36 research outputs found
ExigĂȘncia nutricional de lisina para galinhas poedeiras de ovos brancos e ovos marrons, no segundo ciclo de produção: 2. caracterĂsticas produtivas
Extratores de cåpsulas porosas para o monitoramento da condutividade elétrica e do teor de potåssio na solução de um solo
Mechanical and thermal behavior of polyvinyl alcohol reinforced with aligned carbon nanotubes
ExigĂȘncia nutricional de metionina+cistina para galinhas poedeiras de ovos brancos e marrons, no segundo ciclo de produção: 1. caracterĂsticas produtivas
Estratificação in vitro de embriÔes zigóticos de pessegueiro em diferentes meios de cultura e concentraçÔes de sacarose
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,5â7 vast areas of the tropics remain understudied.8â11 In
the American tropics, Amazonia stands out as the worldâs 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.13â15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazonâs 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 regionâs vulnerability to environmental change. 15%â18% 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