scholarly journals Global and national trends, gaps, and opportunities in documenting and monitoring species distributions

PLoS Biology ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. e3001336
Author(s):  
Ruth Y. Oliver ◽  
Carsten Meyer ◽  
Ajay Ranipeta ◽  
Kevin Winner ◽  
Walter Jetz
Keyword(s):  
Species Distributions ◽  
Sufficient Evidence ◽  
Sharp Decline ◽  
Biodiversity Data ◽  
Terrestrial Vertebrates ◽  
Biodiversity Knowledge ◽  
The Face ◽  
Data Coverage ◽  
National Trends ◽  
Sampling Effectiveness

Conserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. Here, we propose novel indicators of biodiversity data coverage and sampling effectiveness and analyze national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950 to 2019). Despite a rapid rise in data coverage, particularly in the last 2 decades, strong geographic and taxonomic biases persist. For some taxa and regions, a tremendous growth in records failed to directly translate into newfound knowledge due to a sharp decline in sampling effectiveness. However, we found that a nation’s coverage was stronger for species for which it holds greater stewardship. As countries under the post-2020 Global Biodiversity Framework renew their commitments to an improved, rigorous biodiversity knowledge base, our findings highlight opportunities for international collaboration to close critical information gaps.

scholarly journals Global and national trends in documenting and monitoring species distributions

2020 ◽  
Author(s):  
Ruth Y. Oliver ◽  
Carsten Meyer ◽  
Ajay Ranipeta ◽  
Kevin Winner ◽  
Walter Jetz
Keyword(s):  
Species Distributions ◽  
Sufficient Evidence ◽  
Rapid Rise ◽  
Sharp Decline ◽  
Terrestrial Vertebrates ◽  
Biodiversity Knowledge ◽  
The Face ◽  
Data Coverage ◽  
National Trends ◽  
Sampling Effectiveness

AbstractConserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. Here we analyze national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950-2019) based on novel indicators of data coverage and sampling effectiveness. Despite a rapid rise in data coverage, particularly in the last two decades, strong geographic and taxonomic biases persist. For some taxa and regions, a tremendous growth in records failed to directly translate into newfound knowledge due to a sharp decline in sampling effectiveness. But nation’s coverage is stronger for species they hold greater stewardship for. As countries under the post-2020 Global Biodiversity Framework renew their commitments to an improved, rigorous biodiversity knowledge base, our findings highlight opportunities for international collaboration to close critical information gaps.

scholarly journals The Pensoft Data Publishing Workflow: The FAIRway from articles to Linked Open Data

2019 ◽  
Vol 3 ◽  
Author(s):  
Lyubomir Penev ◽  
Teodor Georgiev ◽  
Viktor Senderov ◽  
Mariya Dimitrova ◽  
Pavel Stoev
Keyword(s):  
Open Data ◽  
Structured Data ◽  
Linked Open Data ◽  
Data Publishing ◽  
Knowledge Graph ◽  
Supplementary File ◽  
Biodiversity Data ◽  
Text Format ◽  
Biodiversity Knowledge ◽  
Data Elements

As one of the first advocates of open access and open data in the field of biodiversity publishiing, Pensoft has adopted a multiple data publishing model, resulting in the ARPHA-BioDiv toolbox (Penev et al. 2017). ARPHA-BioDiv consists of several data publishing workflows and tools described in the Strategies and Guidelines for Publishing of Biodiversity Data and elsewhere: Data underlying research results are deposited in an external repository and/or published as supplementary file(s) to the article and then linked/cited in the article text; supplementary files are published under their own DOIs and bear their own citation details. Data deposited in trusted repositories and/or supplementary files and described in data papers; data papers may be submitted in text format or converted into manuscripts from Ecological Metadata Language (EML) metadata. Integrated narrative and data publishing realised by the Biodiversity Data Journal, where structured data are imported into the article text from tables or via web services and downloaded/distributed from the published article. Data published in structured, semanticaly enriched, full-text XMLs, so that several data elements can thereafter easily be harvested by machines. Linked Open Data (LOD) extracted from literature, converted into interoperable RDF triples in accordance with the OpenBiodiv-O ontology (Senderov et al. 2018) and stored in the OpenBiodiv Biodiversity Knowledge Graph. Data underlying research results are deposited in an external repository and/or published as supplementary file(s) to the article and then linked/cited in the article text; supplementary files are published under their own DOIs and bear their own citation details. Data deposited in trusted repositories and/or supplementary files and described in data papers; data papers may be submitted in text format or converted into manuscripts from Ecological Metadata Language (EML) metadata. Integrated narrative and data publishing realised by the Biodiversity Data Journal, where structured data are imported into the article text from tables or via web services and downloaded/distributed from the published article. Data published in structured, semanticaly enriched, full-text XMLs, so that several data elements can thereafter easily be harvested by machines. Linked Open Data (LOD) extracted from literature, converted into interoperable RDF triples in accordance with the OpenBiodiv-O ontology (Senderov et al. 2018) and stored in the OpenBiodiv Biodiversity Knowledge Graph. The above mentioned approaches are supported by a whole ecosystem of additional workflows and tools, for example: (1) pre-publication data auditing, involving both human and machine data quality checks (workflow 2); (2) web-service integration with data repositories and data centres, such as Global Biodiversity Information Facility (GBIF), Barcode of Life Data Systems (BOLD), Integrated Digitized Biocollections (iDigBio), Data Observation Network for Earth (DataONE), Long Term Ecological Research (LTER), PlutoF, Dryad, and others (workflows 1,2); (3) semantic markup of the article texts in the TaxPub format facilitating further extraction, distribution and re-use of sub-article elements and data (workflows 3,4); (4) server-to-server import of specimen data from GBIF, BOLD, iDigBio and PlutoR into manuscript text (workflow 3); (5) automated conversion of EML metadata into data paper manuscripts (workflow 2); (6) export of Darwin Core Archive and automated deposition in GBIF (workflow 3); (7) submission of individual images and supplementary data under own DOIs to the Biodiversity Literature Repository, BLR (workflows 1-3); (8) conversion of key data elements from TaxPub articles and taxonomic treatments extracted by Plazi into RDF handled by OpenBiodiv (workflow 5). These approaches represent different aspects of the prospective scholarly publishing of biodiversity data, which in a combination with text and data mining (TDM) technologies for legacy literature (PDF) developed by Plazi, lay the ground of an entire data publishing ecosystem for biodiversity, supplying FAIR (Findable, Accessible, Interoperable and Reusable data to several interoperable overarching infrastructures, such as GBIF, BLR, Plazi TreatmentBank, OpenBiodiv and various end users.

scholarly journals Data ownership and data publishing

2019 ◽  
Vol 2 ◽  
Author(s):  
Lyubomir Penev
Keyword(s):  
Data Protection ◽  
Open Data ◽  
Data Publishing ◽  
Supplementary File ◽  
Biodiversity Data ◽  
Biodiversity Knowledge ◽  
Data Ownership ◽  
Data Hoarding ◽  
Data Elements ◽  
Access To Data

"Data ownership" is actually an oxymoron, because there could not be a copyright (ownership) on facts or ideas, hence no data onwership rights and law exist. The term refers to various kinds of data protection instruments: Intellectual Property Rights (IPR) (mostly copyright) asserted to indicate some kind of data ownership, confidentiality clauses/rules, database right protection (in the European Union only), or personal data protection (GDPR) (Scassa 2018). Data protection is often realised via different mechanisms of "data hoarding", that is witholding access to data for various reasons (Sieber 1989). Data hoarding, however, does not put the data into someone's ownership. Nonetheless, the access to and the re-use of data, and biodiversuty data in particular, is hampered by technical, economic, sociological, legal and other factors, although there should be no formal legal provisions related to copyright that may prevent anyone who needs to use them (Egloff et al. 2014, Egloff et al. 2017, see also the Bouchout Declaration). One of the best ways to provide access to data is to publish these so that the data creators and holders are credited for their efforts. As one of the pioneers in biodiversity data publishing, Pensoft has adopted a multiple-approach data publishing model, resulting in the ARPHA-BioDiv toolbox and in extensive Strategies and Guidelines for Publishing of Biodiversity Data (Penev et al. 2017a, Penev et al. 2017b). ARPHA-BioDiv consists of several data publishing workflows: Deposition of underlying data in an external repository and/or its publication as supplementary file(s) to the related article which are then linked and/or cited in-tex. Supplementary files are published under their own DOIs to increase citability). Description of data in data papers after they have been deposited in trusted repositories and/or as supplementary files; the systme allows for data papers to be submitted both as plain text or converted into manuscripts from Ecological Metadata Language (EML) metadata. Import of structured data into the article text from tables or via web services and their susequent download/distribution from the published article as part of the integrated narrative and data publishing workflow realised by the Biodiversity Data Journal. Publication of data in structured, semanticaly enriched, full-text XMLs where data elements are machine-readable and easy-to-harvest. Extraction of Linked Open Data (LOD) from literature, which is then converted into interoperable RDF triples (in accordance with the OpenBiodiv-O ontology) (Senderov et al. 2018) and stored in the OpenBiodiv Biodiversity Knowledge Graph Deposition of underlying data in an external repository and/or its publication as supplementary file(s) to the related article which are then linked and/or cited in-tex. Supplementary files are published under their own DOIs to increase citability). Description of data in data papers after they have been deposited in trusted repositories and/or as supplementary files; the systme allows for data papers to be submitted both as plain text or converted into manuscripts from Ecological Metadata Language (EML) metadata. Import of structured data into the article text from tables or via web services and their susequent download/distribution from the published article as part of the integrated narrative and data publishing workflow realised by the Biodiversity Data Journal. Publication of data in structured, semanticaly enriched, full-text XMLs where data elements are machine-readable and easy-to-harvest. Extraction of Linked Open Data (LOD) from literature, which is then converted into interoperable RDF triples (in accordance with the OpenBiodiv-O ontology) (Senderov et al. 2018) and stored in the OpenBiodiv Biodiversity Knowledge Graph In combination with text and data mining (TDM) technologies for legacy literature (PDF) developed by Plazi, these approaches show different angles to the future of biodiversity data publishing and, lay the foundations of an entire data publishing ecosystem in the field, while also supplying FAIR (Findable, Accessible, Interoperable and Reusable) data to several interoperable overarching infrastructures, such as Global Biodiversity Information Facility (GBIF), Biodiversity Literature Repository (BLR), Plazi TreatmentBank, OpenBiodiv, as well as to various end users.

VENUS BY BOTTICELLI AND HER PITUITARY ADENOMA

2019 ◽  
Vol 25 (10) ◽  
pp. 1067-1073
Author(s):  
Paolo Pozzilli ◽  
Luca Vollero ◽  
Anna Maria Colao
Keyword(s):  
Growth Hormone ◽  
Pituitary Adenoma ◽  
Pituitary Apoplexy ◽  
Three Dimensional ◽  
Sufficient Evidence ◽  
Methods Comparison ◽  
Pituitary Growth Hormone ◽  
Beautiful Woman ◽  
The Face ◽  
The Subject

Objective: Simonetta Vespucci, considered the most beautiful woman of the Renaissance, is the inspiration and face of one of the most famous paintings of all times, “The Birth of Venus,” by Botticelli. She died in 1476 at the age of 23 years. We postulate she suffered from a pituitary-secreting tumor progressing to pituitary apoplexy. The goals of this study were 3-fold: (i) verify that the subject depicted by Botticelli in different paintings represents the same woman; (ii) identify the facial traits affected by the progression of a growth hormone– and prolactin-secreting tumor; and (iii) confirm that the observed changes of the face traits observed in the portraits of Simonetta Vespucci are compatible with the facial traits changes identified earlier. Methods: Comparison among face traits was based on the analysis of the face regions measured by means of fiducial points and their distances, and after pose compensation based on three-dimensional head modelling. Results: In favor of the hypothesis that Simonetta suffered from a pituitary growth hormone– and prolactin-secreting tumor stands changes of her lineaments, a feature which becomes evident over the years and particularly manifest in the Allegorical Lady, where galactorrhea is depicted. Conclusion: We conclude that sufficient evidence is presented to suggest that Simonetta Vespucci, the Venus depicted by Botticelli, suffered from pituitary adenoma secreting prolactin and growth hormon with parasellar expansion. The current interpretation of the Venus strabism should be revisited according to this finding. Abbreviation: GH = growth hormone

scholarly journals Biodiversity databanks and scientific exploration

2021 ◽  
Vol 8 (2) ◽  
pp. 32-43
Author(s):  
Anouk Barberousse
Keyword(s):  
Human Genome ◽  
Human Genome Project ◽  
Genome Project ◽  
Biological Knowledge ◽  
Scientific Instruments ◽  
Biodiversity Data ◽  
Biodiversity Knowledge ◽  
Scientific Exploration ◽  
The Human Genome Project

For several decades now, biologists have been developing digital databanks, which are remarkable scientific instruments allowing scientists to accelerate the development of biological knowledge. From the beginnings of the Human Genome Project (HGP) onwards, genetic databanks have been a major component of current biological knowledge, and biodiversity databanks have also been developed in the wake of the HGP. The purpose of this paper is to identify the specific features of biodiversity data and databanks, and to point out their contribution to biodiversity knowledge.

scholarly journals Bringing a Semantic MediaWiki Flora to Life

2018 ◽  
Vol 2 ◽  
pp. e25885 ◽  
Author(s):  
Jocelyn Pender ◽  
Joel L. Sachs ◽  
James Macklin ◽  
Hong Cui ◽  
Andru Vallance ◽  
...  
Keyword(s):  
Language Processing ◽  
Data Linkage ◽  
Current Status ◽  
Biodiversity Data ◽  
The Past ◽  
Biodiversity Knowledge ◽  
Modern Natural ◽  
Taxonomic Groups ◽  
Semantic Mediawiki ◽  
Ongoing Project

The existing web representation of the Flora of North America (FNA) project needs improvement. Despite being electronically available, it has little more functionality than its printed counterpart. Over the past few years, our team has been working diligently to build a new more effective online presence for the FNA. The main objective is to capitalize on modern Natural Language Processing (NLP) tools built for biodiversity data (Explorer of Taxon Concepts or ETC; Cui et al. 2016), and present the FNA online in both machine and human readable formats. With machine-comprehensible data, the mobilization and usability of flora treatments is enhanced and capabilities for data linkage to a Biodiversity Knowledge Graph (Page 2016) are enabled. For example, usability of treatments increases when morphological statements are parsed into finely grained pieces of data using ETC, because these data can be easily traversed across taxonomic groups to reveal trends. Additionally, the development of new features in our online FNA is facilitated by FNA data parsing and processing in ETC, including a feature to enable users to explore all treatments and illustrations generated by an author of interest. The current status of the ongoing project to develop a Semantic MediaWiki (SMW) platform for the FNA is presented here. New features recently implemented are introduced, challenges in assembling the Semantic MediaWiki are discussed, and future opportunities, which include the integration of additional floras and data sources, are explored. Furthermore, implications of standardization of taxonomic treatments, which work such as this entails, will be discussed.

scholarly journals Global priorities for an effective information basis of biodiversity distributions

2015 ◽  
Author(s):  
Carsten Meyer ◽  
Holger Kreft ◽  
Robert P Guralnick ◽  
Walter Jetz
Keyword(s):  
Emerging Economies ◽  
Information Needs ◽  
Distribution Maps ◽  
Terrestrial Vertebrates ◽  
Biodiversity Knowledge ◽  
Accessible Information ◽  
United Nations Convention ◽  
The Tropics ◽  
Information Basis ◽  
Biodiversity Information

Severe gaps and biases in digital accessible information (DAI) of species distributions hamper prospects of safeguarding biodiversity and ecosystem services and reliably addressing central questions in ecology and evolution. Accordingly, governments have agreed on improving and sharing biodiversity knowledge by 2020 (United Nations Convention on Biological Diversity’s Aichi target 19). To achieve this target, gaps in DAI must be identified, and actions prioritized to address their root causes. We take terrestrial vertebrates, an iconic and comparatively well-studied group, as a model and present the first globally comprehensive assessment of patterns and drivers of gaps in DAI, based on an integration of 157 million validated point records with 21,170 expert-based distribution maps. We demonstrate that outside a few well-sampled regions, DAI provides a very limited and spatially highly biased inventory of actual biodiversity. Coarser spatial grains result in more complete inventories, but provide insufficient detail for conservation and resource management. Surprisingly, large emerging economies are particularly under-represented in global DAI, even more so than species-rich, developing countries in the tropics. Multi-model inference reveals that completeness is mainly limited by distance to researchers, locally available research funding, and political participation in data-sharing networks, rather than transportation infrastructure, or size and funding of Western data contributors as often assumed. Our study provides an empirical baseline to advance strategies of enhancing the global information basis of biodiversity. In particular, our results highlight the need for targeted data integration from non-Western data holders and intensified cooperation to more effectively address societal biodiversity information needs.

scholarly journals Imprecise Action Selection in Substance Use Disorder: Evidence for Active Learning Impairments When Solving the Explore-Exploit Dilemma

2020 ◽  
Author(s):  
Ryan Smith ◽  
Philipp Schwartenbeck ◽  
Jennifer Stewart ◽  
Rayus Kuplicki ◽  
Hamed Ekhtiari ◽  
...  
Keyword(s):  
Substance Use ◽  
Information Seeking ◽  
Action Selection ◽  
Learning Rate ◽  
Optimal Decision ◽  
Sufficient Evidence ◽  
Learning Impairments ◽  
The Face ◽  
Optimal Decision Making ◽  
Selection Mechanisms

Background: Substance use disorders (SUDs) are a major public health risk. However, mechanisms accounting for continued patterns of poor choices in the face of negative life consequences remain poorly understood. Methods: We use a computational (active inference) modeling approach, combined with multiple regression and hierarchical Bayesian group analyses, to examine how treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, hallucinogens, and/or opioids; N = 147) and healthy controls (HCs; N = 54) make choices to resolve uncertainty within a gambling task. A subset of SUDs (n = 49) and HCs (n = 51) propensity-matched on age, sex, and verbal IQ were also compared to replicate larger group findings. Results: Results indicate that: (a) SUDs show poorer task performance than HCs (p=.03, Cohen’s d = .33), with model estimates revealing less precise action selection mechanisms (p=.004, d = .43), a lower learning rate from losses (p=.02, d = .36), and a greater learning rate from gains (p=.04, d = .31); and (b) groups do not differ significantly in goal-directed information seeking. Conclusions: Findings suggest a pattern of inconsistent behavior in response to positive outcomes in SUDs combined with a tendency to attribute negative outcomes to chance. Specifically, individuals with SUDs fail to settle on a behavior strategy despite sufficient evidence of its success. These learning impairments could help account for difficulties in adjusting behavior and maintaining optimal decision making during and after treatment.

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