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

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

Long term application of pig manure on the chemical and physical properties of Brazilian Cerrado soil

Intensive pig farming is an important economic activity and generates a large amount of liquid pig manure as a by-product, which is considered a promising resource for the fertilization of tropical soils, characterized as low natural fertility. In an agricultural area under no tillage soybean-corn cropping system, located in southwest of Brazil, an experiment was carried out with different forms of fertilization; that is, organic fertilization with pig manure (17 years) at different rates of application and with mineral fertilization. Regarding the pig manure application rate, with yearly carbon load of 50 m3 ha−1 tended to promote the mineralization of organic matter, with formation of humic substances and to improve the size of aggregates. The use of LPM promoted little soil carbon addition varying of 0.05-3.41 kg ha−1 with 17 years of LPM application and the continuous application of pig tended to be advantageous for the tropical soil, providing a positive carbon balance, which favored the soil and the environment through the rational waste disposal

Expression of EGF receptors in canine prostate with proliferative inflammatory atrophy and carcinoma

<div><p>ABSTRACT: Gene expression of ErbB1 and ErbB2, and immunostaining of EGFR (Her1) and Her2 (c-erbB-2) were evaluated in this study to ascertain whether these receptors are involved in the evolution of canine premalignant and malignant prostatic lesions, as proliferative inflammatory atrophy (PIA) and prostatic carcinoma (PC). With regards to the intensity of EGFR immunostaining, there was no difference between normal prostatic tissue and tissues with PIA or PC. In relation to Her2 immunostaining, there were differences between normal prostatic tissue and those with PIA and PC, as also differences between prostates with PIA and PC. There was no correlation between EGFR and Her2 immunostaining. ErbB1 gene product was detected in two normal tissue samples, in one with PIA, and in all samples with PC. ErbB2 mRNA was recorded in two canine samples with PIA, in all with PC, but was not detected in normal prostatic tissue. It was concluded that EGFR and Her2 play roles in canine PIA and PC, suggesting that those receptors may be involved in canine prostatic carcinogenesis.</p></div

Assessing arsenic, cadmium, and lead contents in major crops in Brazil for food safety purposes

AbstractThe food chain is one of the major sources of human exposure to non-essential trace elements (TEs) present in soils. Human exposure to contaminated food is a worldwide health concern and a food safety issue that threatens agricultural trade. To assess the quality of Brazilian food products with respect to non-essential TEs, we evaluated arsenic (As), cadmium (Cd), and lead (Pb) contents in five major crops grown in Brazil: rice, wheat, corn, soybeans, and potatoes. The samples were collected from field trials with a record of long-term use of phosphate fertilizers in the states of Mato Grosso and Minas Gerais, Brazil. The TE concentrations in soils were all bellow the maximum allowable concentrations for agricultural soils. The mean concentrations of As, Cd, and Pb (μgkg−1 dry weight) were as follows: below the detection limit <15, 29, and <40 for rice; 19, 23, and 64 for wheat; 47, 40, and 95 for corn; 65, 23, and 106 for soybeans; and 59, 22, and <40 for potatoes, respectively. Significant differences were found in the As and Cd contents of the different wheat cultivars. The levels of As, Cd, and Pb found in the studied crops are well below the values reported in the literature and are in accordance with the Codex Alimentarius and the European Union and Brazilian guidelines, indicating that the concentrations of these elements in the crops do not pose a risk to human health