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

The 2014 ALMA Long Baseline Campaign: First Results from High Angular Resolution Observations toward the HL Tau Region

Interstellar matter and star formatio

The 2014 ALMA Long Baseline Campaign: An Overview

Instrumentatio

Effect of a Shot Peening Pre Treatment on the Fatigue Behaviour of Hard Chromium on Electroless Nickel Interlayer Coated AISI 4340 Aeronautical Steel

Multiple layer systems of coatings are considered to have larger resistance to crack propagation in comparison to coatings with simple layer. With regard to fatigue, it is possible to improve the resistance of a component with the application of shot peening treatment, whose compressive residual stresses delay or eliminate the initiation and propagation of fatigue cracks. The aim of this study is to analyse the effects on rotating bending fatigue behaviour of hard chromium <FONT FACE=Symbol>&frac34;</FONT> electroless nickel multilayer system coated AISI 4340 high strength steel submitted to shot peening pre treatment. Results indicated that the interaction between the shot peening process with the multilayer system was not satisfactory, resulting in intense delamination. Fracture surface analysis by SEM was performed toward to identify the fatigue crack origin, as well as the coating-substrate delamination process