Ondas acopladas a convecção na região de África equatorial

Mestrado em Meteorologia e Oceanografia FísicaO clima da região da África equatorial é caracterizado por algumas das tempestades mais intensas associadas a convecção profunda. Esta convecção, na maior parte das vezes, deve-se a perturbações no campo do vento que se propagam para Leste ou para Oeste com velocidades típicas. Estas perturbações podem ser estudadas através do modelo de águas pouco profundas, conforme sugerido por Matsuno (1966), facto que vem sendo comprovado por diversos estudos com base em dados observados. Existem poucas publicações sobre as características de propagação de Sistemas Convectivos de Mesoescala (SCM) na região da África Equatorial. Porém, alguns dos estudos disponíveis revelaram que parte desses SCM é controlada por Ondas Equatoriais. Neste trabalho são analisados alguns dos aspectos dessas ondas, que estarão associados à formação e propagação de SCM que afectam a região. O período seleccionado para estudo inclui os meses de Março, Abril e Maio de 2012. Com base em dados simulados pelo Modelo WFR e dados OLR (Outgoing Longwave Radiation) das reanálises Era-Interim, identificaram-se eventos SCM e, através da análise da energia das ondas equatoriais e do campo da divergência da circulação projectada sobre essas ondas, foi possível identificar alguns eventos sugestivos da existência de acoplamento entre ondas equatoriais e sistemas convectivos. Identificaram-se eventos propagando-se para Oeste em associação com ondas de Rossby-gravíticas mistas e ondas gravítico-inerciais. No período entre 10 e 15 de Abril, observou-se a propagação para Leste de um sistema convectivo de larga escala, acoplado a ondas de Kelvin.The climate of Africa Equatorial is characterized by some of the more intense storms associated with deep convection. This convection is most often due to disturbances in the wind field that propagates eastward or westward with typical speeds. These disturbances can be studied by the shallow water model, as suggested by Matsuno (1966), a fact that has been proven by several studies based on observed data. There are few publications on the propagation characteristics of Mesoscale Convective Systems (MCS) in the Africa Equatorial region. However, some of the existent studies have shown that some of the MCS are controlled by Equatorial Waves. In this study, some aspects of these waves, which are associated with the formation and propagation of MCS affecting the region Equatorial Africa are analysed. The period selected for this study involves the months of March, April and May 2012. Based on the data simulated by the WRF (Weather Research and Forecast) model, and on the OLR (Outgoing Longwave Radiation) of reanalysis ERA-Interim, it was possible to identify MCS events. By analysing the energy of equatorial waves and the divergence of the flow field projected on these waves, it was possible to identify some events suggesting the existence of equatorial waves coupled to the convection systems. The identified events include westward propagating SCMs associated with mixed Rossby-gravity waves and with westward propagating inertial gravity waves. It was also possible to identify a large-scale convection system propagating eastwards coupled with Kelvin waves in de period from 10 to 15 April

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

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