Dataset Information

An inventory of biodiversity data sources for conservation monitoring.

ABSTRACT: Many conservation managers, policy makers, businesses and local communities cannot access the biodiversity data they need for informed decision-making on natural resource management. A handful of databases are used to monitor indicators against global biodiversity goals but there is no openly available consolidated list of global data sets to help managers, especially those in high-biodiversity countries. We therefore conducted an inventory of global databases of potential use in monitoring biodiversity states, pressures and conservation responses at multiple levels. We uncovered 145 global data sources, as well as a selection of global data reports, links to which we will make available on an open-access website. We describe trends in data availability and actions needed to improve data sharing. If the conservation and science community made a greater effort to publicise data sources, and make the data openly and freely available for the people who most need it, we might be able to mainstream biodiversity data into decision-making and help stop biodiversity loss.

SUBMITTER: Stephenson PJ

PROVIDER: S-EPMC7710106 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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An inventory of biodiversity data sources for conservation monitoring.

Stephenson P J PJ Stengel Carrie C

PloS one 20201202 12

Many conservation managers, policy makers, businesses and local communities cannot access the biodiversity data they need for informed decision-making on natural resource management. A handful of databases are used to monitor indicators against global biodiversity goals but there is no openly available consolidated list of global data sets to help managers, especially those in high-biodiversity countries. We therefore conducted an inventory of global databases of potential use in monitoring biod ...[more]

PMID: 33264320

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Project description:The increasing growth of literature in biodiversity presents challenges to users who need to discover pertinent information in an efficient and timely manner. In response, text mining techniques offer solutions by facilitating the automated discovery of knowledge from large textual data. An important step in text mining is the recognition of concepts via their linguistic realisation, i.e., terms. However, a given concept may be referred to in text using various synonyms or term variants, making search systems likely to overlook documents mentioning less known variants, which are albeit relevant to a query term. Domain-specific terminological resources, which include term variants, synonyms and related terms, are thus important in supporting semantic search over large textual archives. This article describes the use of text mining methods for the automatic construction of a large-scale biodiversity term inventory. The inventory consists of names of species, amongst which naming variations are prevalent. We apply a number of distributional semantic techniques on all of the titles in the Biodiversity Heritage Library, to compute semantic similarity between species names and support the automated construction of the resource. With the construction of our biodiversity term inventory, we demonstrate that distributional semantic models are able to identify semantically similar names that are not yet recorded in existing taxonomies. Such methods can thus be used to update existing taxonomies semi-automatically by deriving semantically related taxonomic names from a text corpus and allowing expert curators to validate them. We also evaluate our inventory as a means to improve search by facilitating automatic query expansion. Specifically, we developed a visual search interface that suggests semantically related species names, which are available in our inventory but not always in other repositories, to incorporate into the search query. An assessment of the interface by domain experts reveals that our query expansion based on related names is useful for increasing the number of relevant documents retrieved. Its exploitation can benefit both users and developers of search engines and text mining applications.

Project description:The order Mucorales comprises predominantly fast-growing saprotrophic fungi, some of which are used for the fermentation of foodstuffs but it also includes species known to cause infections in patients with severe immune or metabolic impairments. To inventory biodiversity in Mucorales ITS barcodes of 668 strains in 203 taxa were generated covering more than two thirds of the recognised species. Using the ITS sequences, Molecular Operational Taxonomic Units were defined by a similarity threshold of 99 %. An LSU sequence was generated for each unit as well. Analysis of the LSU sequences revealed that conventional phenotypic classifications of the Mucoraceae are highly artificial. The LSU- and ITS-based trees suggest that characters, such as rhizoids and sporangiola, traditionally used in mucoralean taxonomy are plesiomorphic traits. The ITS region turned out to be an appropriate barcoding marker in Mucorales. It could be sequenced directly in 82 % of the strains and its variability was sufficient to resolve most of the morphospecies. Molecular identification turned out to be problematic only for the species complexes of Mucor circinelloides, M. flavus, M. piriformis and Zygorhynchus moelleri. As many as 12 possibly undescribed species were detected. Intraspecific variability differed widely among mucorealean species ranging from 0 % in Backusella circina to 13.3 % in Cunninghamella echinulata. A high proportion of clinical strains was included for molecular identification. Clinical isolates of Cunninghamella elegans were identified molecularly for the first time. As a result of the phylogenetic analyses several taxonomic and nomenclatural changes became necessary. The genus Backusella was emended to include all species with transitorily recurved sporangiophores. Since this matched molecular data all Mucor species possessing this character were transferred to Backusella. The genus Zygorhynchus was shown to be polyphyletic based on ITS and LSU data. Consequently, Zygorhynchus was abandoned and all species were reclassified in Mucor. Our phylogenetic analyses showed, furthermore, that all non-thermophilic Rhizomucor species belong to Mucor. Accordingly, Rhizomucor endophyticus was transferred to Mucor and Rhizomucor chlamydosporus was synonymised with Mucor indicus. Lecto-, epi- or neotypes were designated for several taxa.

Dataset Information

An inventory of biodiversity data sources for conservation monitoring.

Publications

An inventory of biodiversity data sources for conservation monitoring.

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