Amêndoa de macaúba: incentivo à agricultura familiar por meio do desenvolvimento de produtos

A amêndoa de macaúba, rica em lipídeos, proteínas, fibras e minerais, é um ingrediente promissor para a elaboração de alimentos. Este projeto, uma parceria entre UFV, UFOP e UFMG, teve como objetivo promover o uso desta amêndoa junto a famílias afetadas pelo rompimento da barragem do Fundão e pelos efeitos econômicos causados pela pandemia de COVID-19, a partir da elaboração e divulgação de alimentos saudáveis. Agricultoras familiares de Goiabeiras/MG foram o público-alvo por fabricarem produtos para a merenda escolar e pelo fato de já possuírem a palmeira macaúba presente em suas propriedades. Foram desenvolvidos bolos, cookies, cocadas e extratos solúveis utilizando a amêndoa, os quais foram submetidos às análises de composição nutricional e sensorial. O projeto culminou com a realização de oficinas e cartilhas sobre a elaboração dos produtos. Acredita-se que a comercialização desses produtos seja uma oportunidade de geração de renda para aqueles que vivem do extrativismo da macaúba

Impacto do manejo dos resíduos da colheita, do preparo do solo e da adubação na produtividade de eucalipto

Tem sido cada vez maior a preocupação das empresas do setor florestal em adotar práticas pautadas na conservação do solo e da água. Nesse sentido, este trabalho teve por objetivo avaliar o impacto do manejo dos resíduos da colheita, do preparo do solo e do uso de resíduos industriais, na fertilidade do solo e produtividade de eucalipto. O experimento foi iniciado após o corte raso de um plantio comercial de EUCALYPTUS GRANDIS, onde os resíduos da colheita foram manejados (retirada de todo o resíduo; remoção da casca e dos galhos com diâmetro superior a 3,0 cm; e manutenção de todos os resíduos na superfície do solo). Em seguida, realizaram-se o preparo do solo (com subsolador de uma e três hastes), a aplicação dos resíduos industriais (resíduo de celulose e cinzas) na superfície do solo e o plantio de mudas de EUCALYPTUS GRANDIS X E. UROPHYLLA Foi utilizado o delineamento em blocos ao acaso, contendo oito tratamentos e quatro repetições. Os tratamentos consistiram da combinação dos diferentes tipos de manejo dos resíduos da colheita, preparo do solo e aplicação dos resíduos industriais. Cada parcela experimental foi composta por cinco linhas com 19 plantas cada. Aos 83 meses após o plantio, foram medidos o DAP (diâmetro à altura do peito) e a altura das árvores, para cálculo do volume de madeira. A fertilização e a manutenção dos resíduos da colheita florestal elevaram os teores de Ca2+ e Mg2+ trocáveis no solo. A manutenção total dos resíduos vegetais na área após a colheita resultou em aumento de 71,7 m³ ha-1 de madeira, quando comparado à remoção de todos os resíduos. Não houve diferença entre os modos de preparo do solo com subsolador de uma e três hastes, quanto ao volume de madeira. Os maiores volumes de madeira foram obtidos dos tratamentos que receberam as maiores quantidades de resíduo de celulose e cinzas, ao mesmo tempo em que foi mantida parte do resíduo vegetal após a colheita. A aplicação do resíduo de celulose e cinzas favoreceu a manutenção e, ou, aumento da produtividade do eucalipto

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others