás objetos propios de éstas. Cabe destacar que no existió en los hogares cordobeses de fines del siglo XVIII, gran variedad de muebles, y algunos son, como veremos más adelante, comunes a distintas habitaciones, y no propios o específicos de algún cuarto en particular. Las cartas de dote, de capital, los inventarios post mortem y los testamentos, son invaluables fuentes que nos ofrecen una amplia y rica información sobre los diversos objetos propios de las viviendas cordobesas, el trabajo con estos documentos nos permite formarnos una imagen de ese entorno material cotidiano y, trascendiendo lo descriptivo, analizar esos objetos dentro de las prácticas sociales de las que son parte. A partir de la observación de este grupo de objetos pretendemos demostrar que los bienes materiales contribuyen a definir el lugar que se ocupa en la sociedad ya que también tienen un significado social, y la gente los utiliza como elemento de comparación, diferenciación, superación de otros grupos, para expresar individualidad o afinidad, etc.Facultad de Humanidades y Ciencias de la Educació

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

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

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