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

Alterações morfofisiológicas em folhas de Coffea arabica L. cv. "Oeiras" sob influência do sombreamento por Acacia mangium Willd Morphophysiological alterations in leaves of Coffea arabica L. cv. 'Oeiras' shaded by Acacia mangium Willd

Diferenças na disponibilidade de radiação podem causar modificações na estrutura e função das folhas do cafeeiro, que podem responder de maneira diferencial à radiação por alterações morfológicas, anatômicas, de crescimento e na taxa fotossintética. O objetivo deste trabalho foi avaliar características morfofisiológicas de cafeeiros (Coffea arabica L. cv. "Oeiras") sombreados por acácia (Acacia mangium Willd.) na época seca e chuvosa no sul de Minas Gerais. As maiores taxas fotossintéticas e maiores espessuras da epiderme adaxial foram observadas na estação chuvosa nas linhas de cafeeiros a pleno sol. O sombreamento influenciou em menor espessura das folhas e em espaços intercelulares maiores no tecido esponjoso. Foi também verificada mudança na forma dos cloroplastos, os quais apresentaram-se mais alongados em folhas de cafeeiros a pleno sol quando relacionados aos arborizados.Light availability is one of the most important environmental factors affecting leaf structure and functions in coffee plants that can respond differently to radiation by changes in leaf anatomy, morphology, growth and photosynthetic rate. The objective of this research was evaluate some morphophysiological aspects in leaves of coffee (Coffea arabica L. cv. 'Oeiras') cropped under shelter trees in the south of Minas Gerais during the rainy and dry season. The shade caused lower leaves thickness and higher intercellular spaces in spongious tissue. There was also verified a change in chloroplast shape, which showed more elongated in coffee tree kept at full sunlight in relation to that ones maintained on shading