Seasonal precipitation in eastern Amazon during rainy season: regional observations and RegCM3 simulations

This paper presents a contribution on the climate modelling studies with emphasis on seasonal rainfall variability in eastern Amazonia, during the austral summer and autumn seasons (DJF and MAM). Based on RegCM3 regional climate simulations for a 26 years period (1982/83 to 2007/08) using high resolution domain scale (30 km) and two different convection schemes (Grell and MIT), it was investigated the model performance to simulate the regional pluviometric distribution in eastern Amazon, with reference to a new observational data base containing regional aspects extracted from a dense rain gauge station network. The quantitative analysis showed that RegCM3 presents systematic errors, especially those related to the dry bias in the Amapá and north/northeast of Pará using both schemes Grell and MIT, which indicate that the model does not reproduce ITCZ characteristics over equatorial Atlantic. The simulations using MIT also indicated wet bias in the southwest/south/southeast of Pará and north of Tocantins. Moreover, through composites technique, it was also investigated RegCM3 response to reproduce the anomalous spatial rainfall patterns in association with ENSO episodes and interhemispheric SSTa gradient phases across the intertropical Atlantic. The results showed that the model represented realistically well the spatial pattern related to the rainfall anomalies above (below) than normal in most of eastern Amazonia, during the known favourable scenarios, i.e., La Niña and south Atlantic SSTa gradient (unfavourable, i.e., El Niño and north Atlantic SSTa gradient).O presente trabalho apresenta uma contribuição aos estudos de modelagem climática com ênfase na variabilidade pluviométrica sazonal da Amazônia oriental, durante as estações de verão e outono (DJF e MAM). Baseado nos resultados das simulações regionais do RegCM3 para um período de 26 anos (1982/83 a 2007/08) e usando domínio em alta resolução espacial (30 Km) e dois diferentes esquemas de convecção (Grell e MIT), foi investigado o desempenho do modelo em simular a distribuição regional de precipitação sazonal na Amazônia oriental, com referência a um novo conjunto de dados observacional compilado com informações de uma ampla rede integrada de estações pluviométricas. As análises quantitativas evidenciaram que o RegCM3 apresenta erros sistemáticos, sobretudo aqueles relacionados com viés seco no Amapá e norte/nordeste do Pará usando ambos os esquemas Grell e MIT, os quais apontam que o modelo não reproduz as características da ZCIT sobre o Atlântico equatorial. As simulações usando MIT, também apresentaram viés úmido no sudoeste/sul/sudeste do Pará e norte do Tocantins. Além disso, através da técnica de composições, também foi investigado o desempenho do RegCM3 em reproduzir os padrões espaciais anômalos de precipitação sazonal em associação aos episódios ENOS, e as fases do gradiente térmico sobre o Atlântico intertropical. Os resultados demonstraram que o modelo conseguiu representar realisticamente bem o padrão espacial das anomalias pluviométricas acima (abaixo) do normal em grande parte da Amazônia oriental, durante os conhecidos cenários favoráveis, i.e., condições de La Niña e gradiente de aTSM para o Atlântico sul (desfavoráveis, i.e., El Niño e gradiente de aTSM para o Atlântico norte

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

Responses of the geometric indices of heart rate variability to the active orthostatic test in women

OBJECTIVES: The effects of the orthostatic test on the cardiovascular system have been investigated, but there are no data on the behavior of the geometric indices of heart rate variability. We evaluated the effects of the active orthostatic test on the geometric indices of heart rate variability in women. METHOD: The study was performed on 12 healthy women between ages 18 and 30. For the analysis of heart rate variability, heart rate was recorded beat-to-beat. The RR intervals were transformed into geometric figures, and from these we calculated the triangular index, the triangular interpolation of RR intervals, the SD1, SD2 indexes and the SD1/SD2 ratio, which were obtained from the Poincaré plot. Visual analysis of the plot was also performed. For the test, participants quickly stood up from a seated position in 3 seconds or less, and remained standing still for 15 minutes. Heart rate variability samples were collected at four moments: rest, 0-5 minutes, 5-10 minutes and 10-15 minutes at standing position. RESULTS: The triangular index, the triangular interpolation of RR intervals, the SD1 and SD2 indices were reduced (p < 0.05) at 10-15 minutes after the volunteers stood up from seated position. The SD1/SD2 ratio was decreased at 0-15 minutes after the subjects changed from seated to orthostatic position.OBJETIVOS: Os efeitos do teste ortostático sobre o sistema cardiovascular já foram investigados, mas não há dados sobre o comportamento dos índices geométricos de variabilidade da frequência cardíaca. Aqui,f oram avaliados os efeitos do teste ortostático ativo nos índices geométricos de variabilidade da frequência cardíaca em mulheres. MÉTODO: O estudo foi realizado em 12 mulheres saudáveis com idades entre 18 e 30 anos. Para a análise da variabilidade da frequência cardíaca, este parâmetro foi registrado batimento a batimento. Os intervalos RR foram transformados em figuras geométricas e, a partir destas, foi calculado o índice triangular, a interpolação triangular dos intervalos RR, o SD1, SD2 e a relacão SD1/SD2, que foram obtidos a partir da plotagem de Poincaré. A análise visual do gráfico foi também realizada. Para o teste, os participantes levantaram-se rapidamente de uma posicão sentada (em 3 segundos ou menos) e permaneceram imóveis, de pé, por 15 minutos. Amostras de variacão de frequência cardíaca foram coletadas em quatro momentos: repouso, 0-5 minutos, 5-10 minutos e 10-15 minutos a pé. RESULTADOS: O índice triangular, a interpolacão triangular dos intervalos RR, o SD1 e SD2 índices apresentaram-se reduzidos (p < 0,05) no intervalo 10-15 minutos depois de os voluntários se levantarem. A relacãoSD1/SD2 apresentou-se reduzida durante o intervalo 0-15 minutos depois dos participantes passarem à posicão ortostática. CONCLUSÃO: Os índices geométricos de variabilidade da freqüência cardíaca diminuiram em resposta ao teste ortostático ativo em mulheres saudáveis

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora