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Dive into the research topics where Donat Agosti is active.

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Featured researches published by Donat Agosti.


Ecology Letters | 2009

Climatic drivers of hemispheric asymmetry in global patterns of ant species richness.

Robert R. Dunn; Donat Agosti; Alan N. Andersen; Xavier Arnan; Carsten A. Brühl; Xim Cerdá; Aaron M. Ellison; Brian L. Fisher; Matthew C. Fitzpatrick; Heloise Gibb; Nicholas J. Gotelli; Aaron D. Gove; Benoît S. Guénard; Milan Janda; Michael Kaspari; Edward J. Laurent; Jean-Philippe Lessard; John T. Longino; Jonathan Majer; Sean B. Menke; Terrence P. McGlynn; Catherine L. Parr; Stacy M. Philpott; Martin Pfeiffer; Javier Retana; Andrew V. Suarez; Heraldo Heraldo Vasconcelos; Michael D. Weiser; Nathan J. Sanders

Although many taxa show a latitudinal gradient in richness, the relationship between latitude and species richness is often asymmetrical between the northern and southern hemispheres. Here we examine the latitudinal pattern of species richness across 1003 local ant assemblages. We find latitudinal asymmetry, with southern hemisphere sites being more diverse than northern hemisphere sites. Most of this asymmetry could be explained statistically by differences in contemporary climate. Local ant species richness was positively associated with temperature, but negatively (although weakly) associated with temperature range and precipitation. After contemporary climate was accounted for, a modest difference in diversity between hemispheres persisted, suggesting that factors other than contemporary climate contributed to the hemispherical asymmetry. The most parsimonious explanation for this remaining asymmetry is that greater climate change since the Eocene in the northern than in the southern hemisphere has led to more extinctions in the northern hemisphere with consequent effects on local ant species richness.


ZooKeys | 2010

Semantic tagging of and semantic enhancements to systematics papers: ZooKeys working examples

Lyubomir Penev; Donat Agosti; Teodor Georgiev; Terry Catapano; Jeremy Miller; Vladimir Blagoderov; David Roberts; Vincent S. Smith; Irina Brake; Simon Ryrcroft; Ben Scott; Norman F. Johnson; Robert A. Morris; Guido Sautter; Vishwas Chavan; Tim Robertson; Pavel Stoev; Cynthia Sims Parr; Sandra Knapp; W. John Kress; Chris F. Thompson; Terry L. Erwin

Abstract The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged manuscript (doi: 10.3897/zookeys.50.504); (ii) generated from Scratchpads and submitted as XML-tagged manuscripts (doi: 10.3897/zookeys.50.505 and doi: 10.3897/zookeys.50.506); (iii) generated from an author’s database (doi: 10.3897/zookeys.50.485) and submitted as XML-tagged manuscript. XML tagging and semantic enhancements were implemented during the editorial process of ZooKeys using the Pensoft Mark Up Tool (PMT), specially designed for this purpose. The XML schema used was TaxPub, an extension to the Document Type Definitions (DTD) of the US National Library of Medicine Journal Archiving and Interchange Tag Suite (NLM). The following innovative methods of tagging, layout, publishing and disseminating the content were tested and implemented within the ZooKeys editorial workflow: (1) highly automated, fine-grained XML tagging based on TaxPub; (2) final XML output of the paper validated against the NLM DTD for archiving in PubMedCentral; (3) bibliographic metadata embedded in the PDF through XMP (Extensible Metadata Platform); (4) PDF uploaded after publication to the Biodiversity Heritage Library (BHL); (5) taxon treatments supplied through XML to Plazi; (6) semantically enhanced HTML version of the paper encompassing numerous internal and external links and linkouts, such as: (i) vizualisation of main tag elements within the text (e.g., taxon names, taxon treatments, localities, etc.); (ii) internal cross-linking between paper sections, citations, references, tables, and figures; (iii) mapping of localities listed in the whole paper or within separate taxon treatments; (v) taxon names autotagged, dynamically mapped and linked through the Pensoft Taxon Profile (PTP) to large international database services and indexers such as Global Biodiversity Information Facility (GBIF), National Center for Biotechnology Information (NCBI), Barcode of Life (BOLD), Encyclopedia of Life (EOL), ZooBank, Wikipedia, Wikispecies, Wikimedia, and others; (vi) GenBank accession numbers autotagged and linked to NCBI; (vii) external links of taxon names to references in PubMed, Google Scholar, Biodiversity Heritage Library and other sources. With the launching of the working example, ZooKeys becomes the first taxonomic journal to provide a complete XML-based editorial, publication and dissemination workflow implemented as a routine and cost-efficient practice. It is anticipated that XML-based workflow will also soon be implemented in botany through PhytoKeys, a forthcoming partner journal of ZooKeys. The semantic markup and enhancements are expected to greatly extend and accelerate the way taxonomic information is published, disseminated and used.


Cladistics | 1996

On combining protein sequences and nucleic acid sequences in phylogenetic analysis: the homeobox protein case.

Donat Agosti; David K. Jacobs; Rob DeSalle

Abstract— Amino acid encoding genes contain character state information that may be useful for phylogenetic analysis on at least two levels. The nucleotide sequence and the translated amino acid sequences have both been employed separately as character states for cladistic studies of various taxa, including studies of the genealogy of genes in multigene families. In essence, amino acid sequences and nucleic acid sequences are two different ways of character coding the information in a gene. Silent positions in the nucleotide sequence (first or third positions in codons that can accrue change without changing the identity of the amino acid that the triplet codes for) may accrue change relatively rapidly and become saturated, losing the pattern of historical divergence. On the other hand, non‐silent nucleotide alterations and their accompanying amino acid changes may evolve too slowly to reveal relationships among closely related taxa. In general, the dynamics of sequence change in silent and non‐silent positions in protein coding genes result in homoplasy and lack of resolution, respectively. We suggest that the combination of nucleic acid and the translated amino acid coded character states into the same data matrix for phylogenetic analysis addresses some of the problems caused by the rapid change of silent nucleotide positions and overall slow rate of change of non‐silent nucleotide positions and slowly changing amino acid positions. One major theoretical problem with this approach is the apparent non‐independence of the two sources of characters. However, there are at least three possible outcomes when comparing protein coding nucleic acid sequences with their translated amino acids in a phylogenetic context on a codon by codon basis. First, the two character sets for a codon may be entirely congruent with respect to the information they convey about the relationships of a certain set of taxa. Second, one character set may display no information concerning a phylogenetic hypothesis while the other character set may impart information to a hypothesis. These two possibilities are cases of non‐independence, however, we argue that congruence in such cases can be thought of as increasing the weight of the particular phylogenetic hypothesis that is supported by those characters. In the third case, the two sources of character information for a particular codon may be entirely incongruent with respect to phylogenetic hypotheses concerning the taxa examined. In this last case the two character sets are independent in that information from neither can predict the character states of the other. Examples of these possibilities are discussed and the general applicability of combining these two sources of information for protein coding genes is presented using sequences from the homeobox region of 46 homeobox genes fromDrosophila melanogasterto develop a hypothesis of genealogical relationship of these genes in this large multigene family.


American Museum Novitates | 2001

Acropyga and Azteca Ants (Hymenoptera: Formicidae) with Scale Insects (Sternorrhyncha: Coccoidea): 20 Million Years of Intimate Symbiosis

Christine. Johnson; Donat Agosti; Jacques Hubert Charles Delabie; Klaus Dumpert; D. J. Williams; Michael. von Tschirnhaus; Ulrich Maschwitz

Abstract Species of the genus Acropyga are rarely encountered subterranean ants that rely on mealybugs or aphids to provide their nutritional needs. Female Acropyga (Formicinae) alates of pantropical and Mediterranean species carry mealybugs with their mandibles while swarming and probably inoculate their new nests with these mealybugs. The natural history of Acropyga and other mealybug-tending ant species, a summary of the various reports of Acropyga females toting mealybugs, and a new record from French Guiana are presented here. Also provided are a first report and description of Acropyga alates with mealybugs in Dominican amber dated to the Miocene, a discovery indicating that this intimate association and relatively uncommon behavior has existed for at least 15–20 million years. The mealybugs found with the Acropyga females in amber are related to the hypogaeic genera Eumyrmococcus Silvestri and Neochavesia Williams & Granara de Willink (Pseudococcidae, Rhizoecinae) and represent three new species of a new genus. The genus Electromyrmococcus and the species Electromyrmococcus abductus Williams, Electromyrmococcus inclusus Williams and Agosti, and Electromyrmococcus reginae Williams are described. A piece of Dominican amber containing workers of Azteca alpha Wilson (Dolichoderinae) and 23 scale insects is also presented and the significance of these specimens in Dominican amber is discussed.


ZooKeys | 2011

Creative Commons licenses and the non-commercial condition: Implications for the re-use of biodiversity information

Gregor Hagedorn; Daniel Mietchen; Robert A. Morris; Donat Agosti; Lyubomir Penev; Walter G. Berendsohn; Donald Hobern

Abstract The Creative Commons (CC) licenses are a suite of copyright-based licenses defining terms for the distribution and re-use of creative works. CC provides licenses for different use cases and includes open content licenses such as the Attribution license (CC BY, used by many Open Access scientific publishers) and the Attribution Share Alike license (CC BY-SA, used by Wikipedia, for example). However, the license suite also contains non-free and non-open licenses like those containing a “non-commercial” (NC) condition. Although many people identify “non-commercial” with “non-profit”, detailed analysis reveals that significant differences exist and that the license may impose some unexpected re-use limitations on works thus licensed. After providing background information on the concepts of Creative Commons licenses in general, this contribution focuses on the NC condition, its advantages, disadvantages and appropriate scope. Specifically, it contributes material towards a risk analysis for potential re-users of NC-licensed works.


Biodiversity Data Journal | 2013

Beyond dead trees: integrating the scientific process in the Biodiversity Data Journal

Vincent S. Smith; Teodor Georgiev; Pavel Stoev; Jordan Biserkov; Jeremy Miller; Laurence Livermore; Edward Baker; Daniel Mietchen; Thomas L.P. Couvreur; Gregory M. Mueller; Torsten Dikow; Kristofer M. Helgen; Jiři Frank; Donat Agosti; David Roberts; Lyubomir Penev

Driven by changes to policies of governments and funding agencies, Open Access to content and data is quickly becoming the prevailing model in academic publishing. Open Access benefits scientists with greater dissemination and citation of their work, and provides society as a whole with access to the latest research. Open Access is, however, only one facet of scholarly communication. Core scientific statements or assertions are intertwined and hidden in the scholarly narratives, and the data underlying these statements are often obscured to the point that replication of results is impossible (Nature Editorial 2012). This is in part a result of the way scientific papers are written as narratives, rather than sources of data. An often cited reason for the lack of published data is the absence of a reward mechanism for the individuals involved in creating and managing information (Smith 2009, Costello 2009, Vision 2010, McDade et al. 2011, Duke and Porter 2013). Preparing data for publication is a time consuming activity that few scholars will undertake without recognition from their peers. Data papers are a potential solution to this problem (Chavan and Penev 2011, Chavan and Penev 2013). They allow authors to publish data and receive reward through the traditional citation process. Coupling tools to rapidly and simply generate publications will incentivise this behaviour and create a culture of data curation and sharing within the biodiversity science community. If we are going to incentivise the mass publication of data, we also need mechanisms to ensure quality. Traditional peer review is one of the bottlenecks in standard publication practice (Hauser and Fehr 2007, Fox and Petchey 2010). A common criticism of peer review is the lack of transparency and accountability on the part of the reviewers. To cope with the additional volume of papers created by data publication and to move to a more transparent system, we need to rethink peer review. We need both new methods of reviewing and new tools to automate as much of the review process as possible. This requires a new publishing platform, not just a new journal. An abundance of small isolated datasets does not, however, allow us to address the fundamental problems within the biodiversity science community. These islands of data are only of value if connected and interlinked. The task of interlinking is performed by biodiversity data aggregators like the Global Biodiversity Information Facility (GBIF) and Encylopedia of Life (EOL) which form the backbone of data-driven biodiversity research. By automating the submission of data to these aggregators, we can increase their value to more than the sum of their parts, making small data big. A renewed appreciation of the value of small data will help to reduce the vast amount of research data that exists only on laptops and memory sticks - data that is often lost when people change roles or retire. Works of potentially very limited length can hold intrinsic value to the community, but are almost impossible to publish in traditional journals chasing impact factors. Examples include single species descriptions, local checklists and software descriptions, or ecological surveys and plot data. An infrastructure that allows datasets of any size to be important means we can publish them at any time. There is no need to wait for datasets to reach a critical mass suitable for publication in a traditional journal. Today, we are pleased to announce the official release of the first series of papers published in Biodiversity Data Journal (BDJ). After years of hard work in analyzing, planning and programming the Pensoft Writing Tool (PWT), we now have a publishing platform that addresses the key concerns raised above. This provides the first workflow to support the full life cycle of a manuscript - from writing through submission, community peer-review, publication and dissemination, all within a single online collaborative environment. Shortening distance between “data” and “narrative” publishing Most journals nowadays clearly separate data from narrative (text). Moreover, data publishing through data centres and repositories has almost become a separate sector within the scholarly publishing landscape. BDJ is not a conventional journal, nor is it a conventional “data journal”. It aims to integrate data and text in a single publication by converting several kinds of biodiversity data (e.g., species occurrences, checklists, or data tables) into the text for human-readable use, while simultaneously making data units from the same article harvestable and downloadable. The text itself is marked up and presented in a highly structured and machine readable form. BDJ aims to integrate small data into the text whenever possible. Supplementary data files that underpin graphs, hypotheses and results can also be uploaded on the journal’s website and published with the article. Nonetheless, this is usually not possible for large or complex data, for which we recommend deposition in an established open international repository (for details, see Penev et al. 2011): Large primary biodiversity data sets (e.g., institutional collections of species-occurrence records) should be published with the GBIF Integrated Publishing Toolkit (IPT); small data sets of this kind are imported into the article text through an Excel template, available in PWT. Genomic data should be deposited with INSDC (GenBank/EMBL/DDBJ), either directly or via a partnering repository, e.g. Barcode of Life Data Systems (BOLD). Transcriptomics data should be deposited in Gene Expression Omnibus (GEO) or ArrayExpress. Phylogenetic data should be deposited at TreeBASE, either directly or through the Dryad Data Repository. Biodiversity-related geoscience and environmental data should be deposited in PANGAEA. Morphological images other than those presented in the article should be deposited at Morphbank. Images of a specific kind should be deposited in appropriate repositories if these exist (e.g., Morphosource for MicroCT data). Videos should be uploaded to video sharing sites like YouTube, Vimeo or SciVee and linked back to the article text. Similarly, audio files should go to platforms like FreeSound or SoundCloud, and presentations to Slideshare. In addition, multimedia files can also be uploaded as supplementary files on the journal’s website. 3D and other interactive models can be embedded in the article’s HTML and PDF. Any other large data sets (e.g., ecological observations, environmental data, morphological and other data types) should be deposited in the Dryad Data Repository, either prior to or upon acceptance of the manuscript. Other specialised data repositories can be used if these offer unique identifiers and long-term preservation. All external data used in a BDJ paper must be cited in the reference list, and links to these data (as deposited in external repositories) must be included in a separate data resources section of the article. All datasets, images or multimedia are freely downloadable from the text under the Open Data Commons Attribution License or a Creative Commons CC-Zero waiver / Public Domain Dedication. The article text is available under a Creative Commons (CC-BY) 3.0 license. Primary biodiversity data within an article can be exported in Darwin Core Archive format, which makes them interoperable with biodiversity tools based on the Darwin Core standard. By facilitating open access to the data that underlie every publication, BDJ is setting a new standard in transparency and repeatability in biodiversity science. Perpetual and universal access to primary data stimulates scientific progress by helping authors build upon existing datasets. BDJ’s commitment to supporting automated data aggregation and interlinking is happening alongside multiple advances in biodiversity informatics infrastructure that herald the dawning of an era of collaborative, big-data biodiversity science (Page 2008, Patterson et al. 2010, Thessen and Patterson 2011, Parr et al. 2012).


ZooKeys | 2011

Interlinking journal and wiki publications through joint citation: Working examples from ZooKeys and Plazi on Species-ID

Lyubomir Penev; Gregor Hagedorn; Daniel Mietchen; Teodorss Georgiev; Pavel Stoev; Guido Sautter; Donat Agosti; Andreas Plank; Michael Balke; Lars Hendrich; Terry L. Erwin

Abstract Scholarly publishing and citation practices have developed largely in the absence of versioned documents. The digital age requires new practices to combine the old and the new. We describe how the original published source and a versioned wiki page based on it can be reconciled and combined into a single citation reference. We illustrate the citation mechanism by way of practical examples focusing on journal and wiki publishing of taxon treatments. Specifically, we discuss mechanisms for permanent cross-linking between the static original publication and the dynamic, versioned wiki, as well as for automated export of journal content to the wiki, to reduce the workload on authors, for combining the journal and the wiki citation and for integrating it with the attribution of wiki contributors.


Biological Reviews | 2018

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

W. Daniel Kissling; Jorge A. Ahumada; Anne Bowser; Miguel Fernandez; Néstor Fernández; Enrique Alonso García; Robert P. Guralnick; Nick J. B. Isaac; Steve Kelling; Wouter Los; Louise McRae; Jean-Baptiste Mihoub; Matthias Obst; Monica Santamaria; Andrew K. Skidmore; Kristen J. Williams; Donat Agosti; Daniel Amariles; Christos Arvanitidis; Lucy Bastin; Francesca De Leo; Willi Egloff; Jane Elith; Donald Hobern; David Martin; Henrique M. Pereira; Johannes Peterseil; Hannu Saarenmaa; Dmitry Schigel; Dirk S. Schmeller

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence‐only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi‐source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter‐ or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi‐source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA‐based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.


BMC Research Notes | 2014

Scientific names of organisms: attribution, rights, and licensing

David Patterson; Willi Egloff; Donat Agosti; David Eades; Nico M. Franz; Gregor Hagedorn; Jonathan Rees

BackgroundAs biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world.FindingsThe laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts.ConclusionsA ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.


Nature | 1998

Oldest known ant fossils discovered

Donat Agosti; David A. Grimaldi; James M. Carpenter

Here we report fossil ants, including a new genus of Ponerinae, about 50 million years (Myr) older than the previous oldest specimens. These discoveries in amber from the Turonian stage (92 Myr ago) of New Jersey in the United States have important implications for estimates dating the origin of ants, and extend the age of an extant ant subfamily back about 50 Myr.

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Dive into the Donat Agosti's collaboration.

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Lyubomir Penev

Bulgarian Academy of Sciences

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Guido Sautter

Karlsruhe Institute of Technology

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Teodor Georgiev

Bulgarian Academy of Sciences

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Pavel Stoev

National Museum of Natural History

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David A. Grimaldi

American Museum of Natural History

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Klemens Böhm

Karlsruhe Institute of Technology

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