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

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

Rhodnius prolixus smells repellents: Behavioural evidence and test of present and potential compounds inducing repellency in Chagas disease vectors

International audienceInsect repellents are known since many decades ago and constitute a major tool for personal protection against the biting of mosquitoes. Despite their wide use, the understanding of why and how repellents repel is relatively recent. In particular, the question about to what extent insects other than mosquitoes are repulsed by repellents remains open. We developed a series of bioassays aimed to test the performance of well established as well as potential repellent molecules on the Chagas disease vector Rhodnius prolixus. Besides testing their ability to prevent biting, we tested the way in which they act, i.e., by obstructing the detection of attractive odours or by themselves. By using three different experimental protocols (host-biting, open-loop orientation to odours and heat-triggered proboscis extension response) we show that DEET repels bugs both in the presence and in the absence of host-associated odours but only at the highest quantities tested. Piperidine was effective with or without a host and icar-idine only repelled in the absence of a living host. Three other molecules recently proposed as potential repellents due to their affinity to the Ir40a + receptor (which is also activated by DEET) did not evoke significant repellency. Our work provides novel experimental tools and sheds light on the mechanism behind repellency in haematophagous bugs

Main effects of the predictors on the probability of occurrence of issues on the taxonomic name combinations.

<p>Factors: basisOfRecord, Geographic region, Clade, Number of records shared by Institution and Year. Issues: Synonymy, Misspellings, Conceptual errors, Format errors. “Has issue” denotes the presence of at least one of the cited issues. Effects calculated through logit GLM, with binomial response. For definition of the “Fishes” clade, see text. NS: statistically not significant.</p

Data workflow to create the Gold Standard set of vertebrate names.

<p>Data from providers participating in VertNet were gathered directly from self-hosted data sets (top left), or, for data sets that undergo data cleaning through VertNet migrators prior to publication, as provided previous to migration (top right). The table (center) shows how data were organized in distinct fields for assessment. The composition and characteristics of the 1,000 name combinations in the data set (lower) distinguishes subsets resolved by each researcher (left and right), and cross-analysis performed by both researchers at different levels of certification (check for format errors only and complete double check). DwC: Darwin Core; Sciname: scientific name; <b>con-rank</b> and <b>sn-rank:</b> taxon ranks of <b>constructedscientificname</b> and <b>scientificnameplus</b> fields respectively.</p

Summary of issues encountered in the name combinations that form the basis of the validation set.

<p>Numbers indicate name combinations that showed one or more types of issues. Total number of name combinations assessed for issues = 991, total number of those name combinations with issues = 532, total number of those name combinations with errors (misspelling, conceptual or format error) = 341.</p