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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 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,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 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

Genetic structure analysis of Eufriesea violacea (Hymenoptera, Apidae) populations from southern Brazilian Atlantic rainforest remnants

Random amplified polymorphic DNA (RAPD) markers were used to analyze the genetic structure of Eufriesea violacea populations in three fragments (85.47, 832.58 and 2800 ha) of Atlantic rainforest located in the north of the Brazilian state of Paraná. A total of twelve primers produced 206 loci, of which 129 were polymorphic (95% criterion). The proportions of polymorphic loci in each population ranged from 57.28% to 59.2%, revealing very similar levels of genetic variability in the groups of bees from each fragment. Unbiased genetic distances between groups ranged from 0.0171 to 0.0284, the smallest genetic distance occurring between bees from the two larger fragments. These results suggest that the E. violacea populations from the three fragments have maintained themselves genetically similar to native populations of this species originally present in northern Paraná