Uses of GBIF in scientific research

Peer-reviewed research citing GBIF as a data source, with at least one author from Sudan.
For all researches, please visit our "Peer-reviewed publications" page.

List of publications

  • Samy A, van de Sande W, Fahal A, Peterson A (2014)

    Mapping the potential risk of mycetoma infection in Sudan and South Sudan using ecological niche modeling

    PLoS neglected tropical diseases 8(10) e3250.

    In 2013, the World Health Organization (WHO) recognized mycetoma as one of the neglected tropical conditions due to the efforts of the mycetoma consortium. This same consortium formulated knowledge gaps that require further research. One of these gaps was that very few data are available on the epidemiology and transmission cycle of the causative agents. Previous work suggested a soil-borne or Acacia thorn-prick-mediated origin of mycetoma infections, but no studies have investigated effects of soil type and Acacia geographic distribution on mycetoma case distributions. Here, we map risk of mycetoma infection across Sudan and South Sudan using ecological niche modeling (ENM). For this study, records of mycetoma cases were obtained from the scientific literature and GIDEON; Acacia records were obtained from the Global Biodiversity Information Facility. We developed ENMs based on digital GIS data layers summarizing soil characteristics, land-surface temperature, and greenness indices to provide a rich picture of environmental variation across Sudan and South Sudan. ENMs were calibrated in known endemic districts and transferred countrywide; model results suggested that risk is greatest in an east-west belt across central Sudan. Visualizing ENMs in environmental dimensions, mycetoma occurs under diverse environmental conditions. We compared niches of mycetoma and Acacia trees, and could not reject the null hypothesis of niche similarity. This study revealed contributions of different environmental factors to mycetoma infection risk, identified suitable environments and regions for transmission, signaled a potential mycetoma-Acacia association, and provided steps towards a robust risk map for the disease.

  • Parra-Quijano M, Iriondo J, Torres E (2011)

    Improving representativeness of genebank collections through species distribution models, gap analysis and ecogeographical maps

    Biodiversity and Conservation 21(1) 79-96.

    An efficient germplasm collecting method was evaluated using six Lupinus species and the Spanish Lupinus collection as a study case. This method includes the application of geographic information systems, ecogeographical land characterization maps, species distribution models and gap analysis to identify prioritized collecting sites. To evaluate the efficiency of this collecting method, field collecting expeditions were carried out focusing on prioritized sites and the results of these collections were analyzed. Prioritized sites were identified using spatial and ecogeographical gaps, and potential species richness maps. The spatial gaps corresponded to populations non-included in the collection but recorded by other information sources while ecogeographical gaps corre- sponded to spatial gaps that were located in ecogeographical categories (obtained from the ecogeographical map) that were scarcely represented in the collection. A potential Lupinus species richness map was obtained by adding the information of single maps of Lupinus species distribution models. Subsequently, prioritized sites were obtained in ecogeo- graphical gaps with high potential species richness values. Collecting expeditions were made in Spain in 2006, 2007 and 2008. Results showed that using the efficient germplasm collecting methodology was highly positive not only from a quantitative viewpoint (between 7.8 and 11% increase) but also in qualitative terms, focusing collection efforts in ecogeographical categories with low or null representation in the Spanish Lupinus collection (41% of the new accessions). Phenotypic differences related to adaptation to environment were observed in the field between the populations that grow in low or null represented categories and those that grow in highly represented categories.

    Keywords: Agrobiodiversity, Collecting indices, Efficient germplasm collection, Genebank representativeness, Lupinus