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

Marine biotechnology in Brazil: Recent developments and its potential for innovation

Marine biotechnology is an emerging field in Brazil and includes the exploration of marine microbial products, aquaculture, omics, isolation of biologically active compounds, identification of biosynthetic gene clusters from symbiotic microorganisms, investigation of invertebrate diseases caused by potentially pathogenic marine microbes, and development of antifouling compounds. Furthermore, the field also encompasses description of new biological niches, current threats, preservation strategies as well as its biotechnological potential. Finally, it is important to depict some of the major approaches and tools being employed to such end. To address the challenges of marine biotechnology, the Brazilian government, through the Ministry of Science, Technology, Innovation, and Communication, has established the National Research Network in Marine Biotechnology (BiotecMar) (www.biotecmar.sage.coppe.ufrj.br). Its main objective is to harness marine biodiversity and develop the marine bioeconomy through innovative research.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Institute of Biology and COPPE Federal University of Rio de JaneiroInstitute of Biology University of BrasiliaInstitute de Química de São Carlos Universidade de São PauloInstitute for Sea Studies Admiral Paulo MoreiraInstitute of Biological and Health Sciences Federal University of AlagoasInstitute of Medical Biochemistry Universidade Federal do Rio de JaneiroFaculty of Pharmacy and Biotechnology Center Federal University of Rio Grande do SulPhytotechny Department Federal University of Santa CatarinaAcademic Center of Vitória Federal University of PernambucoInstitute of Biology Federal Fluminense UniversityInstitute for Marine Sciences Federal University of CearáDepartment of Biological Sciences State University of Santa CruzAquaculture Center São Paulo State UniversityInstitute of Oceanography Federal University of Rio GrandeFederal University of Paraiba UFPBFederal University of Pará UFPAUniversity of São Paulo USPNorthern Rio State University UENFFederal University of Santa Catarina UFSCState University of Santa Cruz UESCFederal University of Alagoas UFALUniversidade Federal Rural de Pernambuco UFRPEFederal University of Pernambuco UFPELNCCNational Laboratory For Scientific Computing LNCCOswaldo Cruz Foundation/Rondônia FIOCRUZFederal University of Bahia UFBAUFRJOswaldo Cruz Institute IOC-FIOCRUZIOC-FIOCRUZFederal University of São Paulo UNIFESPMinistry of Health MSMCTICState University of West Rio de Janeiro UEZONational Instute of Industrial Property INPIUnBUNESPAquaculture Center São Paulo State UniversityUNESPFAPESP: N° 408968/2013-3 CNP

Tópico especiais em genética aplicada: volume 6

O presente trabalho trata-se de Tópicos Especiais em Genética com temas gerais sobre genética e assuntos como a molécula de RNA; biorremediação; melhoramento genético florestal, melhoramento clássico de alógamas e autógamas, genômica animal; genômica funcional; epidemiologia molecular de microrganismos; marcadores moleculares; PCR Quantitativa em Tempo Real e LAMP - Loop mediated isothermal amplificationNão recebi financiamentoUniversidade Estadual Paulista (Unesp), Faculdade de Ciências Agrárias e Veterinárias, Jaboticaba