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The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world’s largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

The Natural History Museum, London has a number of online databases that describe interactions between species, including the HOSTS database of lepidopteran host plants (Robinson et al. 2010) and a database of Dipterocarp Seed Predators. These databases were generally bespoke software, which has increased the technical work necessary to sustain these resources. The decision was taken to migrate these to either the Scratchpads Virtual Research Environment (VRE) (Smith et al. 2011) or to the museum's Data Portal (Scott et al. 2019), depending on the complexity of the existing resource, as both are being sustained by the Informatics Group at the Natural History Museum, London. Resources that can be best represented as a single table were moved to the Data Portal, while those best represented in a relational model were transferred to Scratchpads. In addition, the Phthiraptera.info Scratchpad (Smith and Broom 2019), which already contained ecological interaction data, was migrated to the new system. This paper describes the implementation within the Scratchpads VRE of a new ecological interactions module that is capable of handling the needs of these projects, while at the same time is flexible to handle the needs of future projects with different data sources.

Clinopodium polycephalum (Vaniot) C. Y. Wu & S. J. Hsuan, a vital plant in traditional Chinese medicine, has been used for its hemostatic properties since 1220 AD. Despite its recognized medicinal benefits including anti-inflammatory and cardiovascular applications and increasing market demands, research on this plant remains limited, particularly from the perspective of plant ecology. Due to global warming and the resultant climate change, studies on the distribution and conservation of C. polycephalum are of great importance, especially when a clear trend that its habitat shifts to the north was observed. To predict the potential distribution of C. polycephalum under distinct climate situations, the MaxEnt model was used along with the ArcGIS software. As a result, an AUC value of 0.931 was achieved, indicating high predictive accuracy of the model. By analyzing 135 occurrence points and their corresponding bioclimatic factors (including precipitation), soil data, and other environmental variables (49 in total), 16 key factors including pH value and basic saturation were selected for downstream analysis. It was found that solar radiation in May, precipitation in May and April, and the lowest temperature in the coldest month are important factors influencing the growth and distribution of C. polycephalum . Compared to the current climate scenario, the future suitable habitat for C. polycephalum is expected to shift northwest, and under the SSP245-2061-2080 climate scenario, its highly suitable habitat area is projected to increase by 886,000 km 2 . These findings provide crucial insights into the environmental drivers of C. polycephalum distribution and aid in its preservation and sustainable use in traditional medicine. Based on the findings of this study, future research should focus on factors such as solar radiation in May and the lowest temperature in the coldest month within the suitable habitat to ensure its effective conservation.

Aim: Massive digitalization of natural history collections is now leading to a steep accumulation of publicly available species distribution data. However, taxonomic errors and geographical uncertainty of species occurrence records are now acknowledged by the scientific community - putting into question to what extent such data can be used to unveil correct patterns of biodiversity and distribution. We explore this question through quantitative and qualitative analyses of uncleaned versus manually verified datasets of species distribution records across different spatial scales. Location: The American tropics. Methods: As test case we used the plant tribe Cinchoneae (Rubiaceae). We compiled four datasets of species occurrences: one created manually and verified through classical taxonomic work, and the rest derived from GBIF under different cleaning and filling schemes. We used new bioinformatic tools to code species into grids, ecoregions, and biomes following WWF's classification. We analysed species richness and altitudinal ranges of the species. Results: Altitudinal ranges for species and genera were correctly inferred even without manual data cleaning and filling. However, erroneous records affected spatial patterns of species richness. They led to an overestimation of species richness in certain areas outside the centres of diversity in the clade. The location of many of these areas comprised the geographical midpoint of countries and political subdivisions, assigned long after the specimens had been collected. Main conclusion: Open databases and integrative bioinformatic tools allow a rapid approximation of large-scale patterns of biodiversity across space and altitudinal ranges. We found that geographic inaccuracy affects diversity patterns more than taxonomic uncertainties, often leading to false positives, i.e. overestimating species richness in relatively species poor regions. Public databases for species distribution are valuable and should be more explored, but under scrutiny and validation by taxonomic experts. We suggest that database managers implement easy ways of community feedback on data quality.

Background The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. Results The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. Conclusions We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ .

Fungal taxonomy and ecology have been revolutionized by the application of molecular methods and both have increasing connections to genomics and functional biology. However, data streams from traditional specimen- and culture-based systematics are not yet fully integrated with those from metagenomic and metatranscriptomic studies, which limits understanding of the taxonomic diversity and metabolic properties of fungal communities. This article reviews current resources, needs, and opportunities for sequence-based classification and identification (SBCI) in fungi as well as related efforts in prokaryotes. To realize the full potential of fungal SBCI it will be necessary to make advances in multiple areas. Improvements in sequencing methods, including long-read and single-cell technologies, will empower fungal molecular ecologists to look beyond ITS and current shotgun metagenomics approaches. Data quality and accessibility will be enhanced by attention to data and metadata standards and rigorous enforcement of policies for deposition of data and workflows. Taxonomic communities will need to develop best practices for molecular characterization in their focal clades, while also contributing to globally useful datasets including ITS. Changes to nomenclatural rules are needed to enable validPUBLICation of sequence-based taxon descriptions. Finally, cultural shifts are necessary to promote adoption of SBCI and to accord professional credit to individuals who contribute to community resources.

The software KaryoType, an improved and completely renewed version of the previously existing NucType, was developed for plant chromosomes. The primary function of the software is to allow efficient chromosome measurements and karyotype analysis from microphotographs. Karyotype characterization usually includes chromosome number, size, arm ratio, centromeric index, relative lengths and karyotype formula. Moreover, KaryoType is also capable of measuring karyotype asymmetry indices such as CVCL, CVCI and MCA, and can recognize chromosome homologues based on chromosome length and arm ratio automatically or manually. This program runs on Windows 7 and above and Mac OS X and is freely available at the website of the University of Sichuan (http://mnh.scu.edu.cn/soft/blog/karyotype/).

The European Vegetation Archive (EVA) has been developed since 2012 by the IAVS Working Group European Vegetation Survey as a centralized database of European vegetation plots. It stores copies of national and regional vegetation-plot databases on a single software platform. Data storage in EVA does not affect the ongoing independent development of the contributing databases, which remain the property of the data contributors. A prototype of the database management software TURBOVEG 3 has been developed for joint management of multiple databases that use different species lists. This is facilitated by the SynBioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their matches to a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA, contributing in total 1 024 236 vegetation plots from 57 countries, 82% of them with geographical coordinates. EVA provides a unique data source for large-scale analyses of European vegetation diversity both in fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database.

Fauna Europaea is Europe's main zoological taxonomic index, making the scientific names and distributions of all living, currently known, multicellular, European land and freshwater animals species integrally available in one authoritative database. Fauna Europaea covers about 260,000 taxon names, including 145,000 accepted (sub)species, assembled by a large network of (>400) leading specialists, using advanced electronic tools for data collations with data quality assured through sophisticated validation routines. Fauna Europaea started in 2000 as an EC funded FP5 project and provides a unique taxonomic reference for many user-groups such as scientists, governments, industries, nature conservation communities and educational programs. Fauna Europaea was formally accepted as an INSPIRE standard for Europe, as part of the European Taxonomic Backbone established in PESI. Fauna Europaea provides a public web portal at faunaeur.org with links to other key biodiversity services, is installed as a taxonomic backbone in wide range of biodiversity services and actively contributes to biodiversity informatics innovations in various initiatives and EC programs.