Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Fatores que afetam a freqüência e o atraso escolar, nos meios urbano e rural, de São Paulo e Pernambuco

Diversos trabalhos da literatura econômica têm mostrado a influência da educação na melhoria de renda das pessoas e no desenvolvimento econômico de um país. Entretanto, para melhorar o nível médio de escolaridade de um país é importante elevar a freqüência escolar e garantir à criança o avanço nos estudos. Preocupado com essa questão o Governo Federal brasileiro realizou diversas reformas no sistema educacional, especialmente a partir da década de 1990. Em vista disso, o presente trabalho fez uma análise da influência que variáveis associadas a características pessoais e familiares de uma criança, bem como variáveis de infra-estrutura escolar exercem sobre a freqüência e o atraso escolar no ensino fundamental, comparando-se as áreas urbana e rural, de Pernambuco e São Paulo. Os resultados mostraram que políticas voltadas para melhorar a escolaridade do chefe de família e/ou a renda familiar per capita podem aumentar a freqüência e reduzir o atraso escolar. Entretanto, iniciativas voltadas para melhorar a infra-estrutura escolar deverão levar em conta a realidade econômica do estado ou região e o objetivo final a ser alcançado. Além disso, os indicadores educacionais estudados são mais precários na área rural e merecem a elaboração de políticas públicas especialmente voltadas para essa realidade.<br>Many studies in the economic field have showed the importance of education to increase the wellbeing of the society. Trying to improve the educational indicators, in the 90's, many changes were implemented in the Brazilian public school system. The objective of the present study is to evaluate school infrastructure and family characteristics affecting children's decision to study or to drop out from school (frequency and school delay in primary and secondary levels), comparing the urban and rural areas of Pernambuco and São Paulo. The results showed that policies that would increase parents' schooling and/or family income would increase frequency and decrease delay in school. However, policies that would improve the schools' infrastructure and consequently the quality of the schools would have to take the socio-economic aspects of the region into consideration as well as the type of objective to be reached. Moreover, the investments should be focused on rural areas where educational indicators are far behind

Corrective shoeing in horses: analysis of the adaptation period to the new condition imposed

Corrective shoeing is a method commonly used to alter the locomotion pattern in animals or as therapy for various disorders of the locomotive system of horses. However, to date, there have been no scientific studies discussing the period during which animals adapt to this type of intervention. The goal of this study was to evaluate the horseshoe adaptation period with the toe or heel elevated by six degrees at 0, 48, and 96 hours after each type of shoeing. For this analysis, the horses were recorded while walking on a treadmill. Stride length and gait qualitative analyzes were performed using Dvideow software. The level of significance adopted was 5%. In the present study, there was no significant difference between the evaluation times; elevating the toe or heel by six degrees do not generates discomfort during locomotion, therefore, horses are able to return to a regular exercise or training routine immediately after shoeing

Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

For more than three decades, major efforts in sampling and analyzing tree diversity in South America have focused almost exclusively on trees with stems of at least 10 and 2.5 cm diameter, showing highest species diversity in the wetter western and northern Amazon forests. By contrast, little attention has been paid to patterns and drivers of diversity in the largest canopy and emergent trees, which is surprising given these have dominant ecological functions. Here, we use a machine learning approach to quantify the importance of environmental factors and apply it to generate spatial predictions of the species diversity of all trees (dbh ≥ 10 cm) and for very large trees (dbh ≥ 70 cm) using data from 243 forest plots (108,450 trees and 2832 species) distributed across different forest types and biogeographic regions of the Brazilian Amazon. The diversity of large trees and of all trees was significantly associated with three environmental factors, but in contrasting ways across regions and forest types. Environmental variables associated with disturbances, for example, the lightning flash rate and wind speed, as well as the fraction of photosynthetically active radiation, tend to govern the diversity of large trees. Upland rainforests in the Guiana Shield and Roraima regions had a high diversity of large trees. By contrast, variables associated with resources tend to govern tree diversity in general. Places such as the province of Imeri and the northern portion of the province of Madeira stand out for their high diversity of species in general. Climatic and topographic stability and functional adaptation mechanisms promote ideal conditions for species diversity. Finally, we mapped general patterns of tree species diversity in the Brazilian Amazon, which differ substantially depending on size class