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

Detection of cheese whey in raw milk preserved with bronopol® through high performance liquid chromatography

High performance liquid chromatography was used in order to detect cheese whey in samples of raw milk preserved with Bronopol®. Six samples were collected and divided in 45 aliquots of 40mL. From these, 15 were used as control and stored frozen, 15 were added with Bronopol® and stored at 7ºC, and the other 15 were added with Bronopol® and stored at 30ºC. In all groups, five levels of cheese whey addition (0, 2, 5, 10, and 20%) were tested. The samples were submitted to high performance liquid chromatography on the 2nd, 4th, and 8th days of storage. A completely random design was used, following the factorial scheme (5x3x3) and the results were compared through the non-parametric Kruskal-Wallis test. There was no difference among the treatments (P>0.05), which allows the conclusion that raw milk preserved with Bronopol® may be used for the determination of cheese whey addition in milk through high performance liquid chromatography