Morphological Analysis of Air Sacs in the Red-Winged Tinamou (Rhynchotus rufescens Temminck, 1815)

The red-winged tinamou (Rhynchotus rusfencens) is a bird belonging to the order Tinaniforme, family Tinamidae, present in South America, and due to its population decline is classified as LC (Least Concern) on the BirdLife International red list. This study aimed to evaluate the air sacs of this species, as anatomical studies of partridges are scarce. Ten cadaveric specimens were collected, and latex perfusion was used to solidify the material. The cervical air sac in the red-winged tinamou is smaller and has a more irregular conformation than other air sacs. The thoracic air sacs are symmetrical, and the cranial thoracic air sacs are smaller than the caudal ones. The abdominal air sacs are asymmetrical, and the largest, extending to the cloaca. Only one clavicular air sac was found, with three subdivisions: right, left, and medial. Additionally, right, and left extra-coelomatic portions were found, passing under the clavicle. In one of the animals, the latex-filled humeri were found, and in three other ribs, vertebral diverticula were present. There is no clear relationship between taxonomy and biology versus the quantity and conformation of air sacs, as different animals with taxonomic proximity present differences. This study enhances species-specific anatomical knowledge of the red-winged tinamou

Socio-environmental sustainability: a case study in the good future community in barcarena in the Paraense amazon / Sustentabilidade socioambiental: um estudo de caso na comunidade do futuro bom em barcarena, na amazônia Paraense

The present article brings some critical reflections regarding the socio - spatial and environmental condition of the Comunidade of Bom Futuro, in the municipality of Barcarena - PA. These are observations made from the field work, aiming to carry out an analysis of the impacts caused in the community, having as main instrument the geographic analysis observed in the field, the empirical data of the local inhabitants and secondary data, which provide the basis for this discussion , these data will be discussed from the results obtained by the tables and graphs of the tool of analysis of the state of sustainability - MESMIS. The results show that the use of natural resources and socio-spatial and environmental changes have drastically transformed the local landscape, demonstrating that the interest of the capital invested by the company Hydro Alunorte linked to the Norwegian group Norsk Hydro aims at the unrestrained use of resources, without guaranteeing quality of life of the majority of the population. It concludes that the systematization through MESMIS reached a value considered far below the critical level of its global sustainability (Note 2.5: 10.0), which proposes immediate actions by the public power to soften the current situation in the community in question. 

Discrimination based on sexual orientation against MSM in Brazil : a latent class analysis

Introdução: A discriminação por orientação sexual (DPOS) pode influenciar a vulnerabilidade ao HIV aumentando a exposição a comportamentos sexuais de risco entre homens que fazem sexo com homens (HSH). Objetivos: Examinar dados utilizando a análise de classes latentes (ACL) para identificar grupos de indivíduos com padrões específicos de DPOS. Métodos: Estudo transversal com entrevistados recrutados pelo processo amostral respondent driven sampling em 12 cidades brasileiras em 2016. A ACL foi usada para caracterizar o DPOS entre HSH com base em 13 variáveis do bloco de discriminação do questionário da pesquisa. As proporções de DPOS e das variáveis de interesse, bem como seus intervalos de confiança (95%) foram ponderados usando o estimador de Gile. Resultados: A maioria era de jovens, solteiros, com alguma religião, escolaridade média ou superior, cor da pele preta ou parda e com nível socioeconômico médio. Mais da metade referiu ter sido discriminado nos últimos 12 meses por sua orientação sexual (65%), mais de um terço referiu ter tido medo de andar em lugares públicos nos últimos 12 meses e em torno de um quinto dos participantes reportaram ter sofrido agressão física ou sexual na vida. A DPOS foi classificada em 4 classes latentes, “muito alta”, “alta”, “média” e “baixa”, com estimativas de 2,2%, 16,4%, 35,1% e 46,19%, respectivamente. Conclusão: Observou-se alta proporção de discriminação entre os HSH participantes deste estudo. A utilização da ACL discriminou de maneira parcimoniosa as classes de DPOS.Introduction: Discrimination based on sexual orientation can influence vulnerability to HIV, increasing exposure to risky sexual behavior among men who have sex with men (MSM). Objectives: To analyze data using latent class analysis (LCA) to identify groups of individuals with specific patterns of discrimination based on sexual orientation (DSO). Methods: Cross-sectional study using respondent-driven sampling in 12 Brazilian cities in 2016. LCA was used to characterize discrimination among MSM based on 13 variables in the survey questionnaire. The proportions of men reporting DSO and other variables of interest were estimated using Gile’s Successive Sampling estimator. Results: Most MSM were young, single, had a religion, had a high school or college degree, black or brown skin color, and socioeconomic status classified as average. More than half of the participants reported that they had been discriminated against during the last 12 months due to their sexual orientation (65%), more than a third said they had felt afraid of walking in public places during the past 12 months, and about one-fifth of participants reported having been victims of physical or sexual assault due to DSO. DSO was classified into four latent classes: “very high”, “high”, “moderate” and “low”, with estimates of 2.2%, 16.4%, 35.1%, and 46.19%, respectively. Conclusion: We observed a high proportion of discrimination against MSM in this study. The use of LCA differentiated parsimoniously classes of discrimination

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

The biogeography of the Amazonian tree flora

We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Withinplot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central–eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia