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

Multiplicação in vitro DE Ficus carica L.: efeito da cinetina e do ácido giberélico In vitro multiplication of Ficus carica L.: kinetin and giberelic acid effects

A cultura da figueira é afetada pelo vírus-do-mosaico e a cultura de tecidos é uma alternativa para se proceder à limpeza clonal. Neste trabalho, objetivou-se estudar o efeito da cinetina e GA3 na multiplicação in vitro da figueira. Segmentos nodais foram inoculados em meio de cultura WPM contendo as seguintes combinações de cinetina (0; 0,5; 1; 2 e 4 mg.L-1) e GA3 (0, 2, 4, 6 e 8 mg.L-1). Avaliaram-se número e comprimento dos brotos, peso da matéria fresca e seca da parte aérea, número de raízes, peso da matéria fresca e seca do sistema radicular e de calos. A utilização de 0,5 mg.L-1 de cinetina promoveu melhor taxa de multiplicação in vitro de Ficus carica. O GA3 reduziu a formação e multiplicação dos brotos e induziu ao estiolamento, à hiperidricidade, clorose e necrose apical das plântulas.<br>The fig culture is affected by mosaic virus and the tissue culture is an alternative in the clonal cleaning. The kinetin and GA3 effects on in vitro fig multiplication was studied. Nodal segments were inoculated in WPM culture medium containing the following combination of kinetin (0, 0.5, 1, 2 and 4 mg.L-1) and GA3 (0, 2, 4, 6 and 8 mg.L-1). The number and length, fresh and dry weigh matter of aerial part, number of roots, fresh and dry weight matter of root system and fresh and dry weight matter of callus were evaluated. The use of kinetin 0.5 mg.L-1 promoted higher rates of in vitro Ficus carica multiplication. The GA3 reduced the formation and shoot multiplication, and induced etiolation, hyperhydricity, clorosis and apical necrosis at the plantlets

A gestão do conhecimento como técnica de controle: uma abordagem crítica da conversão do conhecimento tácito em explícito

A gestão do conhecimento como tecnologia de gestão é um tema emergente nos espaços acadêmicos e organizacionais. Porém, observa-se que as pesquisas e a literatura sobre o tema têm enfatizado os aspectos funcionalistas, menosprezado questões referentes ao controle e à dominação dos trabalhadores envolvidos por esta tecnologia. A partir da década de 1970, diferentes abordagens propondo alternativas à perspectiva funcionalista, até então amplamente dominante, começaram a ganhar corpo nos estudos organizacionais. Entre elas, destaca-se a perspectiva crítica, que se consolidou no contexto anglo-saxão, nos anos 1990, com a criação e o desenvolvimento do movimento denominado critical management studies, ou seja, estudos críticos em administração. O objetivo deste artigo é abordar de forma crítica a gestão do conhecimento; mais especificamente, a conversão do conhecimento tácito em explícito. Para tanto, foi dividido em cinco partes: introdução, descrição da origem e dos conceitos de gestão do conhecimento, origem e conceitos em estudos críticos em administração, abordagem crítica da gestão do conhecimento e considerações finais