Special Issue "Biodiversity Informatics"

A special issue of Diversity (ISSN 1424-2818).

Deadline for manuscript submissions: closed (31 October 2015).

Special Issue Editor

Prof. Dr. Stefano Martellos
E-Mail Website
Guest Editor
Department of Life Sciences, University of Trieste, Via L. Giorgieri 10, 34127 Trieste, Italy
Interests: lichenology; biodiversity informatics; ecological niche modelling

Special Issue Information

Dear Colleagues,

Biodiversity Informatics can be defined as the application of informatics techniques for improving the management, presentation, discovery, exploration, and analysis of biodiversity data. While apparently a field for informatics scientists, this new discipline requires a thorough knowledge of the complexity of biodiversity data, knowledge of which is the province of biologists. The use of informatics techniques on biodiversity data is as old as informatics itself. For example, the idea of using a standardized language for writing taxonomic descriptions, so as to make them readable by a computer, popped out in 1973. Initially, research in Biodiversity Informatics mainly targeted primary data (e.g., occurrences and natural history specimen data). However, in the last ten years, the focus of researchers has widened. Several efforts started dealing with taxonomies, and aimed to create reliable repositories of scientific names by collecting and organizing environmental data. Also, morphological, ecological, distributional, and molecular data have applications in ecological niche modeling and in the development digital identification tools. Furthermore, the development of common standards for digitalizing and sharing data has assumed much importance.

This Special Issue aims to present some of the most interesting research in the exciting field of Biodiversity Informatics.

Dr. Stefano Martellos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diversity is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Biodiversity data collection, management and aggregation
  • Citizen Science: a new source of biodiversity data
  • Digital identification keys
  • Digitalization of natural history collections
  • Ecological niche modeling
  • Nomenclators and taxonomic databases

Published Papers (1 paper)

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Research

Article
FactorsR: An RWizard Application for Identifying the Most Likely Causal Factors in Controlling Species Richness
Diversity 2015, 7(4), 385-396; https://doi.org/10.3390/d7040385 - 16 Nov 2015
Cited by 6 | Viewed by 4755
Abstract
We herein present FactorsR, an RWizard application which provides tools for the identification of the most likely causal factors significantly correlated with species richness, and for depicting on a map the species richness predicted by a Support Vector Machine (SVM) model. As a [...] Read more.
We herein present FactorsR, an RWizard application which provides tools for the identification of the most likely causal factors significantly correlated with species richness, and for depicting on a map the species richness predicted by a Support Vector Machine (SVM) model. As a demonstration of FactorsR, we used an assessment using a database incorporating all species of terrestrial carnivores, a total of 249 species, distributed across 12 families. The model performed with SVM explained 91.9% of the variance observed in the species richness of terrestrial carnivores. Species richness was higher in areas with both higher vegetation index and patch index, i.e., containing higher numbers of species whose range distribution is less fragmented. Lower species richness than expected was observed in Chile, Madagascar, Sumatra, Taiwan, and Sulawesi. Full article
(This article belongs to the Special Issue Biodiversity Informatics)
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