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1.
  • Hudson, Lawrence N, et al. (författare)
  • The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
  • 2017
  • Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 7:1, s. 145-188
  • Tidskriftsartikel (refereegranskat)abstract
    • The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
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2.
  • Hudson, Lawrence N., et al. (författare)
  • The PREDICTS database : a global database of how local terrestrial biodiversity responds to human impacts
  • 2014
  • Ingår i: Ecology and Evolution. - : Wiley. - 2045-7758. ; 4:24, s. 4701-4735
  • Tidskriftsartikel (refereegranskat)abstract
    • Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
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3.
  • González-De Schroeder, María Mercedes, et al. (författare)
  • Vigilancia ambiental de la circulación de poliovirus en tres municipios considerados como punto transitorio de migrantes en Colombia 2017-2019
  • 2022
  • Ingår i: Infectio. - : Asociacion Colombiana de Infectologia - ACIN. - 0123-9392 .- 2422-3794. ; 26:2, s. 107-112
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To determine the circulation of poliovirus in three municipalities considered as transitory points for migrants in Colombia. Material and Method: Wastewater samples (n = 36) were collected from border municipalities, selected for greater transit of regular and irregular migrants, in the period between 2017-2019. The samples were concentrated and cultured following the World Health Organization (WHO) environmental surveillance algorithm for poliovirus circulation. Molecular identification was performed by polymerase chain reaction using group-specific, serotype and sabin vaccine strain primers. Results: The presence of non-polio Enterovirus (NPV) was detected in the environmental samples obtained and no circulation of poliovirus derived from the vaccine or wild poliovirus was found in the three evaluated municipalities; However, in two previous studies published by Gonzales et al with a similar methodology in 2005 and 2015 evaluating the wastewater of the city of Armenia-Quindío; It was possible to identify the presence of virus derived from vaccine, with negative results for the identification of wild poliovirus. Conclusions: The findings indicate that the wastewater monitoring system in order to determine the presence of viruses is a useful tool to carry out environmental surveillance.
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4.
  • Mahecha, Miguel D., et al. (författare)
  • Earth system data cubes unravel global multivariate dynamics
  • 2020
  • Ingår i: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 11:1, s. 201-234
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model- data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries.
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