SPATIO-TEMPORAL PATTERN AND FACTORS ASSOCIATED WITH TUBERCULOSIS MORTALITY IN A NORTHEASTERN STATE - BRAZIL

Objective: to identify the spatio-temporal pattern of tuberculosis mortality and its related factors.Method: ecological study, using as unit of analysis the municipalities of the state of Ceará, Brazil, during the period from 2001 to 2017. Tuberculosis mortality was analyzed by temporal and spatial analysis techniques.Results: in the period, 1,513 deaths from tuberculosis were reported. An average annual increase of 15% in mortality was detected (95% Confidence Interval: 6.2 - 24.6). The indicators that most influenced mortality were life expectancy at birth (β=3.38), households with inadequate water supply and sanitation (β=-0.01) and probability of survival to 60 years (β=-2.26).Conclusion: this study evidenced the increase in the temporal pattern of tuberculosis mortality over the years. Care strategies aimed at treatment adherence and public health strategies aimed at improving the environment of the population should therefore be emphasized

PATRÓN ESPACIO-TEMPORAL Y FACTORES ASOCIADOS A LA MORTALIDAD POR TUBERCULOSIS EN UN ESTADO DEL NORESTE - BRASIL

Objetivo: identificar el patrón espacio-temporal de la mortalidad por tuberculosis y los factores relacionados.Método: Estudio ecológico, utilizando como unidad de análisis los municipios del estado de Ceará, Brasil, durante 2001 a 2017. La mortalidad por tuberculosis se analizó mediante técnicas de análisis temporal y espacial.Resultados: se notificaron 1.513 muertes por tuberculosis en el periodo. Se detectó un aumento medio anual del 15% de la mortalidad (intervalo de confianza del 95%: 6,2 - 24,6). Los indicadores que más influyeron en la mortalidad fueron: la esperanza de vida al nacer (β=3,38), los hogares con suministro de agua y saneamiento inadecuados (β=-0,01) y la probabilidad de sobrevivir hasta los 60 años (β=-2,26).Conclusión: este estudio evidenció el aumento del patrón temporal de la mortalidad por tuberculosis a lo largo de los años. Por lo tanto, se debe hacer hincapié en las estrategias de atención dirigidas a la adherencia al tratamiento y en las estrategias de salud pública dirigidas a mejorar el entorno de la población

PADRÃO ESPAÇO-TEMPORAL E FATORES ASSOCIADOS À MORTALIDADE POR TUBERCULOSE EM UM ESTADO DO NORDESTE– BRASIL

Objetivo: identificar o padrão espaço-temporal da mortalidade por tuberculose e seus fatores a ela relacionados.Método: estudo ecológico, usando como unidade de análise os municípios do estado do Ceará, Brasil, durante o período de 2001 a 2017. A mortalidade por tuberculose foi analisada por técnicas de análise temporal e espacial.Resultados: no período, foram notificados 1.513 óbitos por tuberculose. Detectou-se aumento anual médio de 15% na mortalidade (Intervalo de Confiança 95%: 6,2 – 24,6). Os indicadores que mais influenciaram a mortalidade foram: esperança de vida ao nascer (β=3,38), domicílios com abastecimento de água e esgotamento sanitário inadequados (β=-0,01) e probabilidade de sobrevivência até os 60 anos (β=-2,26).Conclusão: este estudo evidenciou o aumento no padrão temporal da mortalidade por tuberculose ao longo dos anos. Deve-se, portanto, enfatizar estratégias de cuidado voltadas à adesão ao tratamento e de saúde pública voltadas à melhoria do ambiente da população

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info: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 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

Anais do V Encontro Brasileiro de Educomunicação: Educação midiática e políticas públicas

A presente coletânea, que chega ao público através de um suporte digital, tem como objetivo disponibilizar os papers, bem como os relatos de experiências educomunicativas apresentados durante o V ENCONTRO BRASILEIRO DE EDUCOMUNICAÇÃO, que teve como tema central: “Educação Midiática e Políticas Públicas”. O evento foi realizado em São Paulo, entre 19 e 21 de setembro de 2013, a partir de uma parceria entre o NCE/USP - Núcleo de Comunicação e Educação da USP, a Licenciatura em Educomunicação da ECA/USP, a ABPEducom – Associação Brasileira de Pesquisadores e Profissionais da Educomunicação e a FAPCOM – Faculdade Paulus de Tecnologia e Comunicação, que ofereceu seu campus, na Vila Mariana, para os atos do evento. Os presentes anais disponibilizam o texto de abertura, de autoria do coordenador geral do evento, denominado “Educação midiática e políticas públicas: vertentes históricas da emergência da Educomunicação na América Latina”. Na sequência, apresentam 61 papers sobre aspectos específicos da temática geral, resultantes de pesquisas na área, seguidos de 27 relatos de práticas educomunicativas, em nível nacional

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

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