Distinct Genetic Lineages of Bactrocera caudata (Insecta: Tephritidae) Revealed by COI and 16S DNA Sequences

The fruit fly Bactrocera caudata is a pest species of economic importance in Asia. Its larvae feed on the flowers of Cucurbitaceae such as Cucurbita moschata. To-date it is distinguished from related species based on morphological characters. Specimens of B. caudata from Peninsular Malaysia and Indonesia (Bali and Lombok) were analysed using the partial DNA sequences of cytochrome c oxidase subunit I (COI) and 16S rRNA genes. Both gene sequences revealed that B. caudata from Peninsular Malaysia was distinctly different from B. caudata of Bali and Lombok, without common haplotype between them. Phylogenetic analysis revealed two distinct clades, indicating distinct genetic lineage. The uncorrected ‘p’ distance for COI sequences between B. caudata of Malaysia-Thailand-China and B. caudata of Bali-Lombok was 5.65%, for 16S sequences from 2.76 to 2.99%, and for combined COI and 16S sequences 4.45 to 4.46%. The ‘p’ values are distinctly different from intraspecific ‘p’ distance (0–0.23%). Both the B. caudata lineages are distinctly separated from related species in the subgenus Zeugodacus – B. ascita, B. scutellata, B. ishigakiensis, B. diaphora, B. tau, B. cucurbitae, and B. depressa. Molecular phylogenetic analysis indicates that the B. caudata lineages are closely related to B. ascita sp. B, and form a clade with B. scutellata, B. ishigakiensis, B. diaphora and B. ascita sp. A. This study provides additional baseline for the phylogenetic relationships of Bactrocera fruit flies of the subgenus Zeugodacus. Both the COI and 16S genes could be useful markers for the molecular differentiation and phylogenetic analysis of tephritid fruit flies

Engolo and Capoeira. From Ethnic to Diasporic Combat Games in the Southern Atlantic

This article provides a re-examination of the main Afrocentric narrative of capoeira origins, the engolo or ‘Zebra Dance’, in light of historical primary sources and new ethnographic evidence gathered during fieldwork in south-west Angola. By examining engolo’s bodily techniques, its socio-historical context and cultural meanings, the piece emphasises its insertion into a pastoral lifestyle and highlights the relatively narrow ethnic character of the practice in Angola. This analysis and the comparison with capoeira helps us to develop certain hypotheses about the formation, migration, and re-invention of diasporic combat games between southern Angola and coastal Brazil, and more broadly, to increase our understanding of how African cultures spread across the southern Atlantic

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

100 Years of Scientific Evolution of Work and Organizational Psychology: A Bibliometric Network Analysis From 1919 to 2019

In this study, we explore a 100 years of Work and Organizational Psychology (WOP). To do this, we carry out a bibliometric performance and network analysis (BPNA) to understand the evolution structure and the most important themes in the field of study. To perform the BNPA, 8,966 documents published since 1919 were exported from the Web of Science and Scopus databases. The SciMAT software was used to process data and to create the evolution structure, the strategic diagram, and the thematic network structure of the strategic themes of the field of WOP. We identified 29 strategic clusters and discuss the most important themes (motor themes) and their relationship with other clusters. This research presents the complete evolution of the field of study, identifying emerging themes and others with a high degree of development. We hope that this work will support researchers and future research in the field of WOP

International Society of Human and Animal Mycology (ISHAM)-ITS reference DNA barcoding database - the quality controlled standard tool for routine identification of human and animal pathogenic fungi

Human and animal fungal pathogens are a growing threat worldwide leading to emerging infections and creating new risks for established ones. There is a growing need for a rapid and accurate identification of pathogens to enable early diagnosis and targeted antifungal therapy. Morphological and biochemical identification methods are time-consuming and require trained experts. Alternatively, molecular methods, such as DNA barcoding, a powerful and easy tool for rapid monophasic identification, offer a practical approach for species identification and less demanding in terms of taxonomical expertise. However, its wide-spread use is still limited by a lack of quality-controlled reference databases and the evolving recognition and definition of new fungal species/complexes. An international consortium of medical mycology laboratories was formed aiming to establish a quality controlled ITS database under the umbrella of the ISHAM working group on "DNA barcoding of human and animal pathogenic fungi." A new database, containing 2800 ITS sequences representing 421 fungal species, providing the medical community with a freely accessible tool at http://www.isham.org and http://its.mycologylab.org/ to rapidly and reliably identify most agents of mycoses, was established. The generated sequences included in the new database were used to evaluate the variation and overall utility of the ITS region for the identification of pathogenic fungi at intra-and interspecies level. The average intraspecies variation ranged from 0 to 2.25%. This highlighted selected pathogenic fungal species, such as the dermatophytes and emerging yeast, for which additional molecular methods/genetic markers are required for their reliable identification from clinical and veterinary specimens.This study was supported by an National Health and Medical Research Council of Australia (NH&MRC) grant [#APP1031952] to W Meyer, S Chen, V Robert, and D Ellis; CNPq [350338/2000-0] and FAPERJ [E-26/103.157/2011] grants to RM Zancope-Oliveira; CNPq [308011/2010-4] and FAPESP [2007/08575-1] Fundacao de Amparo Pesquisa do Estado de So Paulo (FAPESP) grants to AL Colombo; PEst-OE/BIA/UI4050/2014 from Fundacao para a Ciencia e Tecnologia (FCT) to C Pais; the Belgian Science Policy Office (Belspo) to BCCM/IHEM; the MEXBOL program of CONACyT-Mexico, [ref. number: 1228961 to ML Taylor and [122481] to C Toriello; the Institut Pasteur and Institut de Veil le Sanitaire to F Dromer and D Garcia-Hermoso; and the grants from the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) and the Fundacao de Amparo a Pesquisa do Estado de Goias (FAPEG) to CM de Almeida Soares and JA Parente Rocha. I Arthur would like to thank G Cherian, A Higgins and the staff of the Molecular Diagnostics Laboratory, Division of Microbiology and Infectious Diseases, Path West, QEII Medial Centre. Dromer would like to thank for the technical help of the sequencing facility and specifically that of I, Diancourt, A-S Delannoy-Vieillard, J-M Thiberge (Genotyping of Pathogens and Public Health, Institut Pasteur). RM Zancope-Oliveira would like to thank the Genomic/DNA Sequencing Platform at Fundacao Oswaldo Cruz-PDTIS/FIOCRUZ [RPT01A], Brazil for the sequencing. B Robbertse and CL Schoch acknowledge support from the Intramural Research Program of the NIH, National Library of Medicine. T Sorrell's work is funded by the NH&MRC of Australia; she is a Sydney Medical School Foundation Fellow.info:eu-repo/semantics/publishedVersio

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives