Origem e distribuição das principais artérias do membro torácico de Cuniculus paca (Linnaeus, 1766)

RESUMO: Objetivou-se descrever as artérias do membro torácico da paca (Cuniculos paca Linanaeus, 1766), mediante a dissecação da região. Para tanto, foram utilizadas 10 pacas adultas, machos ou fêmeas, pesando entre cinco e 10 kg do plantel de pacas do setor de Animais Silvestres da FCAV, Unesp, Jaboticabal-SP. Nos animais, injetou-se látex pela artéria carótida comum esquerda para preencher e corar todo o sistema arterial, seguido pela fixação em formaldeído a 10% e conservação em solução salina a 30% para dissecação anatômica das principais artérias do arco aórtico, braço e antebraço, identificando-se a origem e distribuição destes vasos. Os resultados foram foto documentados e discutidos com base na literatura sobre os animais domésticos, e roedores selvagens. De forma geral, as artérias do membro torácico da paca, assemelham-se com as dos carnívoros domésticos, do rato e da cobaia

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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