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, 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

Indicadores epidemiológicos aplicáveis a estudos sobre a associação entre saneamento e saúde de base municipal Epidemiological indicators applied to studies about association between water supply and sanitation and health based on data at municipal level

É relativamente recente no país a prática da vigilância ambiental em saúde, sendo que a vigilância da qualidade da água para consumo humano, parte integrante da vigilância ambiental em saúde, ressente-se de estudos e pesquisas que forneçam suporte científico à formulação de instrumentos para a prática de tal vigilância. Nesse campo, a formulação e seleção de indicadores epidemiológicos constituem atividade essencial para representar os efeitos da insuficiência das ações de saneamento sobre a saúde humana e, portanto, como ferramenta para a vigilância e orientação de programas e planos de alocação de recursos em saneamento. O presente artigo é parte de um trabalho mais abrangente, elaborado para selecionar indicadores sanitários como sentinelas na prevenção e controle de doenças e agravos relacionados ao saneamento. Neste artigo são enfocados os indicadores epidemiológicos utilizados naquele estudo, apresentando a revisão bibliográfica, resultados da estatística descritiva desses indicadores, a discussão e conclusões sobre os indicadores epidemiológicos mais apropriados para serem utilizados emestudos dessa natureza. Destacam-se, como indicadores convenientes, a mortalidade infantil, a mortalidade até cinco anos por doenças diarréicas e a morbidade até cinco anos por doenças diarréicas com base na MDDA - monitorização de doenças diarréicas agudas.<br>Environmental health surveillance has been recently implemented in Brazil. Drinking water quality surveillance, a fundamental aspect of the environmental health surveillance, lacks specific studies and research to provide scientific background for its practice. In this field, the identification and selection of epidemiological indicators are essential to provide means to evaluate the impact of deficiencies of water supply and sanitation on human health. So, these indicators are powerful tools for the establishment of drinking water surveillance programs, as well as for identification of priorities, rational planning and funding of water supply and sanitation projects. The present paper is part of a broader study on the selection of sanitary indicators to be used as "sentinel indicators" for prevention and control of diseases associated to water and sanitation. In this context, this paper presents a brief literature review, descriptive statistics of some epidemiological indicators collected from municipalities of 4 Brazilian States, as well as a discussion on the applicability of these indicators in studies of this nature. Among the epidemiological indicators evaluated, infant mortality, diarrhoea mortality in children under 5 years old and the diarrhoea morbidity in children under 5 years old based on data from the Brazilian Monitoring of Acute Diarrhoeal Disease program seem to be the more adequate

Notes for genera – Ascomycota

Knowledge of the relationships and thus the classification of fungi, has developed rapidly with increasingly widespread use of molecular techniques, over the past 10--15 years, and continues to accelerate. Several genera have been found to be polyphyletic, and their generic concepts have subsequently been emended. New names have thus been introduced for species which are phylogenetically distinct from the type species of particular genera. The ending of the separate naming of morphs of the same species in 2011, has also caused changes in fungal generic names. In order to facilitate access to all important changes, it was desirable to compile these in a single document. The present article provides a list of generic names of Ascomycota (approximately 6500 accepted names published to the end of 2016), including those which are lichen-forming. Notes and summaries of the changes since the last edition of `Ainsworth Bisby's Dictionary of the Fungi' in 2008 are provided. The notes include the number of accepted species, classification, type species (with location of the type material), culture availability, life-styles, distribution, and selected publications that have appeared since 2008. This work is intended to provide the foundation for updating the ascomycete component of the ``Without prejudice list of generic names of Fungi'' published in 2013, which will be developed into a list of protected generic names. This will be subjected to the XIXth International Botanical Congress in Shenzhen in July 2017 agreeing to a modification in the rules relating to protected lists, and scrutiny by procedures determined by the Nomenclature Committee for Fungi (NCF). The previously invalidly published generic names Barriopsis, Collophora (as Collophorina), Cryomyces, Dematiopleospora, Heterospora (as Heterosporicola), Lithophila, Palmomyces (as Palmaria) and Saxomyces are validated, as are two previously invalid family names, Bartaliniaceae and Wiesneriomycetaceae. Four species of Lalaria, which were invalidly published are transferred to Taphrina and validated as new combinations. Catenomycopsis Tibell Constant. is reduced under Chaenothecopsis Vain., while Dichomera Cooke is reduced under Botryosphaeria Ces. De Not. (Art. 59)