Project description:As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover.
Project description:Fungi are key players in vital ecosystem services, spanning carbon cycling, decomposition, symbiotic associations with cultivated and wild plants and pathogenicity. The high importance of fungi in ecosystem processes contrasts with the incompleteness of our understanding of the patterns of fungal biogeography and the environmental factors that drive those patterns. To reduce this gap of knowledge, we collected and validated data published on the composition of soil fungal communities in terrestrial environments including soil and plant-associated habitats and made them publicly accessible through a user interface at https://globalfungi.com . The GlobalFungi database contains over 600 million observations of fungal sequences across?>?17 000 samples with geographical locations and additional metadata contained in 178 original studies with millions of unique nucleotide sequences (sequence variants) of the fungal internal transcribed spacers (ITS) 1 and 2 representing fungal species and genera. The study represents the most comprehensive atlas of global fungal distribution, and it is framed in such a way that third-party data addition is possible.
Project description:Trees play a key role in the structure and function of many ecosystems worldwide. In the Mediterranean Basin, forests cover approximately 22% of the total land area hosting a large number of endemics (46 species). Despite its particularities and vulnerability, the biodiversity of Mediterranean trees is not well known at the taxonomic, spatial, functional, and genetic levels required for conservation applications. The WOODIV database fills this gap by providing reliable occurrences, four functional traits (plant height, seed mass, wood density, and specific leaf area), and sequences from three DNA-regions (rbcL, matK, and trnH-psbA), together with modelled occurrences and a phylogeny for all 210 Euro-Mediterranean tree species. We compiled, homogenized, and verified occurrence data from sparse datasets and collated them on an INSPIRE-compliant 10 × 10 km grid. We also gathered functional trait and genetic data, filling existing gaps where possible. The WOODIV database can benefit macroecological studies in the fields of conservation, biogeography, and community ecology.
Project description:MotivationFreshwater insects comprise 60% of freshwater animal diversity; they are widely used to assess water quality, and they provide prey for numerous freshwater and terrestrial taxa. Our knowledge of the distribution of freshwater insect diversity in the USA is incomplete because we lack comprehensive, standardized data on their distributions and functional traits at the scale of the contiguous United States (CONUS). We fill this knowledge gap by presenting Freshwater insects CONUS: A database of freshwater insect occurrences and traits for the contiguous United States. This database includes 2.05 million occurrence records for 932 genera in the major freshwater insect orders, at 51,044 stream locations sampled between 2001 and 2018 by federal and state biological monitoring programmes. Compared with existing open-access databases, we tripled the number of occurrence records and locations and added records for 118 genera. We also present life-history, dispersal, morphological and ecological traits and trait affinities (analogous to fuzzy-coded traits) for 1,007 stream insect genera, assembled from existing databases, reference books and the primary literature. We nearly doubled the number of traits for 11 trait groups and added traits for 180 genera that were not available from open-access databases. Our database, Freshwater insects CONUS, facilitates the mapping of freshwater insect taxonomic and functional diversity and, when paired with environmental data, will provide a powerful resource for quantifying how the environment shapes stream insect diversity and taxon-specific distributions.Main types of variables containedGeoreferenced occurrence records and traits for stream insects.Spatial location and grainContiguous United States at a grain of c. 1 m2.Time period and grainOccurrence records from January 2001 to December 2018, with 1-day temporal resolution. Traits from January 1911 to December 2018.Major taxa and level of measurementGenera from the orders Coleoptera, Diptera, Ephemeroptera, Hemiptera, Lepidoptera, Megaloptera, Neuroptera, Odonata, Plecoptera and Trichoptera.Software format.csv.
Project description:Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity [wc]), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc, and nt). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index (lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.
Project description:UnlabelledA motif is a short DNA or protein sequence that contributes to the biological function of the sequence in which it resides. Over the past several decades, many computational methods have been described for identifying, characterizing and searching with sequence motifs. Critical to nearly any motif-based sequence analysis pipeline is the ability to scan a sequence database for occurrences of a given motif described by a position-specific frequency matrix.ResultsWe describe Find Individual Motif Occurrences (FIMO), a software tool for scanning DNA or protein sequences with motifs described as position-specific scoring matrices. The program computes a log-likelihood ratio score for each position in a given sequence database, uses established dynamic programming methods to convert this score to a P-value and then applies false discovery rate analysis to estimate a q-value for each position in the given sequence. FIMO provides output in a variety of formats, including HTML, XML and several Santa Cruz Genome Browser formats. The program is efficient, allowing for the scanning of DNA sequences at a rate of 3.5 Mb/s on a single CPU.Availability and implementationFIMO is part of the MEME Suite software toolkit. A web server and source code are available at http://meme.sdsc.edu.
Project description:Background:The dataset with 49,726 bryophytes occurrences (49,261 moss occurrences and 465 liverworts occurrences), located predominantly on the territory European north-east Russia, is described in this data paper. The dataset was based on the digitised moss labels from the Institute of Biology of Komi Scientific ?enter of the Ural Branch of the Russian Academy of Sciences herbarium (SYKO). The information from the labels was recognised, cleaned and brought into compliance with the Darwin Core. More than 99.9% of occurrences were georeferenced with a precision of at least 3 km. For each occurrence, the original label image URL was given. The dataset contains occurrences of 539 moss and liverworts taxa (species and lower ranks) belonging to 190 genera and 75 families. New information:Information about 49,726 bryophytes occurrences was published in GBIF. The dataset was based on label data of 94% of SYKO herbarium moss collection specimens. Most of the occurrences were described with the following fields: occurrenceID, institutionID, collectionCode, catalogNumber, basisOfRecord, scientificName, taxonRank, kingdom, phylum, class, order, family, genus, recordedBy, identifiedBy, associatedMedia, day, month, year, country, countryCode, decimalLatitude, decimalLongitude, geodeticDatum, coordinateUncertaintyInMetres, georeferencedBy.
Project description:Global mean temperature is thought to have exceeded that of today during the last interglacial episode (LIG, ~ 125,000 yrs b.p.) but robust paleoclimate data are still rare in low latitudes. Occurrence data of tropical reef corals may provide new proxies of low latitude sea-surface temperatures. Using modern reef coral distributions we developed a geographically explicit model of sea surface temperatures. Applying this model to coral occurrence data of the LIG provides a latitudinal U-shaped pattern of temperature anomalies with cooler than modern temperatures around the equator and warmer subtropical climes. Our results agree with previously published estimates of LIG temperatures and suggest a poleward broadening of the habitable zone for reef corals during the LIG.
Project description:The Flanders Environment Agency (VMM) has been performing biological water quality assessments on inland waters in Flanders (Belgium) since 1989 and sediment quality assessments since 2000. The water quality monitoring network is a combined physico-chemical and biological network, the biological component focusing on macro-invertebrates. The sediment monitoring programme produces biological data to assess the sediment quality. Both monitoring programmes aim to provide index values, applying a similar conceptual methodology based on the presence of macro-invertebrates. The biological data obtained from both monitoring networks are consolidated in the VMM macro-invertebrates database and include identifications at family and genus level of the freshwater phyla Coelenterata, Platyhelminthes, Annelida, Mollusca, and Arthropoda. This paper discusses the content of this database, and the dataset published thereof: 282,309 records of 210 observed taxa from 4,140 monitoring sites located on 657 different water bodies, collected during 22,663 events. This paper provides some background information on the methodology, temporal and spatial coverage, and taxonomy, and describes the content of the dataset. The data are distributed as open data under the Creative Commons CC-BY license.
Project description:Background:The Volga basin is one of the most industrially-developed regions of Russia with a high degree of anthropogenic impact on natural ecosystems. Human influence negatively affects the species diversity and number of animals, including reptiles. There are no endemic species in the reptile fauna of the Volga basin. The herpetofauna of the region makes up 25% of the reptile fauna of Russia (Dunaev and Orlova 2017). We began to study the fauna of reptiles and their distribution in the Volga basin in 1988. Although we registered 20 reptile species in the Volga basin to date, apparently this is not a complete list of species in the region (Bakiev et al. 2004, Bakiev et al. 2009a, Bakiev et al. 2015, Kirillov et al. 2020). The distribution of reptiles in this region is not fully understood. New information:Our dataset contains information on reptile occurrences in the Volga River basin. The dataset is based on original research by the staff of the Laboratory of Herpetology and Toxinology and Laboratory of Population Ecology of the Institute of Ecology of the Volga River basin of the Russian Academy of Sciences and Joint Directorate of the Mordovia State Nature Reserve and National Park "Smolny". A total of 5,086 occurrences of 20 species are published for the first time with georeferencing. Many of these reptiles are listed in regional Red Data Lists. The European Pond Turtle Emys orbicularis (Linnaeus, 1758) is included in the IUCN Red List with the category "Near Threatened".