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

Description of a new species of cecidomyiid (Diptera: Cecidomyiidae) predator of mealybugs (Hemiptera: Pseudococcidae) on sugarcane

Diadiplosis saccharum sp. nov. (Diptera: Cecidomyiidae) is described based on male and female prey on nymphs of mealybug Saccharicoccus sacchari (Cockerell) (Hemiptera: Pseudococcidae) on Saccharum spp. (Poaceae) in São Paulo State, Brazil. Herein, the genus is composed by 33 species. The key of the eight species of the Diadiplosis distributed in Brazil is updated

Mortality of Diatraea saccharalis is affected by the pH values of the spore suspension of Beauveria bassiana and Metarhizium anisopliae

ABSTRACT Fungal virulence is multifaceted and dependent on multiple factors including the pH of the spore suspension. In this study, we accessed effects of six pH values of Beauveria bassiana, and Metarhizium anisopliae medium for the growth, sporulation, and mortality on sugarcane stalk borer Diatraea saccharalis. The culture of fungi was performed onplates containing the PDA (Potato Dextrose Agar) medium. Virulence was tested in D. saccharalis larvae distributed in four replicates of 15 larvae. To evaluate the performance of the isolates, they were grown at different pH values in an artificial chitin medium to confirm the degradation capacity of the fungi at each pH. No significant difference was observed for the sporulation at pH ranged from 4 to 9 for both fungi. In the mortality assay, larval mortality was higher at pH 7 and 8 for both fungi, reaching 87% for B. bassiana and 81% for M. anisopliae