Catalogs of Legal and Social Sciences in Pernambuco, Brazil

A criação do Curso de Sciencias Juridicas e Sociaes em Olinda, Pernambuco, exigiu a formação de uma biblioteca a partir de coleções adquiridas. O trabalho tem como objetivo principal compreender e demonstrar o alcance e as características da ordenação dos livros antigos no processo de formação da coleção original do Curso Jurídico, divulgada por meio de listas manuscritas, inventários e catálogos, que se constituem e representam a própria biblioteca de época. Pelo olhar da Bibliografia histórica, da Ciência da informação e da abordagem epistemológica foi analisado o processo catalográfico de suas obras, para a constituição da biblioteca que se firmou com a compilação de seus catálogos.The creation of the Course on Legal Sciences and Societies in Olinda, Pernambuco, required the formation of a library from acquired collections. The main objective of the work is to understand and demonstrate the scope and characteristics of the ordering of old books in the process of forming the original collection of the Legal Course, disseminated through handwritten lists, inventories and catalogs, which constitute and represent the period library itself. Through the eyes of the historical bibliography, information science and the epistemological approach, the cataloging process of his works was analyzed, for the constitution of the library that was established with the compilation of his catalogs.Dossier: Estudios del libro antiguo en América Latina: perspectivas, debates y problemasFacultad de Humanidades y Ciencias de la Educació

Catálogos de Sciencias Juridicas e Sociaes em Pernambuco, Brasil

The creation of the Course on Legal Sciences and Societies in Olinda, Pernambuco, required the formation of a library from acquired collections. The main objective of the work is to understand and demonstrate the scope and characteristics of the ordering of old books in the process of forming the original collection of the Legal Course, disseminated through handwritten lists, inventories and catalogs, which constitute and represent the period library itself. Through the eyes of the historical bibliography, information science and the epistemological approach, the cataloging process of his works was analyzed, for the constitution of the library that was established with the compilation of his catalogs

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