Projeto arte e vida de Van Gogh / Van gogh's art and life Project

O projeto “Arte e Vida de Van Gogh” foi realizado na Escola Municipal das Acácias, escola pública  localizada na Rua das Camélias, Parque Primavera, Itaguaí, Rio de Janeiro, durante o primeiro  semestre de 2021. O projeto foi coordenado pelo professor Fábio De Macedo, sob a supervisão da  professora Elinete Nascimento, contando com oito licenciandos do Pibid-Belas Artes 2020 da Universidade  Federal Rural do Rio de Janeiro com bolsa da CAPES. Devido ao período da Pandemia da Covid 19  que impossibilitou atividades educativas presenciais com os alunos do 6° ao 9° ano do Ensino  Fundamental, utilizamos as tecnologias digitais de informação e comunicação. Para tanto, buscamos  na literatura especializada conhecer sobre Metodologias Ativas, Sala de Aula Invertida, Ensino Híbrido  e Gamificação, possibilidades metodológicas e uso de ferramentas não presenciais. Para basearmos  as habilidades e competências a serem desenvolvidas consideramos os marcos normativos vigentes,  como a Base Nacional Comum Curricular de 2018, o Plano Pedagógico do curso de Licenciatura em  Belas Artes e o Projeto Político Pedagógico da citada escola. Os alunos foram devidamente  sensibilizados a fazer a inscrição através do Google formulário que contou com aulas síncronas através  do Google Meet e assíncronas a partir de videoaulas postadas no canal do Youtube criado para o  projeto e disponibilizadas no grupo do WhatsApp e plataforma Google Sala de aula. Além das  videoaulas foram disponibilizados quiz, imagens, links e textos. Os trabalhos dos alunos foram expostos  em mural virtual através do Padlet. Os alunos foram avaliados através da participação, formulários,  jogos e dos trabalhos recebidos. Realizamos avaliações diagnósticas, antes da realização do projeto,  avaliações formativas e avaliação qualitativa durante todo o processo de ensino-aprendizagem mediado  por debates em uma relação pedagógica horizontal. A experiência se demonstrou um desafio enriquecedor  à formação de todos os atores envolvidos: pesquisadores, docentes, licenciandos, alunos e direção da  unidade escolar.

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

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq