Seleção de espécies de abelhas para avaliação de risco ambiental de algodoeiro GM no Cerrado brasileiro

The objective of this work was to list potential candidate bee species for environmental risk assessment (ERA) of genetically modified (GM) cotton and to identify the most suited bee species for this task, according to their abundance and geographical distribution. Field inventories of bee on cotton flowers were performed in the states of Bahia and Mato Grosso, and in Distrito Federal, Brazil. During a 344 hour sampling, 3,470 bees from 74 species were recovered, at eight sites. Apis mellifera dominated the bee assemblages at all sites. Sampling at two sites that received no insecticide application was sufficient to identify the three most common and geographically widespread wild species: Paratrigona lineata, Melissoptila cnecomola, and Trigona spinipes, which could be useful indicators of pollination services in the ERA. Indirect ordination of common wild species revealed that insecticides reduced the number of native bee species and that interannual variation in bee assemblages may be low. Accumulation curves of rare bee species did not saturate, as expected in tropical and megadiverse regions. Species‑based approaches are limited to analyze negative impacts of GM cotton on pollinator biological diversity. The accumulation rate of rare bee species, however, may be useful for evaluating possible negative effects of GM cotton on bee diversity. O objetivo deste trabalho foi listar espécies de abelhas candidatas potenciais para análise de risco ambiental (ARA) de algodoeiros geneticamente modificados (GM) e identificar as espécies de abelhas mais adequadas para essa finalidade, de acordo com sua abundância e distribuição geográfica. Inventários de abelhas em flores de algodoeiro foram realizados nos estados da Bahia e do Mato Grosso, e no Distrito Federal. Durante 344 horas de amostragem, foram coletadas 3.470 abelhas de 74 espécies, em oito locais. Apis mellifera dominou as assembleias de abelhas em todos os locais. A amostragem em dois locais que não receberam aplicação de inseticidas foi suficiente para identificar as três species de abelhas silvestres mais comuns e de distribuição geográfica mais ampla: Paratrigona lineata, Melissoptila cnecomola e Trigona spinipes, as quais poderiam ser usadas como indicadoras de serviços de polinização na ARA. A ordenação indireta de espécies silvestres comuns revelou que os inseticidas reduziram o número de espécies de abelhas nativas e que a variação interanual nas assembleias de abelhas pode ser baixa. As curvas de acumulação de espécies raras de abelhas não saturaram, conforme esperado em regiões tropicais e megadiversas. As abordagens baseadas em espécies são limitadas para avaliar os impactos negativos de algodoeiros GM sobre a diversidade biológica de polinizadores. A taxa de acumulação de espécies raras de abelhas, no entanto, pode ser útil para avaliar os possíveis efeitos negativos de algodoeiros GM sobre a diversidade de abelhas

Data standardization of plant-pollinator interactions

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.Fil: Salim, José A. Universidade de Sao Paulo; BrasilFil: Saraiva, Antonio M.. Universidade de Sao Paulo; BrasilFil: Zermoglio, Paula Florencia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Patagonia Norte. Instituto de Investigaciones En Recursos Naturales, Agroecologia y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones En Recursos Naturales, Agroecologia y Desarrollo Rural.; ArgentinaFil: Agostini, Kayna. Universidade Federal do São Carlos; BrasilFil: Wolowski, Marina. Universidade Federal de Alfenas; BrasilFil: Drucker, Debora P.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Soares, Filipi M.. Universidade de Sao Paulo; BrasilFil: Bergamo, Pedro J.. Jardim Botânico do Rio de Janeiro; BrasilFil: Varassin, Isabela G.. Universidade Federal do Paraná; BrasilFil: Freitas, Leandro. Jardim Botânico do Rio de Janeiro; BrasilFil: Maués, Márcia M.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Rech, Andre R.. Universidade Federal dos Vales do Jequitinhonha e Mucuri; BrasilFil: Veiga, Allan K.. Universidade de Sao Paulo; BrasilFil: Acosta, Andre L.. Instituto Tecnológico Vale; BrasilFil: Araujo, Andréa C. Universidade Federal do Mato Grosso do Sul; BrasilFil: Nogueira, Anselmo. Universidad Federal do Abc; BrasilFil: Blochtein, Betina. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Freitas, Breno M.. Universidade Estadual do Ceará; BrasilFil: Albertini, Bruno C.. Universidade de Sao Paulo; BrasilFil: Maia Silva, Camila. Universidade Federal Rural Do Semi Arido; BrasilFil: Nunes, Carlos E. P.. University of Stirling; BrasilFil: Pires, Carmen S. S.. Empresa Brasileira de Pesquisa Agropecuaria (embrapa);Fil: Dos Santos, Charles F.. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Queiroz, Elisa P.. Universidade de Sao Paulo; BrasilFil: Cartolano, Etienne A.. Universidade de Sao Paulo; BrasilFil: de Oliveira, Favízia F. Universidade Federal da Bahia; BrasilFil: Amorim, Felipe W.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Fontúrbel, Francisco E.. Pontificia Universidad Católica de Valparaíso; ChileFil: da Silva, Gleycon V.. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Consolaro, Hélder. Universidade Federal de Catalão; Brasi

Data standardization of plant–pollinator interactions

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of termsinfo:eu-repo/semantics/publishedVersio

Caracterização da proteina H-NS relacionada a patogenicidade de Xylella fastidiosa

Orientador: Anete Pereira de SouzaTese (doutorado) - Universidade Estadual de Campinas, Instituto de BiologiaDoutorad

DPP-T50-6_S6_L001_R2_001_QC

Zipped Fastq file (R2) of the sequenced TruSeq-Illumina library of the gut contents of Harmonia axyridis 96 hours after feeding

DPP-T50-2_S2_L001_R2_001_QC

Zipped Fastq file (R2) of the sequenced TruSeq-Illumina library of the gut contents of Harmonia axyridis immediately after feeding

Unveiling the diet of predatory mites through DNA metabarcoding—can abiotic factors affect prey detectability?

Despite the importance of predatory mites as biological control agents, the way that generalist species can maintain in agrosystems, the alternative prey they can feed on, the way they choose to eat one prey, or another are poorly known. For some phytoseiid predatory mite species, prey consumption has been characterized by lab tests (Cavalcante et al., 2015, 2017; Juan-Blasco et al., 2012; Oliveira et al., 2007). However, those approaches are sometimes difficult to perform, very time consuming and do not totally reflect interactions occurring in field conditions. New technologies that allow determining the diet of predatory mites in situ are highly desirable to supporting biological control programs. A promising avenue for deciphering the diet of predatory mites is offered by DNA metabarcoding. Although this approach has been used in the study of insects (Hosseini et al., 2008; Kaunisto et al., 2017; Paula et al., 2022), only starts to be applied to microarthropod biological control agents, as predatory mites (Navia et al., 2019). DNA metabarcoding was successfully applied to identify prey species of phytoseiid mites using group-specific primers. However, biotic and abiotic factors can affect the detectability of predatory mite preys through metabarcoding, as previously showed for studies using traditional molecular methods (=PCR Multiplex and Sanger sequencing) (Pérez-Sayas et al., 2015). This information is relevant to understanding the limits of using the methodology, to guide sample collection procedures, and to assure the correct interpretation of the results

DPP-T50-4_S4_L001_R1_001_QC

Zipped Fastq file (R1) of the sequenced TruSeq-Illumina library of the gut contents of Harmonia axyridis 24 hours after feeding

DPP-T50-5_S5_L001_R2_001_QC

Zipped Fastq file (R2) of the sequenced TruSeq-Illumina library of the gut contents of Harmonia axyridis 48 hours after feeding