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

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

Arsenic-induced responses in Pityrogramma calomelanos (L.) Link: Arsenic speciation, mineral nutrition and antioxidant defenses

Arsenic (As) hyperaccumulation trait has been described in a limited number of fern species. The physiological basis of hyperaccumulation remains unclear, especially in non-Pteris species such as Pityrogramma calomelanos. Aiming at a better understanding of As-induced responses, P. calomelanos plants were exposed to 1 mM As for 21 days and compared with control plants. Chemical analyses revealed that As accumulation was ten times higher in pinnae then in roots and stipes. In pinnae, As was present mainly as arsenite, whereas arsenate was the dominant form in stipes and roots. Arsenic promoted an increase in antioxidant enzyme activities in both fern parts and several alterations in mineral nutrition, especially with regard to P and K. A higher content of non-protein thiols was observed in pinnae of plants exposed to As, whereas As induced the increase in lipid peroxidation in roots. The results showed that Pityrogramma calomelanos shares with Pteris vittata several aspects of As metabolism. High root-shoot As translocation showed to be essential to avoid toxic effects in roots, since the root is more sensitive to the metalloid. The higher capacity of P. calomelanos to sequester arsenite in the pinna and its efficient antioxidant system maintain the reactive oxygen species at a low level, thus enhancing the continuous accumulation of As. Molecular investigations are needed to elucidate the evolution of As-tolerance mechanisms in Pteridaceae species, especially with regard to membrane transporters and ROS signaling