System complexity and policy integration challenges: The Brazilian Energy- Water-Food Nexus

The Energy-Water-Food Nexus is one of the most complex sustainability challenges faced by the world. This is particularly true in Brazil, where insufficiently understood interactions within the Nexus are contributing to large-scale deforestation and land-use change, water and energy scarcity, and increased vulnerability to climate change. The reason is a combination of global environmental change and global economic change, putting unprecedented pressures on the Brazilian environment and ecosystems. In this paper, we identify and discuss the main Nexus challenges faced by Brazil across sectors (e.g. energy, agriculture, water) and scales (e.g. federal, state, municipal). We use four case studies to explore all nodes of the Nexus. For each, we analyse data from economic and biophysical modelling sources in combination with an overview of the legislative and policy landscape, in order to identify governance shortcomings in the context of growing challenges. We analyse the complex interdependence of developments at the global and local (Brazilian) levels, highlighting the impact of global environmental and economic change on Brazil and, conversely, that of developments in Brazil for other countries and the world. We conclude that there is a need to adjust the scientific approach to these challenges as an enabling condition for stronger science-policy bridges for sustainability policy-making. © 2019 The Author(s

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

Desenvolvimento de tubos polínicos em cruzamentos entre cultivares brasileiras de macieira

O objetivo deste trabalho foi avaliar o desenvolvimento do tubo polínico em cruzamentos entre cultivares brasileiras de macieira. Realizou-se a polinização dirigida entre cultivares com mesma época de floração (34 cruzamentos). As polinizações foram realizadas em três estigmas de cada uma das dez flores emasculadas por cruzamento. O crescimento dos tubos polínicos foi avaliado por meio da técnica da fluorescência, em flores coletadas 120 horas após a polinização. Na grande maioria das polinizações cruzadas, houve alta percentagem de tubos polínicos que cresceram até o ovário. O acompanhamento do crescimento do tubo polínico pela técnica de fluorescência permite separar cruzamentos compatíveis ou parcialmente compatíveis dos incompatíveis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press