Viabilidade Técnica E Econômica Da Irrigação Localizada Do Cafeeiro, Nas Condições Climáticas Do Planalto De Araxá, Mg

In the region of Araxá highlands, the economical production of coffee is traditionally made without irrigation. Notwithstanding in recent years, with climate change, water deficit of 150 mm have been verified, affecting the vegetative and productive development of the culture. Within this context, the aim of this study was to evaluate supplementary irrigation to increase production and profitability of the coffee grown in the highlands of Araxá, compared to a non-irrigated and irrigated cultivation throughout the year. The work was implemented in Araxá, Minas Gerais in 2006 and carried out throughout the period of nine years. Different periods of water stress (from April to November) were evaluated, compared with irrigation throughout the year and the witness. After 6 consecutive harvests, it can be concluded that supplemental irrigation promoted an increased productivity in the coffee grown under the conditions of the Araxá Plateau, especially in years of drought. With regard to economic performance, the process of irrigation applied throughout the year promoted profits of 279% (R$/ha year-1) compared to the treatment without irrigation. © 2016, Editora UFLA. All rights reserved.11334735

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