A Queda do Céu: ensinamentos da cosmoecologia Yanomami

Neste artigo, busca-se apresentar os resultados de uma pesquisa de iniciação científica, onde foi estudado sobre os ensinamentos que a cosmoecologia dos Yanomami poderiam trazer no contexto contemporâneo do Antropoceno, denominação atual da nova era geológica cuja atuação antrópica tem impacto planetário. Procura-se destacar, na cosmologia Yanomami, quais aspectos que remetem à compreensão de sua relação com as categorias humanidade/mundo, com destaque para a noção de humanidade estendida e de mundos plurais. A cosmoecologia configura-se na relação dos seres com o  meio ambiente, a partir da interpretação da narrativa cosmológica. A seguir, é apresentada uma contra-antropologia, nas considerações do líder e xamã Davi Kopenawa acerca do “povo da mercadoria”. Ainda neste tópico, discorre-se sobre a polissemia do termo matihi na cultura yanomami, que vai desde objetos de troca, mercadorias, à objetos ritualísticos e por fim, também fornecem a chave de compreensão do princípio das trocas e socialidade deste povo, com ênfase no desapego e na generosidade. O terceiro e último tópico apresenta o mito escatológico yanomami que fala da queda do céu, interpretando-o também como um alerta frente à destruição da floresta amazônica e a degradação ambiental causada pelo desmatamento para diversos fins e pelo garimpo ilegal, causando danos irreversíveis à saúde dos Yanomami e ao equilíbrio deste imenso bioma.  Por fim, busca-se extrair os ensinamentos de cada aspecto discorrido, como possibilidades e aberturas à modos outros de ser e estar no  planeta comum denominado Terra, com vistas à preservação e cuidado a todas as formas de existência

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

Reflexões acerca de indicadores de sustentabilidade em comunidades locais: do desenvolvimento sustentável à sustentabilidade socioambiental - qualificando o diálogo com as diferenças

Este artigo procura ressaltar a importância de se fazer uso de abordagens qualitativas e participativas na elaboração de indicadores de sustentabilidade aplicado diretamente a comunidades locais, sugerindo uma proposta de ampliar o conceito de desenvolvimento sustentável para o conceito de sustentabilidade socioambiental,. Na medida em que estas abordagens servem de abertura ao diálogo com atores sociais específicos, consequentemente, pode impulsionar à formação de uma cidadania ambiental, e assim, uma maior equanimização entre os quatro vetores da sustentabilidade socioambiental: o institucional, o econômico, o ambiental e o social. Foi adotado como exemplo descritivo, o Diagnóstico Rural Participativo  - DRP.Palavras chave: Indicadores de Sustentabilidade Socioambiental; Comunidades Locais; Cidadania Ambienta

Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications