2024-03-29T08:59:22Z
http://journals.ku.edu/index/oai
oai:ojs.pkp.sfu.ca:article/3
2022-10-03T18:09:03Z
jbi:ART
nmb a2200000Iu 4500
"041111 2004 eng "
1546-9735
10.17161/bi.v1i0.3
doi
dc
Global Biodiversity Informatics: setting the scene for a "new world" of ecological forecasting
Canhos, Vanderlei Perez
Centro de Referência em Informação Ambiental, CRIA
Souza, Sidnei de
Centro de Referência em Informação Ambiental, CRIA
Giovanni, Renato De
Centro de Referência em Informação Ambiental, CRIA
Canhos, Dora Ann Lange
Centro de Referência em Informação Ambiental, CRIA
Recent developments in information and communication technology are allowing new experiences in the integration, analysis and visualization of biodiversity information, and are leading to development of a new field of research, biodiversity informatics. Although this field has great potential in diverse realms, including basic biology, human economics, and public health, much of this potential remains to be explored. The success of several concerted international efforts depends largely on broad deployment of biodiversity informatics information and products. Several global and regional efforts are organizing and providing data for conservation and sustainable development research, including the Global Biodiversity Information Facility, the European Biodiversity Information Network, and the Inter-American Biodiversity Information Network. Critical to development of this field is building a biodiversity information infrastructure, making primary biodiversity data freely and openly available over the Internet. In addition to specimen and taxonomic data, access to non-biological environmental data is critical to spatial analysis and modeling of biodiversity. Adoption of standards and protocols and development of tools for collection management, data-cleaning, georeferencing, and modeling tools, are allowing a quantum leap in the area. Open access to research data and open-source tools are leading to a new era of web services and computational frameworks for spatial biodiversity analysis, bringing new opportunities and dimensions to novel approaches in ecological analysis, predictive modeling, and synthesis and visualization of biodiversity information.
The University of Kansas
2004-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3
Biodiversity Informatics; Vol. 1 (2004)
eng
Copyright (c) 2004 Vanderlei Perez Canhos, Sidnei de Souza, Renato De Giovanni, Dora Ann Lange Canhos
oai:ojs.pkp.sfu.ca:article/4
2022-10-03T18:12:35Z
jbi:ART
nmb a2200000Iu 4500
"050113 2005 eng "
1546-9735
10.17161/bi.v2i0.4
doi
dc
Interpretation of Models of Fundamental Ecological Niches and Species' Distributional Areas
Soberon, Jorge
CONABIO
Peterson, A. Townsend
Natural History Museum, KU
Ecological niche modeling, that is, estimation of the dimensions of fundamental ecological niches of species to predict their geographic distributions is increasingly being employed in systematics, ecology, conservation, public health, etc. This technique is often (of necessity) based on data comprising records of presences only. In recent years, many modeling approaches have been devised to estimate these interrelated expressions of a species' ecology, distributional biology, and evolutionary history nevertheless, in many cases, a formal basis in ecological and evolutionary theory has been lacking. In this paper, we outline such a formal basis for the suite of techniques that can be termed 'ecological niche modeling,' analyze example situations that can be modeled using these techniques, and clarify the interpretation of results.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c) 2005 Jorge Soberon, A. Townsend Peterson
oai:ojs.pkp.sfu.ca:article/5
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"050509 2005 eng "
1546-9735
10.17161/bi.v2i0.5
doi
dc
Environmental Information: Placing Biodiversity Phenomena in an Ecological and Environmental Context
Chapman, Arthur D
Australian Biodiversity information Services
Muñoz, Mauro E.S.
Centro de Referência em Informação Ambiental (CRIA)
Koch, Ingrid
Centro de Referência em Informação Ambiental (CRIA),
Environmental models are increasingly being used as surrogates to determine plant and animal species’ distributions for a range of uses. This use of models has become an important part of the recent science that has become known as biodiversity informatics. Because of the nature of species data, considerable effort has often been spent in managing the quality of those species data, but less time has generally been spent on determining the quality and efficacy of the environmental data against which the species data are being modeled. This paper examines a range of environmental data being used in species distribution modeling, and looks at how they are prepared, their quality and use, and some of the commonly encountered pitfalls and problems in using these data in species’ distribution modeling.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/5
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"041124 2004 eng "
1546-9735
10.17161/bi.v1i0.6
doi
dc
Bioinformatics, the Clearing-House Mechanism and the Convention on Biological Diversity
Silva, Marcos R.
Secretariat of the Convention on Biological Diversity
This paper will discuss the development and role of the Convention’s Clearing-House Mechanism (CHM), its synergies with the Biosafety Clearing-House (BCH), and its support for bioinformatic initiatives in light of the Convention’s programme areas and cross-cutting issues. Within this context, the paper will also examine the significance of bioinformatics in assisting Parties to implement obligations under the Convention and the role of the CHM in facilitating activities by Parties and Governments to exploit the benefits arising from the evolving bioinformatics global infrastructure.
The University of Kansas
2004-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/6
Biodiversity Informatics; Vol. 1 (2004)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/7
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"041111 2004 eng "
1546-9735
10.17161/bi.v1i0.7
doi
dc
Mammals of the World: MaNIS as an example of data integration in a distributed network environment
Stein, Barbara R
Museum of Vertebrate Zoology
Wieczorek, John R.
Museum of Vertebrate Zoology
Natural history collections are the authoritative source of knowledge about the identity, evolutionary relationships, and attributes of species with which we share this planet. As such, collections of research specimens play a central and critical role in the conservation and sustainable use of biodiversity. The potential contribution of specimen data to systematic, genomic, and ecological analyses is enormous, and will be orders of magnitude greater when information is made easily accessible via distributed networks compared with stand-alone database systems in use up to the present. The Mammal Networked Information System (MaNIS) is a distributed database network that permits participating institutions to provide web-based global access to their collections data for research, education and informed decision-making. The simplicity of the network’s design ensures that any institution wishing to join MaNIS may do so at relatively little cost and with relatively little technical expertise. Although development of MaNIS and its underlying architecture relied on a number of key programming tasks and innovations, much of what the project can offer at this pivotal juncture is insight into its approach and a template by which other disciplines can engage in a similar process with equal success.
The University of Kansas
2004-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/7
Biodiversity Informatics; Vol. 1 (2004)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/8
2022-10-03T18:13:52Z
jbi:ART
nmb a2200000Iu 4500
"050526 2005 eng "
1546-9735
10.17161/bi.v2i0.8
doi
dc
Climate Change and Biodiversity: Some Considerations in Forecasting Shifts in Species' Potential Distributions
Martinez-Meyer, Enrique
Instituto de Biologia, UNAM
Global climate change and its broad spectrum of effects on human and natural systems has become a central research topic in recent years; biodiversity informatics tools particularly ecological niche modeling (ENM) have been used extensively to anticipate potential effects on geographic distributions of species. Misuse of these tools, however, is counterproductive, as biased conclusions might be reached. In this paper, I discuss some issues related to niche theory, geographic distributions, data quality, and algorithms, all of which are relevant when using ENM in climate change projections for biodiversity. This assortment of opinions and ideas is presented in the hope that ENM applications to climate change questions can be made more realistic and more predictive.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/8
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c) 2005 Enrique Martinez-Meyer
oai:ojs.pkp.sfu.ca:article/9
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"050116 2005 eng "
1546-9735
10.17161/bi.v2i0.9
doi
dc
Place prioritization for biodiversity content using species ecological niche modeling
Sánchez-Cordero, Víctor
Departamento de Zoologia, Instituto de Biologia, Universidad Nacional Autonoma de Mexico.
Cirelli, Verónica
Departamento de Zoologia, Instituto de Biologia, Universidad Nacional Autonoma de Mexico.
Munguial, Mariana
Departamento de Zoologia, Instituto de Biologia, Universidad Nacional Autonoma de Mexico.
Sarkar, Sahotra
Section of Integrative Biology and Department of Philosophy, University of Texas
Place prioritization for biodiversity representation is essential for conservation planning, particularly in megadiverse countries where high deforestation threatens biodiversity. Given the collecting biases and uneven sampling of biological inventories, there is a need to develop robust models of species’ distributions. By modeling species’ ecological niches using point occurrence data and digitized environmental feature maps, we can predict potential and extant distributions of species in untransformed landscapes, as well as in those transformed by vegetation change (including deforestation). Such distributional predictions provide a framework for use of species as biodiversity surrogates in place prioritization procedures such as those based on rarity and complementarity. Beyond biodiversity conservation, these predictions can also be used for place prioritization for ecological restoration under current conditions and under future scenarios of habitat change (e.g., deforestation) scenarios. To illustrate these points, we (1) predict distributions under current and future deforestation scenarios for the Mexican endemic mammal Dipodomys phillipsii, and show how areas for restoration may be selected; and (2) propose conservation areas by combining nonvolant mammal distributional predictions as biodiversity surrogates with place prioritization procedures, to connect decreed natural protected areas in a region holding exceptional biodiversity: the Transvolcanic Belt in central Mexico.
La selección de áreas prioritarias de conservación es fundamental en la planeación sistemática de la conservación, particularmente en países de mega-diversidad, en donde la alta deforestación es una de las amenazas a la biodiversidad. Debido a los sesgos taxonómicos y geográficos de colecta de los inventarios biológicos, es indispensable generar modelos robustos de distribución de especies. Al modelar el nicho ecológico de especies usando localidades de colecta, mapas digitales de variables ambientales y sistemas de información geográficos, se proyecta las distribuciones potencial y actual en hábitat transformados y no transformados por la deforestación. Estas hipótesis de distribución proveen un marco teórico para predecir presencia y ausencia de especies, como indicadores de la biodiversidad existente en áreas prioritarias seleccionadas con base en los principios de rareza y complementariedad. Para ilustrar esto, se muestran dos ejemplos; (1) se modeló el nicho ecológico de un roedor endémico Dipodomys phillipsii, proyectando su distribución en escenarios de deforestación actuales y a futuro. La predicción de la distribución de especies puede ser útil en la selección de áreas prioritarias para la conservación y la restauración, bajo escenarios actuales y futuros de deforestación, permitiendo una planeación sistemática adecuada de la conservación de la biodiversidad, y (2) proponer áreas de conservación, usando predicciones de distribuciones de mamíferos no voladores y procedimientos de selección de áreas prioritarias, como corredores que conecten las áreas naturales prioritarias decretadas en el Eje Neovolcánico, una región de alta biodiversidad.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/9
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/16
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"051113 2005 eng "
1546-9735
10.17161/bi.v2i0.16
doi
dc
Resolving taxonmic discrepancies: Role of Electronic Catalogues of Known Organisms
Chavan, Vishwas Shravan
National Chemical Laboratory
Rane, Nilesh Sunil
National Chemical Laboratory
Watve, Aparna
National Chemical Laboratory
Ruggiero, Michael
Integrated Taxonomic Information System, US Geological Survey, Smithsonian Institution, Washington DC, USA
There is a disparity in availability of nomenclature change literature to the taxonomists of the developing world and availability of taxonomic papers published by developing world scientists to their counterparts in developed part of the globe. This has resulted in several discrepancies in the naming of organisms. Development of electronic catalogues of names of known organisms would help in pointing out these issues. We have attempted to highlight a few of such discrepancies found while developing IndFauna, an electronic catalogue of known Indian fauna and comparing it with existing global and regional databases.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/16
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/17
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"051116 2005 eng "
1546-9735
10.17161/bi.v2i0.17
doi
dc
TaxonGrab: Extracting Taxonomic Names From Text
Koning, Drew
American Museum of Natural History
Sarkar, Indra Neil
American Museum of Natural History
Moritz, Thomas
American Museum of Natural History
Identification of organism names in biological texts is essential for the management of archival resources to facilitate comparative biological investigation. Because organism nomenclature conforms closely to prescribed rules, automated techniques may be useful for identifying organism names from existing documents, and may also support the completion of comprehensive indices of taxonomic names; such comprehensive lists are not yet available. Using a combination of contextual rules and a language lexicon, we have developed a set of simple computational techniques for extracting taxonomic names from biological text. Our proposed method consistently performs at greater than 96% Precision and 94% Recall, and at a much higher speed than manual extraction techniques. An implementation of the described method is available as a Web based tool written in PHP. Additionally, the PHP source code is available from SourceForge: http://sourceforge.net/projects/taxongrab, and the project website is http://research.amnh.org/informatics/taxlit/apps/.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/17
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/19
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"050808 2005 eng "
1546-9735
10.17161/bi.v2i0.19
doi
dc
Challenges Building Online GIS Services to Support Global Biodiversity Mapping and Analysis: Lessons from the Mountain and Plains Database and Informatics project.
Guralnick, Robert P
University of Colorado
Neufeld, David
University of Colorado
We argue that distributed mapping and analysis of biodiversity information becoming available on global distributed networks is a lynchpin activity linking together research and development challenges in biodiversity informatics. Online mapping is a core activity because it allows users to visually explore the spatial context of biodiversity information and quickly assemble the datasets needed to ask and answer biodiversity research and management questions. We make the case that a free, online global biodiversity mapping tool utilizing distributed species occurrence records is now within reach and discuss how such a system can be built using existing technology. We also discuss additional challenges and solutions given experiences building a regional distributed GIS tool called MaPSTeDI (Mountain and Plains Spatio-Temporal Database and Informatics Initiative). We focus on solutions to three challenges in particular: Returning result queries in a reasonable amount of time given network limitations; Accessing multiple data sources using different transmission mechanisms; Scaling from a solution for a handful of data providers to hundreds or thousands of providers. We close by discussing the future challenges and potential solutions for integrating analysis tools into distributed mapping applications.
The University of Kansas
2005-01-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/19
Biodiversity Informatics; Vol. 2 (2005)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/25
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"060602 2006 eng "
1546-9735
10.17161/bi.v3i0.25
doi
dc
Taxonomic names, metadata, and the Semantic Web
Page, Roderic D. M.
University of Glasgow
Life Science Identifiers (LSIDs) offer an attractive solution to the problem of globally unique identifiers for digital objects in biology. However, I suggest that in the context of taxonomic names, the most compelling benefit of adopting these identifiers comes from the metadata associated with each LSID. By using existing vocabularies wherever possible, and using a simple vocabulary for taxonomy-specific concepts we can quickly capture the essential information about a taxonomic name in the Resource Description Framework (RDF) format. This opens up the prospect of using technologies developed for the Semantic Web to add ``taxonomic intelligence" to biodiversity databases. This essay explores some of these ideas in the context of providing a taxonomic framework for the phylogenetic database TreeBASE.
The University of Kansas
2006-06-22 20:39:49
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/25
Biodiversity Informatics; Vol. 3 (2006)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/26
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"061015 2006 eng "
1546-9735
10.17161/bi.v3i0.26
doi
dc
A synecological framework for systematic conservation planning
Hortal, Joaquín
Center for Macroecology, University of Copenhagen
Lobo, Jorge M
Museo Nacional ciencias Naturales
Biodiversity conservation design, though difficult with fragmentary or insufficient biological data, can be planned and evaluated with several methods. One of them, the complementarity criterion, is commonly used nowadays to deal with the distribution of number of species (i.e., an autoecological approach). At the same time, the patchiness and spatial bias of available distribution data has also been dealt with through distribution modelling. However, both the uncertainty of the ranges estimated, and the changes in species distribution in response to changing climates, limit single-species the biodiversity attribute to be used in complementarity strategies. Several technical and theoretical advantages of composite biodiversity variables (i.e., a synecological approach) may, however, make them ideal biodiversity indicators for conservation area selection. The drawbacks associated with current biodiversity data are discussed herein, along with the possible advantages and disadvantages of conservation planning through a synecological or autoecological approach.
The University of Kansas
2006-06-22 20:39:49
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/26
Biodiversity Informatics; Vol. 3 (2006)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/29
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"061201 2006 eng "
1546-9735
10.17161/bi.v3i0.29
doi
dc
Uses and Requirements of Ecological Niche Models and Related Distributional Models
Peterson, A. Townsend
University of Kansas
Abstract.—Modeling approaches that relate known occurrences of species to landscape features to discover ecological properties and predict geographic occurrences have seen extensive recent application in ecology, systematics, and conservation. A key component in this process is estimation or characterization of species’ distributions in ecological space, which can then be useful in understanding their potential distributions in geographic space. Hence, this process is often termed ecological niche modeling or (less boldly) species distribution modeling. Applications of this approach vary widely in their aims, products, and requirements; this variety is reviewed herein, examples are provided, and differences in data needs and possible interpretations are discussed.
The University of Kansas
2006-06-22 20:39:49
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/29
Biodiversity Informatics; Vol. 3 (2006)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/34
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"061202 2006 eng "
1546-9735
10.17161/bi.v3i0.34
doi
dc
A combining approach to find all taxon names (FAT)
Sautter, Guido
Böhm, Klemens
Agosti, Donat
Most of the literature on natural history is hidden in millions of pages stacked up in our libraries. Various initiatives aim now at making these publications digitally accessible and searchable, applying xml-mark up technologies. The unique biological names play a crucial role to link content related to a particular taxon. Thus discovering and marking them up is extremely important. Since their manual extraction and markup is cumbersome and time-intensive, it needs be automated. In this paper, we present computational linguistics techniques and evaluate how they can help to extract taxonomic names auto-matically. We build on an existing approach for extraction of such names (Koning et al. 2005) and combine it with several other learning techniques. We apply them to the texts sequentially so that each technique can use the results from the preceding ones. In particular, we use structural rules, dynamic lexica with fuzzy lookups, and word-level language recognition. We use legacy documents from different sources and times as test bed for our evaluation. The experimental results for our combining approach (FAT) show greater than 99% precision and recall. They reveal the potential of computational linguis-tics techniques towards an automated markup of biosystematics publications.
The University of Kansas
2006-06-22 20:39:49
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/34
Biodiversity Informatics; Vol. 3 (2006)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/35
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"071113 2007 eng "
1546-9735
10.17161/bi.v4i0.35
doi
dc
Online Biodiversity Resources - Principles for Usability
Neale, Sophie
Pullan, M. R.
Watson, M. F.
Online biodiversity portals and databases enabling access to large volumes of biological information represent a potentially extensive set of resources for a variety of user groups. However, in order for these resources to live up to their promise they need to be both useful and easy to use. We discuss a number of principles for designing systems for usability, examine how these have been applied to the development of online biodiversity resources and compare this with a portal project developed by the Astrophysics community. We highlight a lack of user involvement and formalised requirements analysis by biodiversity projects resulting in a poor understanding of both the users and their tasks. We suggest a change in the way large biodiversity portal projects are structured, that is by providing infrastructure and supporting user groups developing individual interfaces.
The University of Kansas
2007-08-21 13:53:04
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/35
Biodiversity Informatics; Vol. 4 (2007)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/36
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"070821 2007 eng "
1546-9735
10.17161/bi.v4i0.36
doi
dc
A Quantitative Comparison of XML Schemas for Taxonomic Publications
Sautter, Guido
Böhm, Klemens
Agosti, Donat
Large numbers of legacy taxonomic publications are currently being digitized to make them online available and ready for full text search. The documents are being marked up with XML for two purposes: To preserve the document structure, and to facilitate access via standard query languages like XQuery. With regard to the second aspect, the choice of an appropriate XML schema is crucial. It affects both query performance and the correctness of query results. Over the last few years, several different XML schemas have been proposed as markup standards for taxonomic publications. In this paper, we report on a thorough evaluation and com¬parison of these schemas. We have examined if they facilitate formulation and correct processing of queries that are common when it comes to taxonomic literature. We also compare the performance of these queries on documents that are marked up with the different schemas. Finally, we propose extensions to the schemas that enhance correctness of query results.
The University of Kansas
2007-08-21 13:53:04
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/36
Biodiversity Informatics; Vol. 4 (2007)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/37
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"070821 2007 eng "
1546-9735
10.17161/bi.v4i0.37
doi
dc
Ecological Niche Modeling Approaches to Conservation of Endangered and Threatened Birds in Central and Eastern Europe
Papes, Monica
University of Kansas
Comprehensive biodiversity surveys are unavailable for most Central and Eastern European countries. Although birds in general are well-studied, distributional information in the region is sparse and largely out-of of-date; I used museum specimen locality records and raster GIS data layers summarizing environmental dimensions to produce distributional hypotheses for the 36 threatened and endangered bird species in the region using ecological niche modeling. These ecological niche models were also used to predict likely future (2055) distributional shifts owing to global climate change. The entire suite of distributional information that resulted was used to evaluate strategies for conservation via simple heuristic place-prioritization algorithms based on complementarity and rarity considerations. These analyses identified priority areas in southern and eastern Romania, as well as other areas across the region, as priority targets for conservation action in the region.
The University of Kansas
2007-08-21 13:53:04
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/37
Biodiversity Informatics; Vol. 4 (2007)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/39
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"080120 2008 eng "
1546-9735
10.17161/bi.v5i0.39
doi
dc
Where and how to manage: Optimal selection of conservation actions for multiple species.
Teeffelen, Astrid van
Wageningen University, the Netherlands http://www.lup.wur.nl/uk/staff/teeffelen
Moilanen, Atte
Metapopulation Research Group, Department of Biological and Environmental Sciences, University of Helsinki, FINLAND
Multiple alternative options are frequently available for the protection, maintenance or restoration of conservation areas. The choice of a particular management action can have large effects on the species occurring in the area, because different actions have different effects on different species. Together with the fact that conservation funds are limited and particular management actions are costly, it would be desirable to be able to identify where, and what kind of management should be applied to maximize conservation benefits. Currently available site-selection algorithms can identify the optimal set of sites for a reserve network. However, these algorithms have not been designed to answer what kind of action would be most beneficial at these sites when multiple alternative actions are available. We describe an algorithm capable of solving multi-species planning problems with multiple management options per site. The algorithm is based on benefit functions, which translate the effect of a management action on species representation levels into a value, in order to identify the most beneficial option. We test the performance of this algorithm with simulated data for different types of benefit functions and show that the algorithm’s solutions are optimal, or very near globally optimal, partially depending on the type of benefit function used. The good performance of the proposed algorithm suggests that it could be profitably used for large multi-action multi-species conservation planning problems.
The University of Kansas
2008-01-20 12:44:51
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/39
Biodiversity Informatics; Vol. 5 (2008)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/40
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"080131 2008 eng "
1546-9735
10.17161/bi.v5i0.40
doi
dc
More complex distribution models or more representative data?
Lobo, Jorge M
Museo Nacional de Ciencias Naturales
Distribution models for species are increasingly used to summarize species’ geography in conservation analyses. These models use increasingly sophisticated modeling techniques, but often lack detailed examination of the quality of the biological occurrence data on which they are based. I analyze the results of the best comparative study of the performance of different modeling techniques, which used pseudo-absence data selected at random. I provide an example of variation in model accuracy depending on the type of absence information used, showing that good model predictions depend most critically on better biological data.
The University of Kansas
2008-01-20 12:44:51
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/40
Biodiversity Informatics; Vol. 5 (2008)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/46
2018-01-12T01:58:46Z
jbi:ART
nmb a2200000Iu 4500
"080428 2008 eng "
1546-9735
10.17161/bi.v5i0.46
doi
dc
Converting Taxonomic Descriptions to New Digital Formats
cui, hong
Abstract.--The majority of taxonomic descriptions is currently in print format. The majority of digital descriptions are in formats such as DOC, HTML, or PDF and for human readers. These formats do not convey rich semantics in taxonomic descriptions for computer-aided process. Newer digital formats such as XML and RDF accommodate semantic annotations that allow computers to process the rich semantics on human's behalf, thus open up opportunities for a wide range of innovative usages of taxonomic descriptions, such as searching in more precise and flexible ways, integrating with gnomic and geographic information, generating taxonomic keys automatically, and text data mining and information visualization etc. This paper discusses the challenges in automated conversion of multiple collections of descriptions to XML format and reports an automated system, MARTT. MARTT is a machine-learning system that makes use of training examples to tag new descriptions into XML format. A number of utilities are implemented as solutions to the challenges. The utilities are used to reduce the effort for training example preparation, to facilitate the creation of a comprehensive schema, and to predict system performance on a new collection of descriptions. The system has been tested with several plant and alga taxonomic publications including Flora of China and Flora of North America.
The University of Kansas
2008-01-20 12:44:51
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/46
Biodiversity Informatics; Vol. 5 (2008)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/1574
2022-10-03T18:18:20Z
jbi:ART
nmb a2200000Iu 4500
"090715 2009 eng "
1546-9735
10.17161/bi.v6i1.1574
doi
dc
BRIDGING THE GAP BETWEEN TECHNOLOGY AND SCIENCE WITH EXAMPLES FROM ECOLOGY AND BIODIVERSITY
Downey, Laura
Pennington, Deana
Early informatics focused primarily on the application of technology and computer science to a specific domain; modern informatics has broadened to encompass human and knowledge dimensions. Application of technology is but one aspect of informatics. Understanding domain members’ issues, priorities, knowledge, abilities, interactions, tasks and work environments is another aspect, and one that directly impacts application success. Involving domain members in the design and development of technology in their domain is a key factor in bridging the gap between technology and science. This user-centered design (UCD) approach in informatics is presented via an ecoinformatics case study in three areas: collaboration, usability, and education and training.
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/1574
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Laura Downey, Deana Pennington
oai:ojs.pkp.sfu.ca:article/1626
2022-10-03T18:16:40Z
jbi:ART
nmb a2200000Iu 4500
"090213 2009 eng "
1546-9735
10.17161/bi.v6i1.1626
doi
dc
DARWIN CORE BASED DATA STREAMLINING WITH DigiMus 2.0
Kakodkar, Aditya P
National Institute of Oceanography, Dona Paula, Goa, India.
Kerkar, Sarika S.
National Institute of Oceanography, Dona Paula, Goa, India.
Varghese, Neena S.
National Institute of Oceanography, Dona Paula, Goa, India.
Kavlekar, Devanand P.
National Institute of Oceanography, Dona Paula, Goa, India.
Achuthankutty, C. T.
National Institute of Oceanography, Dona Paula, Goa, India.
Cataloguing biological specimen is a important activity of biological museums world over. Software developed especially for this purpose have evolved overtime to achieve more accuracy in retrieving data from large and diverse datasets. Combining smaller datasets in to a larger information system requires uniformity of data based on a single data standard. In the developing world smaller datasets are maintained by individual researchers or small college and university groups. For standardizing data from such datasets, software needs to be developed, which require expertise and sufficient funds which are often unavailable. We present a simple open source web based tool developed using PHP to enable an individual with little or no knowledge of information systems or databases, to effectively streamline specimen data with data standard Darwin Core 1.2 ( DwC 1.2). Such data can then be shared and easily provided to larger datasets like Ocean Biogeographic Information Systems (OBIS) and Global Biodiversity Information Facility (GBIF). This tool can be accessed at http://www.niobioinformatics.in/digimus.php and its source code is freely available at http://www.niobioinformatics.in/digimus_source.php
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/1626
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Aditya P Kakodkar, Sarika S. Kerkar, Neena S. Varghese, Devanand P. Kavlekar, C. T. Achuthankutty
oai:ojs.pkp.sfu.ca:article/1631
2022-10-03T18:19:57Z
jbi:ART
nmb a2200000Iu 4500
"090905 2009 eng "
1546-9735
10.17161/bi.v6i1.1631
doi
dc
EFFECTIVELY SEARCHING SPECIMEN AND OBSERVATION DATA WITH TOQE, THE THESAURUS OPTIMIZED QUERY EXPANDER
Güntsch, Anton
Botanic Garden and Botanical Museum Berlin-Dahlem http://www.bgbm.org/guentsch/
Hoffmann, Niels
Botanic Garden and Botanical Museum Berlin-Dahlem
Kelbert, Patricia
Botanic Garden and Botanical Museum Berlin-Dahlem
Berendsohn, Walter G.
Botanic Garden and Botanical Museum Berlin-Dahlem
Today’s specimen and observation data portals lack a flexible mechanism, able to link up thesaurus-enabled data sources such as taxonomic checklist databases and expand user queries to related terms, significantly enhancing result sets. The TOQE system (Thesaurus Optimized Query Expander) is a REST-like XML web-service implemented in Python and designed for this purpose. Acting as an interface between portals and thesauri, TOQE allows the implementation of specialized portal systems with a set of thesauri supporting its specific focus. It is both easy to use for portal programmers and easy to configure for thesaurus database holders who want to expose their system as a service for query expansions. Currently, TOQE is used in four specimen and observation data portals. The documentation is available from http://search.biocase.org/toqe/.
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/1631
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Anton Güntsch, Niels Hoffmann, Patricia Kelbert, Walter G. Berendsohn
oai:ojs.pkp.sfu.ca:article/1633
2022-10-03T18:17:53Z
jbi:ART
nmb a2200000Iu 4500
"090410 2009 eng "
1546-9735
10.17161/bi.v6i1.1633
doi
dc
AN EFFICIENT SEGMENTATION ALGORITHM FOR ENTITY INTERACTION
Ch'ng, Eugene
University of Wolverhampton, School of Computing and Information Technology, UK http://opennature.org
The inventorying of biological diversity and studies in biocomplexity require the management of large electronic datasets of organisms. While species inventory has adopted structured electronic databases for some time, the
computer modelling of the functional interactions between biological entities at all levels of life is still in the stage of development. One of the challenges for this type of modelling is the biotic interactions that occur between large datasets of entities represented as computer algorithms. In real-time simulation that models the biotic interactions of large population datasets, the use of computational processing time could be extensive. One way of increasing the efficiency of such simulation is to partition the landscape so that entities need only traverse its local space for entities that falls within the interaction proximity. This article presents an efficient segmentation algorithm for biotic
interactions for research related to the modelling and simulation of biological systems.
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/1633
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Eugene Ch'ng
oai:ojs.pkp.sfu.ca:article/1634
2022-10-03T18:18:51Z
jbi:ART
nmb a2200000Iu 4500
"090820 2009 eng "
1546-9735
10.17161/bi.v6i1.1634
doi
dc
ENVIRONMENTAL CORRELATION STRUCTURE AND ECOLOGICAL NICHE MODEL PROJECTIONS
Jiménez-Valverde, Alberto
University of Kansas
Nakazawa, Yoshinori
University of Kansas
Lira-Noriega, Andrés
University of Kansas
Peterson, A. Townsend
University of Kansas
None
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/1634
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Alberto Jiménez-Valverde, Yoshinori Nakazawa, Andrés Lira-Noriega, A. Townsend Peterson
oai:ojs.pkp.sfu.ca:article/3314
2022-10-03T18:19:22Z
jbi:ART
nmb a2200000Iu 4500
"090905 2009 eng "
1546-9735
10.17161/bi.v6i1.3314
doi
dc
LOCALITY UNCERTAINTY AND THE DIFFERENTIAL PERFORMANCE OF FOUR COMMON NICHE-BASED MODELING TECHNIQUES
Fernandez, Miguel
Blum, Stanley
Research Informatics, California Academy of Sciences
Reichle, Steffen
The Nature Conservancy
Guo, Qinghua
Sierra Nevada Research Institute, University of California Merced
Holzman, Barbara
Department of Geography, San Francisco State University
Hamilton, Healy
Center for Biodiversity & Research, California Academy of Sciences
We address a poorly understood aspect of ecological niche modeling: its sensitivity to different levels of geographic uncertainty in organism occurrence data. Our primary interest was to assess how accuracy degrades under increasing uncertainty, with performance measured indirectly through model consistency. We used Monte Carlo simulations and a similarity measure to assess model sensitivity across three variables: locality accuracy, niche modeling method, and species. Randomly generated data sets with known levels of locality uncertainty were compared to an original prediction using Fuzzy Kappa. Data sets where locality uncertainty is low were expected to produce similar distribution maps to the original. In contrast, data sets where locality uncertainty is high were expected to produce less similar maps. BIOCLIM, DOMAIN, Maxent and GARP were used to predict the distributions for 1200 simulated datasets (3 species x 4 buffer sizes x 100 randomized data sets). Thus, our experimental design produced a total of 4800 similarity measures, with each of the simulated distributions compared to the prediction of the original data set and corresponding modeling method. A general linear model (GLM) analysis was performed which enables us to simultaneously measure the effect of buffer size, modeling method, and species, as well as interactions among all variables. Our results show that modeling method has the largest effect on similarity scores and uniquely accounts for 40% of the total variance in the model. The second most important factor was buffer size, but it uniquely accounts for only 3% of the variation in the model. The newer and currently more popular methods, GARP and Maxent, were shown to produce more inconsistent predictions than the earlier and simpler methods, BIOCLIM and DOMAIN. Understanding the performance of different niche modeling methods under varying levels of geographic uncertainty is an important step toward more productive applications of historical biodiversity collections.
The University of Kansas
2009-02-13 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3314
Biodiversity Informatics; Vol. 6 (2009)
eng
Copyright (c) 2009 Miguel Fernandez, Stanley Blum, Steffen Reichle, Qinghua Guo, Barbara Holzman, Healy Hamilton
oai:ojs.pkp.sfu.ca:article/3631
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"100615 2010 eng "
1546-9735
10.17161/bi.v7i1.3631
doi
dc
USING TAXONOMIC REVISION DATA TO ESTIMATE THE GLOBAL SPECIES RICHNESS AND CHARACTERISTICS OF UNDESCRIBED SPECIES OF DIVING BEETLES (COLEOPTERA: DYTISCIDAE)
Nilsson-Örtman, Viktor
http://www.emg.umu.se/en/researchers/viktor-nilsson.html
Nilsson, Anders N.
Umeå University
Many methods used for estimating species richness are either difficult to use on poorly known taxa or require input data that are laborious and expensive to collect. In this paper we apply a method which takes advantage of the carefully conducted tests of how the described diversity compares to real species richness that are inherent in taxonomic revisions. We analyze the quantitative outcome from such revisions with respect to body size, zoogeographical region and phylogenetic relationship. The best fitting model is used to predict the diversity of unrevised groups if these would have been subject to as rigorous species level hypothesis-testing as the revised groups. The sensitivity of the predictive model to single observations is estimated by bootstrapping over resampled subsets of the original data. The Dytiscidae is with its 4080 described species (end of May 2009) the most diverse group of aquatic beetles and have a world-wide distribution. Extensive taxonomic work has been carried out on the family but still the number of described species increases exponentially in most zoogeographical regions making many commonly used methods of estimation difficult to apply. We provide independent species richness estimates of subsamples for which species richness estimates can be reached through extrapolation and compare these to the species richness estimates obtained through the method using revision data. We estimate there to be 5405 species of dytiscids, a 1.32-fold increase over the present number of described species. The undescribed diversity is likely to be biased towards species with small body size from tropical regions outside of Africa.
The University of Kansas
2010-06-15 00:00:00
Peer-reviewed Article
application/pdf
application/vnd.openxmlformats-officedocument.wordprocessingml.document
application/vnd.openxmlformats-officedocument.wordprocessingml.document
https://journals.ku.edu/jbi/article/view/3631
Biodiversity Informatics; Vol. 7 No. 1 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3664
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"100615 2010 eng "
1546-9735
10.17161/bi.v7i1.3664
doi
dc
ORGANIZATION OF BIODIVERSITY RESOURCES BASED ON THE PROCESS OF THEIR CREATION AND THE ROLE OF INDIVIDUAL ORGANISMS AS RESOURCE RELATIONSHIP NODES
Baskauf, Steven J
Vanderbilt University Dept. of Biological Sciences http://bioimages.vanderbilt.edu/
Abstract. - Kinds of occurrences (evidence of particular living organisms) can be grouped by common data and metadata characteristics that are determined by the way that the occurrence represents the organism. The creation of occurrence resources follows a pattern which can be used as the basis for organizing both the metadata associated with those resources and the relationships among the resources. The central feature of this organizational system is a resource representing the individual organism. This resource serves as a node which connects the organism's occurrences and any determinations of the organism's taxonomic identity. I specify a relatively small number of predicates which can define the important relationships among these resources and suggest which metadata properties should logically be associated with each kind of resource.
The University of Kansas
2010-06-15 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3664
Biodiversity Informatics; Vol. 7 No. 1 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3927
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"110109 2011 eng "
1546-9735
10.17161/bi.v7i1.3927
doi
dc
BIOLOGICAL TAXONOMY AND ONTOLOGY DEVELOPMENT: SCOPE AND LIMITATIONS
Franz, Nico M
University of Puerto Rico
The prospects of integrating full-blown biological taxonomies into an ontological reasoning framework are critically reviewed. The common usage of a static 'snapshot' hierarchy in ontological representations of taxonomy is contrasted with a more realistic situation that involves dynamic, piece-meal revisions of particular taxonomic groups and requires alignment with relevant preceding perspectives. Taxonomic practice is characterized by a range of phenomena that are orthogonal to the logical background from which ontological entities and relationships originate, and therefore pose special challenges to ontological representation and reasoning. Among these phenomena are: (1) the notion that there is a single phylogenetic hierarchy in nature which taxonomy can only gradually approximate; (2) the evolvability of taxa which means that taxon-defining features may be lost in subordinate members or independently gained across multiple sections of the tree of life; (3) the hybrid approach of defining taxa both in reference to properties (intensional) and members (ostensive) which undermines the individual/class dichotomy sustaining conventional ontologies; (4) the idiosyncratic yet inferentially valuable usage of Linnaean ranks; (5) the indelible and semantically complex 250-year legacy of nomenclatural and taxonomic changes that characterizes the current system; (6) the insufficient taxonomic exploration of large portions of the tree of life; and the need to use a sophisticated terminology for aligning taxonomic entities in order to integrate both (7) single and (8) multiple hierarchies. It is suggested that research along the taxonomy/ontology interface should focus on either strictly nomenclatural entities or specialize in ontology-driven methods for producing alignments between multiple taxonomies.
The University of Kansas
2010-06-15 00:00:00
Peer-reviewed Article
application/pdf
application/pdf
https://journals.ku.edu/jbi/article/view/3927
Biodiversity Informatics; Vol. 7 No. 1 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3986
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101104 2010 eng "
1546-9735
10.17161/bi.v7i3.3986
doi
dc
A SPREADSHEET MAPPING APPROACH FOR ERROR CHECKING AND SHARING COLLECTION POINT DATA
Foley, Desmond
Division of Entomology, Walter Reed Army Institute of Research
The ready availability of online maps of plant and animal collection locations has drawn attention to the need for georeference accuracy. Many obvious georeference errors, for example, that map land animals over sea, the wrong hemisphere, or the wrong country, may be avoided if collectors and data providers could easily map their data points prior to publication. Various tools are available for quality control of georeference data, but many involve an investment of time to learn the software involved. This paper presents a method for the rapid map display of longitude and latitude data using the chart function in Microsoft Office Excel®, arguably the most ubiquitous spreadsheet software. Advantages of this method include: immediate visual feedback to assess data point accuracy; and results that can be easily shared with others. Methods for making custom Excel chart maps are given, and we provide free charts for the world and a selection of countries at http://www.vectormap.org/resources.htm.
The University of Kansas
2011-01-07 16:25:58
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3986
Biodiversity Informatics; Vol. 7 No. 3 (2011)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3987
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3987
doi
dc
Leveraging the fullest potential of scientific collections through digitisation.
Baird, Roger Charles
Canadian Museum of Nature http://www.nature.ca
Access to digitised specimen data is a vital means to distribute information and in turn create knowledge. Pooling the accessibility of specimen and observation data under common standards and harnessing the power of distributed datasets places more and more information and the disposal of a globally dispersed work force, which would otherwise carry on its work in relative isolation, and with limited profile and impact. Citing a number of higher profile national and international projects, it is argued that a globally coordinated approach to the digitisation of a critical mass of scientific specimens and specimen-related data is highly desirable and required, to maximize the value of these collections to civil society and to support the advancement of our scientific knowledge globally.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3987
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3988
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3988
doi
dc
Using geographical and taxonomic metadata to set priorities in specimen digitization
Berendsohn, Walter G.
Seltmann, Peggy
Botanic Garden & Botanical Museum Berlin-Dahlem, Freie Universität Berlin
Digitizing the information carried by specimens in natural history collections is a key endeavor providing falsifiable information about past and present biodiversity on a global scale, for application in a variety of research fields far beyond the current application in biosystematics. Existing digitization efforts are driven by individual institutional necessities and are not coordinated on a global scale. This led to an over-all information resource that is patchy in taxonomic and geographic coverage as well as in quality. Digitizing all specimens is not an achievable aim at present, so that priorities need to be set. Most biodiversity studies are both taxonomically and geographically restricted, but access to non-digitized collection information is almost exclusively by taxon name. Creating a “Geotaxonomic Index” providing metadata on the number of specimens from a specific geographic region belonging to a specific higher taxonomic category may provide a means to attract the attention of researchers and governments towards relevant non-digitized holdings of the collections and set priorities for their digitization according to the needs of information users outside the taxonomic community.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3988
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3989
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3989
doi
dc
Summary of Recommendations of the GBIF Task Group on the Global Strategy and Action Plan for the Digitisation of Natural History Collections
Berendsohn, Walter G.
Chavan, Vishwas
Macklin, James
The Global Biodiversity Information Facility’s Task Group has formulated three basic recommendations to the GBIF Governing Board in order to increase the rate of the digitization of natural history collections and improve the usage of this information resource: (i) GBIF must facilitate access to information about non-digitized collection resources by publicizing the research potential of collections through metadata and assessing the number of non-digitized specimens; (ii) GBIF must work with collections to continue to increase the efficiency of specimen data capture and to enhance data quality by means of technical measures, by means of ensuring attribution and professional credit and influencing institutional priorities, and by engaging with funding agencies; (iii) GBIF must continue to improve and promote the global infrastructure used to mobilize digitized collection data through technical measures, outreach activities and political measures.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3989
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3990
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3990
doi
dc
TOWARDS DEMAND DRIVEN PUBLISHING: APPROCHES TO THE PRIORITISATION OF DIGITISATION OF NATURAL HISTORY COLLECTIONS DATA
Chavan, Vishwas
Global Biodiversity Information Facility http://www.vishwaschavan.com
BERENTS, PENNY
Australian Museum
HAMER, MICHELLE
South African National Biodiversity Institute
Natural history collections represent a vast repository of biodiversity data of international significance. There is an imperative to capture the data through digitisation projects in order to expose the data to new and established users of biodiversity data. On the basis of review of current state of digitization of natural history collections, a demand driven approach is advocated through the use of metadata to promote and increase access to natural history collection data.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
application/msword
https://journals.ku.edu/jbi/article/view/3990
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3991
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3991
doi
dc
Approaches to estimating the universe of natural history collections data
Ariño, Arturo H.
University of Navarra http://www.unav.es/unzyec/
This contribution explores the problem of recognizing and measuring the universe of specimen-level data existing in Natural History Collections around the world, in absence of a complete, world-wide census or register. Estimates of size seem necessary to plan for resource allocation for digitization or data capture, and may help represent how many vouchered primary biodiversity data (in terms of collections, specimens or curatorial units) might remain to be mobilized.
Three general approaches are proposed for further development, and initial estimates are given. Probabilistic models involve crossing data from a set of biodiversity datasets, finding commonalities and estimating the likelihood of totally obscure data from the fraction of known data missing from specific datasets in the set. Distribution models aim to find the underlying distribution of collections’ compositions, figuring out the occult sector of the distributions. Finally, case studies seek to compare digitized data from collections known to the world to the amount of data known to exist in the collection but not generally available or not digitized.
Preliminary estimates range from 1.2 to 2.1 gigaunits, of which a mere 3% at most is currently web-accessible through GBIF’s mobilization efforts. However, further data and analyses, along with other approaches relying more heavily on surveys, might change the picture and possibly help narrow the estimate. In particular, unknown collections not having emerged through literature are the major source of uncertainty.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
application/msword
https://journals.ku.edu/jbi/article/view/3991
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3992
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.3992
doi
dc
Natural History Specimen Digitization: Challenges and Concerns
Vollmar, Ana
Macklin, James Alexander
Harvard University Herbaria
Ford, Linda
A survey on the challenges and concerns invovled with digitizing natural history specimens was circulated to curators, collections managers, and administrators in the natural history community in the Spring of 2009, with over 200 responses received. The overwhelming barrier to digitizing collections was a lack of funding, based on a limited number of sources, leaving institutions mostly responsible for providing the necessary support. The uneven digitization landscape leads to a patchy accumulation of records at varying qualities, and based on different priorities, ulitimately influencing the data's fitness for use. The survey also found that although the kind of specimens found in collections and their storage can be quite varible, there are many similar challenges when digitizing including imaging, automated text scanning and parsing, geo-referencing, etc. Thus, better communication between domains could foster knowledge on digitization leading to efficiencies that could be disseminated through documentation of best practices and training.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3992
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/3994
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101016 2010 eng "
1546-9735
10.17161/bi.v7i2.3994
doi
dc
Rationale and Value of Natural History Collections Digitisation
Scoble, Malcolm
Deparrtment of Entomology, Natural History Museum, Cromwell Road, London
Natural science collections comprise a small component of a more extensive source of data on which questions about the natural world may be addressed. However, NHC data offer, when digitised, an exceptional resource: within collections lies the most extensive dataset that exists of the planet’s biodiversity. Indeed, our entire knowledge of most species is based on just one or very few specimens housed in natural science collections. Nevertheless, for most species, collections provide us with the best record available. The physical presence of specimens allows us to examine them many times using new techniques (e.g. the extraction and study of molecular data). In this article we argue in favor of expedited digitisation of NHC data.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/3994
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4019
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"101009 2010 eng "
1546-9735
10.17161/bi.v7i2.4019
doi
dc
Thoughts on implementation of the recommendations of the GBIF Task Group on a Global Strategy and Action Plan for Mobilisation of Natural History Collections Data
King, Nicholas
Global Biodiversity Information Facility
Krishtalka, Leonard
Natural History Museum and Biodiversity Research Center, Department of Ecology and Evolutionary Biology, The University of Kansas
Chavan, Vishwas
Global Biodiversity Information Facility http://www.vishwaschavan.com
The Global Biodiversity Information Facility (GBIF) has a mandate to facilitate free and open access to primary biodiversity data worldwide. This Special Issue of Biodiversity Informatics publishes the findings of the recent GBIF Task Group on a Global Strategy and Action Plan for Mobilisation of Natural History Collections Data (GSAP-NHC). The GSAP-NHC Task Group has made three primary recommendations dealing with discovery, capture, and publishing of natural history collections data. This overview article provides insight on various activities initiated by GBIF to date to assist with an early uptake and implementation of these recommendations. It calls for proactive participation by all relevant players and stakeholder communities. Given recent technological progress and growing recognition and attention to biodiversity science worldwide, we think rapid progress in discovery, publishing and access to large volumes of useful collection data can be achieved for the immediate benefit of science and society.
The University of Kansas
2010-10-11 12:13:20
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4019
Biodiversity Informatics; Vol. 7 No. 2 (2010)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4094
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"130709 2013 eng "
1546-9735
10.17161/bi.v8i2.4094
doi
dc
Assessment of user needs of primary biodiversity data: Analysis, concerns, and challenges
Ariño, Arturo H.
University of Navarra http://www.unav.es/unzyec/
Chavan, Vishwas
Global Biodiversity Information Facility Secretariat http://www.gbif.org
Faith, Daniel P.
Australian Museum
A Content Needs Assessment (CNA) survey has been conducted in order to determine what GBIF-mediated data users may be using, what they would be using if available, and what they need in terms of primary biodiversity data records. The survey was launched in 2009 in six languages, and collected more than 700 individual responses. Analysis of the responses showed some lack of awareness about the availability of accessible primary data, and pointed out some types of data in high demand for linking to distribution and taxonomical data now derived from the GBIF cache. A notable example was linkages to molecular data. Also, the CNA survey uncovered some biases in the design of user needs surveys, by showing demographic and linguistic effects that may have influenced the distribution of responses received in analogous surveys conducted at the global scale.
The University of Kansas
2013-07-09 11:01:34
Peer-reviewed Article
application/pdf
application/pdf
https://journals.ku.edu/jbi/article/view/4094
Biodiversity Informatics; Vol. 8 No. 2 (2013)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4095
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"120716 2012 eng "
1546-9735
10.17161/bi.v8i1.4095
doi
dc
The Darwin Core extension for genebanks opens up new opportunities for sharing genebank datasets
Endresen, Dag Terje Filip
Global Biodiversity Information Facility http://www.gbif.org
Knüpffer, Helmut
Leibniz Institute of Plant Genetics and Crop Plant Research http://www.ipk-gatersleben.de/Internet/Forschung/Genbank
Darwin Core (DwC) defines a standard set of terms to describe the primary biodiversity data. Primary biodiversity data are data records derived from direct observation of species occurrences in nature or describing specimens in biological collections. The Darwin Core terms can be seen as an extension to the standard Dublin Core metadata terms. The new Darwin Core extension for genebanks declares the additional terms required for describing genebank datasets, and is based on established standards from the plant genetic resources community. The Global Biodiversity Information Facility (GBIF) provides an information infrastructure for biodiversity data including a suite of software tools for data publishing, distributed data access, and the capture of biodiversity data. The Darwin Core extension for genebanks is a key component that provides access for the genebanks and the plant genetic resources community to the GBIF informatics infrastructure including the new toolkits for data exchange. This paper provides one of the first examples and guidelines for how to create extensions to the Darwin Core standard.
The University of Kansas
2012-06-21 16:10:38
Peer-reviewed Article
application/pdf
application/octet-stream
https://journals.ku.edu/jbi/article/view/4095
Biodiversity Informatics; Vol. 8 (2012)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4117
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"130709 2013 eng "
1546-9735
10.17161/bi.v8i2.4117
doi
dc
Discovery and publishing of primary biodiversity data associated with multimedia resources: The Audubon Core strategies and approaches
Morris, Robert A
Barve, Vijay
Foundation for Revitalisation of Local Health Traditions, Bangalore
Carausu, Mihail
Danish Biodiversity Information Facility (DanBIF)
Chavan, Vishwas
Global Biodiversity Information Facility Secretariat
Cuadra, José
Global Biodiversity Information Facility Secretariat
Freeland, Chris
Missouri Botanical Garden
Hagedorn, Gregor
Museum für Naturkunde Berlin
Leary, Patrick
Encyclopedia of Life
Mozzherin, Dimitry
Encyclopedia of Life
Olson, Annette
US Geological Survey, Reston, VA, USA (under contract via Information International Associates)
Riccardi, Gregory
Florida State University
Teage, Ivan
Natural History Museum
Whitbread, Greg
Australian National Botanical Gardena
The Audubon Core Multimedia Resource Metadata Schema is a representation-free vocabulary for the description of biodiversity multimedia resources and collections, now in the final stages as a proposed Biodiversity Informatics Standards (TDWG) standard. By defining only six terms as mandatory, it seeks to lighten the burden for providing or using multimedia useful for biodiversity science. At the same time it offers rich optional metadata terms that can help curators of multimedia collections provide authoritative media that document species occurrence, ecosystems, identification tools, ontologies, and many other kinds of biodiversity documents or data. About half of the vocabulary is re-used from other relevant controlled vocabularies that are often already in use for multimedia metadata, thereby reducing the mapping burden on existing repositories. A central design goal is to allow consuming applications to have a high likelihood of discovering suitable resources, reducing the human examination effort that might be required to decide if the resource is fit for the purpose of the application.
The University of Kansas
2013-07-09 11:01:34
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4117
Biodiversity Informatics; Vol. 8 No. 2 (2013)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4124
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"130709 2013 eng "
1546-9735
10.17161/bi.v8i2.4124
doi
dc
Content assessment of the primary biodiversity data published through GBIF network: Status, challenges and potentials
Gaiji, Samy
GBIF http://www.gbif.org
Chavan, Vishwas
GBIF
Ariño, Arturo H.
University of Navarra
Otegui, Javier
University of Navarra
Hobern, Donald
GBIF
Sood, Rajesh
GBIF
Robles, Estrella
University of Navarra
With the establishment of the Global Biodiversity Information Facility (GBIF) in 2001 as an inter-governmental co-ordinating body, concerted efforts were made during the past decade to establish a global research infrastructure to facilitate the sharing, discovery and access to primary biodiversity data. As on date the participants in GBIF have enabled the discovery and access to over 267+ million such data records. While this remarkable achievement in terms of volume of data must be acknowledged, concerns about the quality and ‘fitness-for-use’ of the data should also be carefully considered in future developments. This contribution is therefore a direct response to the calls for comprehensive content assessment of the GBIF mobilised data. It is the first comprehensive assessment of the coverage of the content mobilised so far through GBIF, as well as a mean to identify the existing gaps and reflect on fitness-for-use requirements. This paper describes the complementary methodologies adopted by the GBIF Secretariat and University of Navarra for the development of a comprehensive content assessment. Outcomes of these research initiatives are summarised in four categories, namely, (a) data quality assessment, (b) trends/patterns assessment, (c) fitness-for-use assessment, and (d) ecosystem specific data diversity assessment. In conclusion we make specific suggestions to the GBIF community on the adoption of common indicators to assess progress towards future targets as well as recommendations to populate such exercise at various levels within the GBIF Network from national level to thematic levels.
The University of Kansas
2013-07-09 11:01:34
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4124
Biodiversity Informatics; Vol. 8 No. 2 (2013)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4125
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"130709 2013 eng "
1546-9735
10.17161/bi.v8i2.4125
doi
dc
On the dates of GBIF mobilised primary biodiversity records
Otegui, Javier
University of Navarra http://www.unav.es/unzyec/
Ariño, Arturo H.
University of Navarra http://www.unav.es/unzyec/
Chavan, Vishwas
Global Biodiversity Information Facility Secretariat http://www.gbif.org
Gaiji, Samy
Global Biodiversity Information Facility Secretariat http://www.gbif.org
There are more than 267 million primary biodiversity data records published by hundreds of data publishers through the GBIF network. Thus, GBIF network is the single most comprehensive index for this kind of data. Ensuring or, at least, assessing data quality is of capital importance for the reliability and usability of this data. While conducting a time data gap analysis on this mass of data, we have detected some issues with the way date information is processed and shared. Dates can be obscured or altered under certain circumstances, when a specific combination of publisher’s error or date handling features, and faulty or inadequate date parsing and processing routines gets chained together. The extent of the date unreliability (either at the source or through GBIF portal) is not high, and further it is concentrated in a few data publishers. We analyse the types of errors and misprocessing in dates through the sources and the published records; assess their impact on the overall data quality of the published index, and suggest corrective measures.
The University of Kansas
2013-07-09 11:01:34
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4125
Biodiversity Informatics; Vol. 8 No. 2 (2013)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4126
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"130709 2013 eng "
1546-9735
10.17161/bi.v8i2.4126
doi
dc
Bridging the biodiversity data gaps: Recommendations to meet users’ data needs
Faith, Dan
Collen, Ben
Ariño, Arturo
Patricia Koleff, Patricia Koleff
Guinotte, John
Kerr, Jeremy
Chavan, Vishwas
A strong case has been made for freely available, high quality data on species occurrence, in order to track changes in biodiversity. However, one of the main issues surrounding the provision of such data is that sources vary in quality, scope, and accuracy. Therefore publishers of such data must face the challenge of maximizing quality, utility and breadth of data coverage, in order to make such data useful to users. Here, we report a number of recommendations that stem from a content need assessment survey conducted by the Global Biodiversity Information Facility (GBIF). Through this survey, we aimed to distil the main user needs regarding biodiversity data. We find a broad range of recommendations from the survey respondents, principally concerning issues such as data quality, bias, and coverage, and extending ease of access. We recommend a candidate set of actions for the GBIF that fall into three classes: 1) addressing data gaps, data volume, and data quality, 2) aggregating new kinds of data for new applications, and 3) promoting ease-of-use and providing incentives for wider use. Addressing the challenge of providing high quality primary biodiversity data can potentially serve the needs of many international biodiversity initiatives, including the new 2020 biodiversity targets of the Convention on Biological Diversity, the emerging global biodiversity observation network (GEO BON), and the new Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES).
The University of Kansas
2013-07-09 11:01:34
Peer-reviewed Article
application/pdf
application/msword
https://journals.ku.edu/jbi/article/view/4126
Biodiversity Informatics; Vol. 8 No. 2 (2013)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4263
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"120621 2012 eng "
1546-9735
10.17161/bi.v8i1.4263
doi
dc
A new era for specimen databases and biodiversity information management in South Africa
Coetzer, Willem
South African Institute for Aquatic Biodiversity http://www.saiab.ac.za
We comment on the inherited legacy, current state of, and future direction of the management of biodiversity information in natural history museums in South Africa. We emphasise the importance of training and capacity development to improve the quality and integration of biodiversity information for research.
The University of Kansas
2012-06-21 16:10:38
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4263
Biodiversity Informatics; Vol. 8 (2012)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4300
2018-01-12T01:58:47Z
jbi:TM
nmb a2200000Iu 4500
"120829 2012 eng "
1546-9735
10.17161/bi.v8i1.4300
doi
dc
Niche Modeling - Model Evaluation
Peterson, A. Townsend
Ecological niche modeling has become a very popular tool in ecological and biogeographic studies across broad extents. The tool is used in hundreds of publications each year now, but some fundamental aspects of the approach have seen a fair amount of carelessness. Among these aspects is that of model evaluation or validation. This unit provides a simple introduction to the basic concepts that are important in model validation, using some very simple examples. The focus is on two solutions to the challenge of model evaluation: a simple cumulative binomial approach that can be used with binary model outputs, and partial ROC analysis, which can be used with continuous model outputs.
The University of Kansas
2012-06-21 16:10:38
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/4300
Biodiversity Informatics; Vol. 8 (2012)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4326
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"120813 2012 eng "
1546-9735
10.17161/bi.v8i1.4326
doi
dc
DISENTANGLING INTERPOLATION AND EXTRAPOLATION UNCERTAINTIES IN SPECIES DISTRIBUTION MODELS: A NOVEL VISUALIZATION TECHNIQUE FOR THE SPATIAL VARIATION OF PREDICTOR VARIABLE COLINEARITY
Rödder, Dennis
Zoologisches Forschungsmuseum Alexander Koenig
Engler, Jan O.
Zoologisches Forschungsmuseum Alexander Koenig
Abstract. - Species distribution models (SDMs) are increasingly used in many scientific fields, with most studies requiring the application of the SDM to predict the likelihood of occurrence and/or environmental suitability in locations and time periods outside the range of the data set used to fit the model. Uncertainty in the quality of SDM predictions caused by errors of interpolation and extrapolation has been acknowledged for a long time, but the explicit consideration of the magnitude of such errors is, as yet, uncommon. Among other issues, the spatial variation in the colinearity of the environmental predictor variables used in the development of SDMs may cause misleading predictions when applying SDMs to novel locations and time periods. In this paper, we provide a framework for the spatially explicit identification of areas prone to errors caused by changes in the inter-correlation structure (i.e. their colinearity) of environmental predictors used for SDM development. The proposed method is compatible with all SDM algorithms currently employed, and expands the available toolbox for assessing the uncertainties raising from SDM predictions. We provide an implementation of the analysis as a script for the R statistical platform in an online appendix.
The University of Kansas
2012-06-21 16:10:38
Peer-reviewed Article
application/pdf
application/octet-stream
https://journals.ku.edu/jbi/article/view/4326
Biodiversity Informatics; Vol. 8 (2012)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4611
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"140327 2014 eng "
1546-9735
10.17161/bi.v9i1.4611
doi
dc
Character Selection During Interactive Taxonomic Identification: “Best Characters”
Talent, Nadia
Royal Ontario Museum http://www.cs.toronto.edu/~ntalent/index.html
Dickinson, Richard B.
Dickinson, Timothy A.
Royal Ontario Museum
Software interfaces for interactive multiple-entry taxonomic identification (polyclaves) sometimes provide a “best character” or “separation” coefficient, to guide the user to choose a character that could most effectively reduce the number of identification steps required. The coefficient could be particularly helpful when difficult or expensive tasks are needed for forensic identification, and in very large databases, uses that appear likely to increase in importance. Several current systems also provide tools to develop taxonomies or single-entry identification keys, with a variety of coefficients that are appropriate to that purpose. For the identification task, however, information theory neatly applies, and provides the most appropriate coefficient. To our knowledge, Delta-Intkey is the only currently available system that uses a coefficient related to information theory, and it is currently being reimplemented, which may allow for improvement. We describe two improvements to the algorithm used by Delta-Intkey. The first improves transparency as the number of remaining taxa decreases, by normalizing the range of the coefficient to [0,1]. The second concerns numeric ranges, which require consistent treatment of sub-intervals and their end-points. A stand-alone Bestchar program for categorical data is provided, in the Python and R languages. The source code is freely available and dedicated to the Public Domain.
The University of Kansas
2014-03-27 16:44:38
Peer-reviewed Article
application/pdf
text/plain
https://journals.ku.edu/jbi/article/view/4611
Biodiversity Informatics; Vol. 9 (2014)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4717
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"140604 2014 eng "
1546-9735
10.17161/bi.v9i1.4717
doi
dc
PointSampler: A GIS Tool for Point Intercept Sampling of Digital Images
Gobbett, David Lyon
CSIRO Ecosystem Sciences / Sustainable Agriculture Flagship http://www.csiro.au/people/David.Gobbett.html
Zerger, Andre
Environmental Information Services, Bureau of Meteorology
Close-range digital photography to assess vegetation cover is useful in disciplines ranging from ecological monitoring to agricultural research. An on-screen point intercept sampling method, which is analogous to the equivalent field based method, can be used to manually derive the percentage occurrence of multiple cover classes within an image. PointSampler is a GIS embedded tool that provides a semi-automated approach for performing point intercept sampling of digital images, and which integrates with existing GIS functionality and workflows. We describe and illustrate the two general applications of this tool, in in efficiently deriving primary ecological data from digital photographs , and for the generation of validation data to complement automated image classification of a time series of groundcover images. The flexible design and GIS integration of PointSampler allows it to be put to a wide range of similar uses.
The University of Kansas
2014-03-27 16:44:38
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4717
Biodiversity Informatics; Vol. 9 (2014)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4748
2018-01-12T01:58:47Z
jbi:ART
nmb a2200000Iu 4500
"141205 2014 eng "
1546-9735
10.17161/bi.v9i1.4748
doi
dc
DigiWeb - a workflow environment for quality assurance of transcription in digitization of natural history collections
Mononen, Tero
University of Eastern Finland http://www.digitarium.fi
Tegelberg, Riitta
University of Eastern Finland http://www.digitarium.fi
Sääskilahti, Mira
University of Eastern Finland http://www.digitarium.fi
Huttunen, Markku A.
University of Eastern Finland http://www.digitarium.fi
Tähtinen, Marko
University of Eastern Finland http://www.digitarium.fi
Saarenmaa, Hannu
University of Eastern Finland
Data produced by digitization increases the scientific use of natural history collections. However, in mass digitization, attention must be paid to the flawless management of the workflows, and high quantities of end results should not be compromised by a low standard of quality. A web-based environment DigiWeb was created for controlling the workflow of transcribing data from images of natural history specimens. Using DigiWeb, it was possible to manage the workflow of transcription and data proofing, include all participants to the workflow, allow collaboration and training, and also to provide useful processing features. The data emerging from this process passes quality control standards which are supported by DigiWeb and based on the strict requirements of the ISO 2859 standard.
The University of Kansas
2014-03-27 16:44:38
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4748
Biodiversity Informatics; Vol. 9 (2014)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4801
2018-01-12T01:59:02Z
jbi:ART
nmb a2200000Iu 4500
"150904 2015 eng "
1546-9735
10.17161/bi.v10i0.4801
doi
dc
Indices of Biodiversity Pattern Based on Presence-Absence Matrices: A GIS Implementation
Soberon, Jorge
University of Kansas
Cavner, Jeff
Biodiversity Institute, University of Kansas
In this work we present mathematical notation and formulae relating a number of indices of the biodiversity pattern of an aggregate of species, and an Open Source implementation of them as a plug-in for the increasingly popular Open Source geographical information system Quantum GIS. We provide detailed formulae relating three indices of beta diversity, two of pattern of nestedness, one of checkerboard pattern, and two of ratios of variances. The above is done by deriving six vectors from the full presence-absence matrix. Our GIS implementation is done via Web Services, tapping the LifeMapper platform for calculating potential species distributions.
The University of Kansas
2015-08-23 11:52:52
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4801
Biodiversity Informatics; Vol. 10 (2015)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4853
2018-01-12T01:59:02Z
jbi:ART
nmb a2200000Iu 4500
"150904 2015 eng "
1546-9735
10.17161/bi.v10i0.4853
doi
dc
OMWS: A Web Service Interface for Ecological Niche Modelling
Giovanni, Renato De
Centro de Referência em Informação Ambiental, CRIA
Torres, Erik
Universitat Politècnica de València
Amaral, Rafael Burlamaqui
Universidade Federal Fluminense
Blanquer, Ignacio
Universitat Politècnica de València
Rebello, Vinod
Universidade Federal Fluminense
Canhos, Vanderlei Perez
Centro de Referência em Informação Ambiental, CRIA
Ecological niche modelling (ENM) experiments often involve a high number of tasks to be performed. Such tasks may consume a significant amount of computing resources and take a long time to complete, especially when using personal computers. OMWS is a Web service interface that allows more powerful computing back-ends to be remotely exploited by other applications to carry out ENM tasks. Its latest version includes a new operation that can be used to specify complex workflows in a single request, adding the possibility of using workflow management systems on parallel computing back-end. In this paper we describe the OMWS protocol and compare its most recent version with the previous one by running the same ENM experiment using two functionally equivalent clients, each designed for one of the OMWS interface versions. Different back-end configurations were used to investigate how the performance scales for each protocol version when more processing power is made available. Results show that the new version outperforms (in a factor of 2) the previous one when more computing resources are used.
The University of Kansas
2015-08-23 11:52:52
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4853
Biodiversity Informatics; Vol. 10 (2015)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4914
2019-01-31T23:33:25Z
jbi:BD
nmb a2200000Iu 4500
"150921 2015 eng "
1546-9735
10.17161/bi.v10i2.4914
doi
dc
DIVERSITY OF WILD PALMS (ARECACEAE) IN THE REPUBLIC OF BENIN: FINDING THE GAPS IN THE NATIONAL INVENTORY COMBINING FIELD AND DIGITAL ACCESSIBLE KNOWLEDGE
Idohou, Rodrigue
Laboratory of Biomathematics and Forest Estimations
Arino, Arturo
Department of Environmental Biology, University of Navarra, Pamplona, Spain
Assogbadjo, Achille
Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, Benin
Glele Kakai, Romain
Laboratory of Biomathematics and Forest Estimations, University of Abomey-Calavi, Benin
Sinsin, Brice
Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, Benin
Despite many efforts by researchers worldwide to assess the biodiversity of plant groups, many locations on Earth remain not well surveyed and data-deprivation biases often occur. Robust estimates of inventory completeness could help alleviate the problem. This study aimed at identifying areas representing gaps in current knowledge of African palms, with a focus on Benin (West Africa). We assessed the completeness of knowledge of African palms targeting geographical distance and climatic difference from well-known sites. Data derived from intensive fieldwork were combined with independent data available online. Completeness inventory indices were calculated and coupled with other criteria to decide on the extent of knowledge. Results showed a high overall value for inventory completeness, as well as an even distribution of well-known areas across the country. However, poorly-known areas were distinctly identified and correlated to remote locations with low accessibility. This study illustrates how biodiversity survey and inventory efforts can be guided by existing knowledge. We strongly recommend the combination of digital accessible knowledge and fieldwork, coupled with expert knowledge, to obtain a better picture of the completeness of the inventory in tropical ecosystems.
The University of Kansas
2015-09-21 11:06:08
Peer-reviewed paper
application/pdf
https://journals.ku.edu/jbi/article/view/4914
Biodiversity Informatics; Vol. 10 No. 2 (2015): National Biodiversity Diagnoses
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4955
2018-01-12T01:59:02Z
jbi:ART
nmb a2200000Iu 4500
"150823 2015 eng "
1546-9735
10.17161/bi.v10i0.4955
doi
dc
EcoClimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers
Lima-Ribeiro, Matheus Souza
UFG
Varela, Sara
González-Hernández, Javier
de Oliveira, Guilherme
Diniz-Filho, José Alexandre F.
Terribile, Levi Carina
Studies in biogeography and macroecology have been increasing massively since climate and biodiversity databases became easily accessible. Climate simulations for past, present, and future have enabled macroecologists and biogeographers to combine data on species’ occurrences with detailed information on climatic conditions through time to predict biological responses across large spatial and temporal scales. Here we present and describe ecoClimate, a free and open data repository developed to serve useful climate data to macroecologists and biogeographers. ecoClimate arose from the need for climate layers with which to build ecological niche models and test macroecological and biogeographic hypotheses in the past, present, and future. ecoClimate offers a suite of processed, multi-temporal climate data sets from the most recent multi-model ensembles developed by the Coupled Modeling Intercomparison Projects (CMIP5) and Paleoclimate Modeling Intercomparison Projects (PMIP3) across past, present, and future time frames, at global extents and 0.5° spatial resolution, in convenient formats for analysis and manipulation. A priority of ecoClimate is consistency across these diverse data, but retaining information on uncertainties among model predictions. The ecoClimate research group intends to maintain the web repository updated continuously as new model outputs become available, as well as software that makes our workflows broadly accessible.
The University of Kansas
2015-08-23 11:52:52
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/4955
Biodiversity Informatics; Vol. 10 (2015)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/4959
2018-01-12T01:59:02Z
jbi:BD
nmb a2200000Iu 4500
"160715 2016 eng "
1546-9735
10.17161/bi.v11i1.4959
doi
dc
Digital Knowledge of Kenyan Succulent Flora and Priorities for Future Inventory and Documentation
Wabuyele, Emily
Kang’ethe, Simon
Newton, Leonard E.
Biodiversity inventory in Kenya has been ongoing for about a century and a half, coinciding with the arrival of naturalists from Europe, America, and elsewhere outside Africa. Since the first collections in the mid-to-late 1800s, there has been a steady increase of plant surveys, frequency of inventory, and discovery of new species that have considerably increased knowledge of faunal and floristic elements. However, as in all other countries, such historical biological collection activities are more often than not, ad hoc, resulting in gaps in knowledge of species and their habitats. While Kenya is relatively rich botanically, with a succulent flora of about 428 taxa, it is apparent that the list is understated owing to, among other factors, difficulty of preparing herbarium material and restricted access to some sites. This study investigated completeness of geographic knowledge of succulent plants in Kenya, with the aim of establishing species distribution patterns and identifying gaps that will guide and justify priority setting for future work on the group. Species data were filtered from the general BRAHMS database at the East African Herbarium and cleaned via an iterative series of inspections and visualizations designed to detect and document inconsistencies in taxonomic concepts, geographic coordinates, and dates of collection. Eight grid squares fulfilled criteria for completeness of inventory: one in the city of Mombasa, one in the Kulal–Nyiro complex, one in Garissa, one in Baringo, and four grid squares in the Nairobi–Nakuru–Laikipia area. Poorly-known areas, mostly in the west, north, and north-eastern regions of the country, were extremely isolated from well-known sites, both geographically and environmentally. These localities should be prioritised for future inventory as they are likely to yield species new to science, species new to the national flora, and/or contribute new knowledge on habitats. To avoid inconsistencies and data leakage, biodiversity inventory and documentation needs streamlining to generate standardised metadata that should be digitised to enhance access and synthesis.
The University of Kansas
2016-03-01 00:00:00
Peer-reviewed paper
application/pdf
https://journals.ku.edu/jbi/article/view/4959
Biodiversity Informatics; Vol. 11 No. 1 (2016)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/5007
2019-01-31T23:34:16Z
jbi:BD
nmb a2200000Iu 4500
"151003 2015 eng "
1546-9735
10.17161/bi.v10i2.5007
doi
dc
THE PRESENT STATE OF BOTANICAL INVESTIGATIONS IN CÔTE D’IVOIRE
KOFFI, Kouao Jean
University Nangui Abrougoua
KOUASSI, Akossoua Faustine
ADOU YAO, Constant Yves
BAKAYOKO, Adama
IPOU, Ipou Joseph
BOGAERT, Jan
The aim of this present study is to summarize the current state of research on the flora of the Côte d’Ivoire from the SIG IVOIRE database to better direct future collection efforts. Herbarium specimen data used for this study covered the period from 1894 to 2000, and were assembled by 226 collectors. This database comprises 15,228 samples, grouped in 3621 species, 1371 genera, and 198 families. A grid system was used to cover the Ivorian territory at spatial resolution of 0.75° x 0.75°. Indices of evenness and completeness were calculated to characterize sampling and identify floristically well-known regions. The exploration of the Ivorian territory is far from uniform, such that some areas were more densely surveyed, but others partially or not at all. The regions of Grands Ponts, Agnéby-Tiassa, Loh-Djiboua, part of Gbèkè, Boukani, San Pedro and Cavally were floristically well known; environmentally, the largest gaps in coverge were in the mountains in western Côte d'Ivoire.
The University of Kansas
2015-09-21 11:06:08
Peer-reviewed paper
application/pdf
https://journals.ku.edu/jbi/article/view/5007
Biodiversity Informatics; Vol. 10 No. 2 (2015): National Biodiversity Diagnoses
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/5008
2018-01-12T01:59:02Z
jbi:TM
nmb a2200000Iu 4500
"160301 2016 eng "
1546-9735
10.17161/bi.v11i1.5008
doi
dc
Biodiversity Informatics Training Curriculum, version 1.2
Peterson, A. Townsend
University of Kansas http://orcid.org/0000-0003-0243-2379
Ingenloff, Kate
University of Kansas
The Biodiversity Informatics Training Curriculum represents an integration of three years of teaching and interaction by many instructors and students in a series of interactions in courses across Africa. Digital videos of these courses--shared openly via YouTube--have been compiled into a first field-wide curriculum, which is presented herein. The compilation is, in effect, a digital textbook covering the entire field of biodiversity informatics.
The University of Kansas
2016-03-01 00:00:00
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/5008
Biodiversity Informatics; Vol. 11 No. 1 (2016)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/5053
2018-01-12T01:59:02Z
jbi:BD
nmb a2200000Iu 4500
"160715 2016 eng "
1546-9735
10.17161/bi.v11i1.5053
doi
dc
Completeness of Digital Accessible Knowledge of Plants of Benin and Priorities for Future Inventory and Data Discovery
Ganglo, Jean Cossi
University of Abomey-Calavi. Faculty of Agricultural Sciences. Benin, West Africa
Kakpo, Sunday Berlioz
University Of Abomey-Calavi. Faculty of Agricultural Sciences. Bénin, West Africa
Discovery of and access to primary biodiversity data are critical components in informed decision-making regarding sustainable use of biological resources and conservation of biodiversity. Primary biodiversity data are increasingly available from Benin, but information about completeness of this information across the country is still lacking for most groups. This study analyzed the Digital Accessible Knowledge regarding the plants of Benin to identify gaps in both geographic and environmental dimensions. Many gaps exist in plant data for Benin, particularly in the northern most departments; central and southern Benin are better known, but some gaps remain even there. The resulting view of Beninese Digital Accessible Knowledge can guide future inventory and data discovery efforts.
The University of Kansas
2016-03-01 00:00:00
Peer-reviewed paper
application/pdf
https://journals.ku.edu/jbi/article/view/5053
Biodiversity Informatics; Vol. 11 No. 1 (2016)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/5860
2018-01-12T01:59:02Z
jbi:BD
nmb a2200000Iu 4500
"160610 2016 eng "
1546-9735
10.17161/bi.v11i1.5860
doi
dc
Completeness of Digital Accessible Knowledge of the Plants of Ghana
Asase, Alex
University of Ghana
Peterson, A. Townsend
University of Kansas http://orcid.org/0000-0003-0243-2379
Providing comprehensive, informative, primary, research-grade biodiversity information represents an important focus of biodiversity informatics initiatives. Recent efforts within Ghana have digitized >90% of primary biodiversity data records associated with specimen sheets in Ghanaian herbaria; additional herbarium data are available from other institutions via biodiversity informatics initiatives such as the Global Biodiversity Information Facility. However, data on the plants of Ghana have not as yet been integrated and assessed to establish how complete site inventories are, so that appropriate levels of confidence can be applied. In this study, we assessed inventory completeness and identified gaps in current Digital Accessible Knowledge (DAK) of the plants of Ghana, to prioritize areas for future surveys and inventories. We evaluated the completeness of inventories at ½° spatial resolution using statistics that summarize inventory completeness, and characterized gaps in coverage in terms of geographic distance and climatic difference from well-documented sites across the country. The southwestern and southeastern parts of the country held many well-known grid cells; the largest spatial gaps were found in central and northern parts of the country. Climatic difference showed contrasting patterns, with a dramatic gap in coverage in central-northern Ghana. This study provides a detailed case study of how to prioritize for new botanical surveys and inventories based on existing DAK.
The University of Kansas
2016-03-01 00:00:00
Peer-reviewed paper
application/pdf
https://journals.ku.edu/jbi/article/view/5860
Biodiversity Informatics; Vol. 11 No. 1 (2016)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/5886
2018-01-12T01:59:02Z
jbi:ART
nmb a2200000Iu 4500
"161014 2016 eng "
1546-9735
10.17161/bi.v11i1.5886
doi
dc
Rescuing and Sharing Historical Vegetation Data for Ecological Analysis: The California Vegetation Type Mapping Project
Kelly, Maggi
UC Berkeley http://kellylab.berkeley.edu/ http://orcid.org/0000-0002-0198-2822
Research efforts that synthesize historical and contemporary ecological data with modeling approaches improve our understanding of the complex response of species, communities, and landscapes to changing biophysical conditions through time and in space. Historical ecological data are particularly important in this respect. There are remaining barriers that limit such data synthesis, and technological improvements that make multiple diverse datasets more readily available for integration and synthesis are needed. This paper presents one case study of the Wieslander Vegetation Type Mapping project in California and highlights the importance of rescuing, digitizing and sharing historical datasets. We review the varied ecological uses of the historical collection: the vegetation maps have been used to understand legacies of land use change and plan for the future; the plot data have been used to examine changes to chaparral and forest communities around the state and to predict community structure and shifts under a changing climate; the photographs have been used to understand changing vegetation structure; and the voucher specimens in combination with other specimen collections have been used for large scale distribution modeling efforts. The digitization and sharing of the data via the web has broadened the scope and scale of the types of analysis performed. Yet, additional research avenues can be pursued using multiple types of VTM data, and by linking VTM data with contemporary data. The digital VTM collection is an example of a data infrastructure that expands the potential of large scale research through the integration and synthesis of data drawn from numerous data sources; its journey from analog to digital is a cautionary tale of the importance of finding historical data, digitizing it with best practices, linking it with other datasets, and sharing it with the research community.
The University of Kansas
2016-03-01 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/5886
Biodiversity Informatics; Vol. 11 No. 1 (2016)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6507
2018-01-12T01:59:02Z
jbi:TM
nmb a2200000Iu 4500
"170603 2017 eng "
1546-9735
10.17161/bi.v12i0.6507
doi
dc
Introducción a los Análisis Espaciales con Énfasis en Modelos de Nicho Ecológico
Cuervo-Robayo, Angela P.
Escobar, Luis E
Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota http://ecoguate2003.wix.com/escobar
Osorio-Olvera, Luis A.
Nori, Javier
Varela, Sara
Martinez-Meyer, Enrique
Velasquez-Tibata, Jorge
Rodriguez-Soto, Clarita
Munguia, Mariana
Castaneda-Alvarez, Nora P.
Lira-Noriega, Andres
Soley-Guardia, Mariano
Serra-Diaz, Josep M.
Peterson, A. Townsend
En 2016 implementamos un sistema de seminarios de enseñanza, en formato de videos libres y accesibles desde internet, con la finalidad de dar a conocer de forma sencilla y en castellano, las bases conceptuales y aplicaciones de los modelos de nicho ecológico en estudios de ecología, conservación biológica, epidemiología y agrobiodviersidad, así como su implementación para el diseño de políticas públicas de los recursos naturales. Cada seminario fue desarrollado por uno o varios expertos discutiendo conceptos, métodos y diferentes herramientas disponibles para elaborar modelos de distribución de especies. Este manuscrito reúne los resúmenes de cada uno de los seminarios en línea, dando referencias clave para cada tema y el enlace al video correspondiente. Los videos están disponibles de forma libre en YouTube o en formato .mp4 bajo solicitud.
The University of Kansas
2017-06-03 00:36:21
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/6507
Biodiversity Informatics; Vol. 12 (2017)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6522
2018-01-12T01:59:02Z
jbi:ART
nmb a2200000Iu 4500
"170603 2017 eng "
1546-9735
10.17161/bi.v12i0.6522
doi
dc
IRMNG 2006–2016: 10 Years of a Global Taxonomic Database
Rees, Tony
Private http://orcid.org/0000-0003-1887-5211
Vandepitte, Leen
Flanders Marine Institute
Decock, Wim
Flanders Marine Institute
Vanhoorne, Bart
Flanders Marine Institute
IRMNG, the Interim Register of Marine and Nonmarine Genera, was commenced in 2006 as an initiative of the Australian OBIS Node (OBIS Australia) following an analysis of the taxonomic names management needs of the Ocean Biogeographic Information System (OBIS). The main objectives were to produce a hierarchical classification of all life, both extant and fossil, to at least generic level (and to species as data were readily available) and to provide a tool to distinguish marine from nonmarine, and extant from fossil taxa. Over its first 10 years of operation IRMNG has acquired almost 487,000 of an estimated 510,000 published genus names (including both valid names and synonyms) in addition to almost 1.8 million species names, of which 1.3 million are considered valid. Throughout this time IRMNG data have been available for public query via a dedicated web interface based at CSIRO in Australia, as well as being supplied as bulk downloads for use by a range of global biodiversity projects. Over the period 2014-2016 responsibility for the system has been passed to the Data Centre Division of the Flanders Marine Institute (VLIZ) in Belgium, which is continuing the maintenance and development of IRMNG at its new web location, www.irmng.org. With its present estimated holdings of >95% of all published genus names (plus associated authorities and years of publication) across all taxonomic domains, including fossil as well as extant taxa, within an internally consistent taxonomic hierarchy, IRMNG is at present uniquely placed to provide an overview of “all life” to at least generic level, to permit the discovery of trends in publication of genera through time, to provide preliminary information on the marine vs. nonmarine and extant vs. fossil status of the taxa concerned, and to generate lists of both unique and non-unique names (homonyms sensu lato) for the benefit of users of biodiversity data.
The University of Kansas
2017-06-03 00:36:21
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/6522
Biodiversity Informatics; Vol. 12 (2017)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6646
2020-01-11T17:02:26Z
jbi:ART
nmb a2200000Iu 4500
"171114 2017 eng "
1546-9735
10.17161/bi.v12i0.6646
doi
dc
Crowdsourcing Natural History Archives: Tools for Extracting Transcriptions and Data
Mika, Katherine A.
Harvard University, Museum of Comparative Zoology, Ernst Mayr Library http://orcid.org/0000-0002-8839-0503
De Veer, Joseph
Rinaldo, Constance
This paper is a survey of the landscape of current, successful, and innovative platforms for extracting full text transcriptions and structured data using crowdsourcing as a tool. Archival manuscript items are the key case studies reviewed to develop a set of tools for the Biodiversity Heritage Library for use in enhancing access to and extraction information from items in scientific and natural history collections.
The University of Kansas
2017-06-03 00:36:21
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/6646
Biodiversity Informatics; Vol. 12 (2017)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6707
2020-01-11T17:01:32Z
jbi:ART
nmb a2200000Iu 4500
"171116 2017 eng "
1546-9735
10.17161/bi.v12i0.6707
doi
dc
Botanical Sampling Gaps Across the Cameroon Mountains
Sainge, Moses Nsanyi
Tropical Plant Exploration Group (TroPEG) Cameroon
Onana, Jean-Michel
Nchu, Felix
Kenfack, David
Peterson, A. Townsend
With the emergence of a new field, biodiversity informatics, an important task has been to evaluate completeness of biodiversity information that is existing and available for various countries and regions. This paper offers a first and very basic assessment of sampling gaps and inventory completeness across the Cameroon Mountains. Because digital accessible knowledge is severely limited for the region, we relied on qualitative evaluations of inventory completeness, supplemented by large amounts of data from the National Herbarium of Cameroon (YA) database. Detailed botanical inventories have been developed for Mt Cameroon, the Kupe-Mwanenguba Mountains, Mt Oku, and the Mambila Plateau, leaving substantial geographic and environmental coverage gaps corresponding to Rumpi Hills, Mt Nlonako, Kimbi Fungom National Park, Bali and Bafut Ngemba, Mt Bamboutos, Kagwene, and Tchabal Mbabo. This paper provides a roadmap for a comprehensive botanical survey for this region. Completing this survey plan, the resulting data will allow researchers to track changes in biodiversity and identify priority areas for conservation on the various mountain ranges that make up this important biodiversity hotspot.
The University of Kansas
2017-06-03 00:36:21
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/6707
Biodiversity Informatics; Vol. 12 (2017)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6744
2020-01-11T16:59:38Z
jbi:ART
nmb a2200000Iu 4500
"180206 2018 eng "
1546-9735
10.17161/bi.v13i0.6744
doi
dc
A metric to quantify analogous conditions and rank environmental layers
Lowenberg Neto, Peter
Analogous conditions in environmental variables are expected because environments are spatially autocorrelated and often present similar combinations over geographic space. That similar environmental combinations may be found at different localities provides a crucial basis for correlative species distribution modeling. An absolutely analogous variable is constant, while a non-analogous variable has no-repeating values, yet no current method allows researchers to quantify intermediate degrees of analogous conditions and rank environmental layers. I approached this issue from the perspective of dual-space correspondence, in which (a) variable range and modal frequency have a theoretical inverse relationship (y ∝ x-1), and (b) modal values of frequency are limited by the number of pixels in a given raster layer. For two geographic extents and two resolutions (2.5’ and 10’), I obtained range and modal frequency of 19 bioclimatic variables and 5 reference variables. Then, I measured Euclidean distances from candidate variables to the non-analogous variable as a metric for degree of analogous conditions, which were used to rank variables. Bioclimatic layers were plotted in log-log scatterplots of range vs. modal frequency; variables were located inside the upper-right triangle (except for one set), and no layer fit the inverse model. Temperature variables presented higher degrees of analogous conditions than precipitation for South America and the Araucaria Moist Forests ecoregion. Geographic extent and pixel resolution changed the degree of analogous conditions of derived variables (quarterly and monthly); however, a pattern of change was not observed, which suggested ad hoc hypotheses on geographic and temporal idiosyncrasies. Variables with high contribution in previous SDM/ENM studies (e.g., temperature seasonality and annual precipitation) showed low degree of analogous conditions. It is expected that heterogeneous layers would generate better correlational geographic distributional predictions than analogous variables, even though this hypothesis remains untested. Ranking layers can provide grounds for selecting variables in distribution and niche modeling, particularly as regards interpreting spatial projection and transferability. Alternatively, ranking can be used to compare degrees of analogous conditions of the same layer in different time spans.
The University of Kansas
2018-02-02 11:20:50
Peer-reviewed Article
application/pdf
application/pdf
https://journals.ku.edu/jbi/article/view/6744
Biodiversity Informatics; Vol. 13 (2018)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/6975
2020-01-11T17:00:32Z
jbi:ART
nmb a2200000Iu 4500
"180202 2018 eng "
1546-9735
10.17161/bi.v13i0.6975
doi
dc
An open-access platform for camera-trapping data
Lavariega, Mario César
Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional, Unidad Oaxaca, Instituto Politécnico Nacional
In southern Mexico, local communities have been playing important roles in the design and collection of wildlife data through camera-trapping in community-based monitoring of biodiversity projects. However, the methods used to store the data have limited their use in matters of decision-making and research. Thus, we present the Platform for Community-based Monitoring of Biodiversity (PCMB), a repository, which allows storage, visualization, and downloading of photographs captured by community-based monitoring of biodiversity projects in protected areas of southern Mexico. The platform was developed using agile software development with extensive interaction between computer scientists and biologists. System development included gathering data, design, built, database and attributes creation, and quality control. The PCMB currently contains 28,180 images of 6478 animals (69.4% mammals and 30.3% birds). Of the 32 species of mammals recorded in 18 PA since 2012, approximately a quarter of all photographs were of white-tailed deer (Odocoileus virginianus). Platforms permitting access to camera-trapping data are a valuable step in opening access to data of biodiversity; the PCMB is a practical new tool for wildlife management and research with data generated through local participation. Thus, this work encourages research on the data generated through the community-based monitoring of biodiversity projects in protected areas, to provide an important information infrastructure for effective management and conservation of wildlife.
The University of Kansas
2018-02-02 11:20:50
Peer-reviewed Article
application/pdf
application/vnd.openxmlformats-officedocument.wordprocessingml.document
https://journals.ku.edu/jbi/article/view/6975
Biodiversity Informatics; Vol. 13 (2018)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/7036
2020-01-11T16:57:50Z
jbi:ART
nmb a2200000Iu 4500
"180719 2018 eng "
1546-9735
10.17161/bi.v13i0.7036
doi
dc
From theory to practice: a photographic inventory of museum collections to optimize collection management
Merckx, Jonas
Biodiversity Inventory for Conservation (BINCO)
Van Roie, Martijn
Biodiversity Inventory for Conservation (BINCO)
University of Antwerp
Gómez-Zurita, Jesús
CSIC University
Dekoninck, Wouter
Royal Belgian Institute of Natural Sciences (RBINS)
The digitization of museum specimens is a key priority in the Digital Era. Digital databases help to avoid unnecessary manipulation hazards to delicate collections, increase their accessibility to third party researchers, and contribute to the ongoing documentation of global biodiversity. Time, workforce and the need of specialized infrastructures limit the processing of the vast number of specimens in natural history collections. Cheaper, easy-to-use methods and volunteer programs are developing quickly to help bridge the gap. We present the results of combining citizen science for the digitization of an entomological collection in conjunction with the cooperation of a taxonomic expert for the remote identification of samples. In addition, we provide an assessment of the avoided monetary costs and the time needed for each step of the process. A photographic inventory of specimens belonging to the leaf beetle genus Calligrapha was compiled by volunteers using a low-cost compact camera and the species were identified using these images. Using digital photographs allowed for a rapid screening of specimens in the collection and resulted in an updated taxonomic identification of the Calligrapha collection at the Royal Belgian Institute of Natural Sciences. The pictures of the specimens and their original labels, as well as the new information from this endeavor were placed in an online public catalogue. This study demonstrates a worked example of how digitization has led to a practical, useful outcome through cooperation with an end user and highlights the value of museum collection digitization projects.
The University of Kansas
2018-02-02 11:20:50
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/7036
Biodiversity Informatics; Vol. 13 (2018)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/7108
2020-01-11T16:58:46Z
jbi:ART
nmb a2200000Iu 4500
"180316 2018 eng "
1546-9735
10.17161/bi.v13i0.7108
doi
dc
Assessment of biodiversity data holdings and user data needs for Ghana
Asase, Alex
University of Ghana
Schwinger, Gladys O
Data on biodiversity are important to addressing the challenges of sustainable development, and for decision-making about natural resources and environments. Biodiversity information, when mobilized and shared openly, has the potential to impact science and conservation positively. However, biodiversity data mobilization is expensive, such that data mobilization and sharing activities must be prioritized to meet the needs of the user community. In this study, we undertook a detailed assessment of biodiversity data holdings and user needs in Ghana through semi-structured questionnaire interviews, and focus-group discussions in the form of a workshop. Most biodiversity data-holding organizations were at preliminary stages of digital biodiversity data mobilization and sharing. Taxonomic, checklist, and geographic data on plants and animals were identified as most needed. Priority thematic needs were as regards protected areas, invasive alien species, threatened species, economic species (timber and non-timber forest products), and pathogens and diseases. Human and infrastructural capacities, and sustainable coordination were identified as the major challenges to biodiversity data management. This study provides a detailed case study of how assessing biodiversity data holdings and user data needs can be used to strategize biodiversity data mobilization, data publication, and data use activities.
The University of Kansas
2018-02-02 11:20:50
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/7108
Biodiversity Informatics; Vol. 13 (2018)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/7600
2020-07-15T16:00:39Z
jbi:TM
nmb a2200000Iu 4500
"181024 2018 eng "
1546-9735
10.17161/bi.v13i0.7600
doi
dc
Sample data and training modules for cleaning biodiversity information
Cobos, Marlon E
University of Kansas
Jiménez, Laura
University of Kansas http://orcid.org/0000-0002-6683-9576
Nuñez-Penichet, Claudia
University of Kansas http://orcid.org/0000-0001-7442-8593
Romero-Alvarez, Daniel
University of Kansas
Simoes, Marianna
University of Kansas
Large-scale biodiversity databases have become crucial information sources in many analyses in biogeography, macroecology, and conservation biology, often involving development of empirical models of species’ ecological niches and predictions of their geographic distributions. These analyses, however, can be impaired by the presence of errors, particularly as regards taxonomic identifications and accurate geographic coordinates. Here, we present a detailed data-cleaning exercise based on two contrasting datasets; we link these example data with a step-by-step guide to overcoming these problems and improving data quality for analyses based on these data.
The University of Kansas
2018-02-02 11:20:50
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/7600
Biodiversity Informatics; Vol. 13 (2018)
eng
Copyright (c)
oai:ojs.pkp.sfu.ca:article/8189
2020-01-11T16:56:00Z
jbi:TM
nmb a2200000Iu 4500
"190502 2019 eng "
1546-9735
10.17161/bi.v14i0.8189
doi
dc
Curso Modelado de Nicho Ecológico, Version 1.0
Peterson, A. Townsend
University of Kansas
Anderson, Robert P
Department of Biology, City College of New York, City University of New York, 160 Convent Avenue, New York, NY 10031 USA; Doctoral Program in Biology, Graduate Center, City University of New York, 365 5th Avenue, New York, NY 10016 USA; American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024 USA
Cobos, Marlon E
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Cuahutle, Martín
Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Ciudad de México, C.P., México
Cuervo-Robayo, Angela P
Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Ciudad de México, C.P., México; Instituto de Biología, Universidad Nacional Autónoma de México, México City 04510, México
Escobar, Luis E
Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia 24061 USA
Fernández, Marc
Centre for Ecology, Evolution and Environmental Changes/Azorean Biodiversity Group, and Faculdade de Ciências e Tecnologia, Universidade dos Açores, Ponta Delgada, 9501-801, Portugal
Jiménez-García, Daniel
Centro de Agroecología y Ambiente, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla. Edif. Val1, Ecocampus-BUAP. Km 1.7 Carretera San Baltazar Tetela, San Pedro Zacachimalpa. C.P. 72960, Puebla, Puebla, México
Lira-Noriega, Andrés
Instituto de Ecología, A.C.; Carretera antigua a Coatepec No. 351, El Haya, 91070 Xalapa, Veracruz, México
Lobo, Jorge M
Dept. Biogeography and Global Change, National Museum of Natural Sciences, c/ José Gutiérrez Abascal, 2, 288006, Madrid, Spain
Machado-Stredel, Fernando
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Martínez-Meyer, Enrique
Instituto de Biología, Universidad Nacional Autónoma de México, México City 04510, México; Centro del Cambio Global y la Sustentabilidad en el Sureste AC, CP 86080, Villahermosa, Tabasco, Mexico
Nuñez-Penichet, Claudia
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Nori, Javier
Instituto de Diversidad y Ecología Animal (IDEA-CONICET) and Centro de Zoología Aplicada, Universidad Nacional de Córdoba,Córdoba, Argentina
Osorio-Olvera, Luis
Centro del Cambio Global y la Sustentabilidad en el Sureste AC, CP 86080, Villahermosa, Tabasco, Mexico
Rodríguez, María Teresa
Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), Ciudad de México, C.P., México
Rojas-Soto, Octavio
Instituto de Ecología, A.C.; Carretera antigua a Coatepec No. 351, El Haya, 91070 Xalapa, Veracruz, México
Romero-Álvarez, Daniel
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Soberón, Jorge
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Varela, Sara
Museum für Naturkunde Leibniz Institut für Evolutions und Biodiversitätsforschung. Invalidenstraße 43. D-10115 Berlin, Germany
Yañez-Arenas, Carlos
Laboratorio de Ecología Geográfica, Unidad de Biología de la Conservación, Parque Científico y Tecnológico de Yucatán, Facultad de Ciencias, Universidad Nacional Autónoma de México, 97302 Sierra Papacal, Yucatán, México
El conjunto de ideas, métodos y programas informáticos que se conoce como “Modelado de Nicho Ecológico” (MNE)—y el relacionado “Modelado de Distribución de Especies” (MDS)—han sido objeto de intensa exploración e investigación en las últimas décadas. A pesar de existir al menos cuatro síntesis publicadas, este campo ha crecido tanto en complejidad, que la formación de nuevos investigadores es difícil. Hasta ahora, dicha formación se ha hecho de manera presencial en cursos organizados por universidades o centros de investigación, de los que hemos formado parte como instructores. Sin embargo, el acceso a este tipo de cursos especializados es restringido, por un lado, porque los cursos no se ofrecen en todas las universidades, y por otro, porque normalmente se imparten en inglés. Para facilitar el acceso a una mayor comunidad de científicos de habla hispana, presentamos un curso en español, completamente digital y de acceso gratuito, que se realizó vía Internet durante 23 semanas consecutivas en 2018. Aunque las barreras intrínsecas al uso de Internet pueden dificultar la accesibilidad a los materiales del curso, hemos usado diversos formatos para la divulgación de los contenidos académicos (video, audio, pdf) con el objetivo de eliminar la mayor parte de estos problemas.
The University of Kansas
2019-05-03 09:24:22
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/8189
Biodiversity Informatics; Vol. 14 (2019)
spa
Copyright (c) 2019 A. Townsend Peterson, Robert P Anderson, Marlon E Cobos, Martín Cuahutle, Angela P Cuervo-Robayo, Luis E Escobar, Marc Fernández, Daniel Jiménez-García, Andrés Lira-Noriega, Jorge M Lobo, Fernando Machado-Stredel, Enrique Martínez-Meyer, Claudia Nuñez-Penichet, Javier Nori, Luis Osorio-Olvera, María Teresa Rodríguez, Octavio Rojas-Soto, Daniel Romero-Álvarez, Jorge Soberón, Sara Varela, Carlos Yañez-Arenas
oai:ojs.pkp.sfu.ca:article/9786
2020-01-11T16:55:05Z
jbi:ART
nmb a2200000Iu 4500
"190603 2019 eng "
1546-9735
10.17161/bi.v14i0.9786
doi
dc
climateStability: An R package to estimate climate stability from time-slice climatologies
Owens, Hannah Lois
Guralnick, Robert
As continental and global-scale paleoclimate model data become more readily available, biologists can now ask spatially explicit questions about the tempo and mode of past climate change and the impact of those changes on biodiversity patterns. In particular, researchers have focused on climate stability as a key variable that can drive expected patterns of richness, phylogenetic diversity and functional diversity. Yet, climate stability measures are not formalized in the literature and tools for generating stability metrics from existing data are nascent. Here we define “deviation” of a climate variable as the mean standard deviation between time slices over time elapsed; “stability” is defined as the inverse of this deviation. Finally, climate stability is the product of individual climate variable stability estimates. We also present an R package, climateStability, which contains tools for researchers to generate climate stability estimates from their own data.
The University of Kansas
2019-05-03 09:24:22
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/9786
Biodiversity Informatics; Vol. 14 (2019)
eng
Copyright (c) 2019 Hannah Lois Owens, Robert Guralnick
oai:ojs.pkp.sfu.ca:article/9798
2020-07-15T15:30:40Z
jbi:ART
nmb a2200000Iu 4500
"200131 2020 eng "
1546-9735
10.17161/bi.v15i1.9798
doi
dc
Co-occurrence Networks do not Support Identification of Biotic Interactions
Peterson, A. Townsend
University of Kansas
Soberón, Jorge
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Ramsey, Janine
Instituto Nacional de Salud Pública, Tapachula, Chiapas, México
Osorio-Olvera, Luis
Centro del Cambio Global y la Sustentabilidad en el Sureste AC, CP 86080, Villahermosa, Tabasco, Mexico
We assess a body of work that has attempted to use co-occurrence networks to infer the existence and type of biotic interactions between species. Although we see considerable interest in the approach as an exploratory tool for understanding patterns of co-occurrence of species, we note and describe numerous problems in the step of inferring biotic interactions from the co-occurrence patterns. These problems are both theoretical and empirical in nature, and limit confidence in inferences about interactions rather severely. We examine a series of examples that demonstrates striking discords between interactions inferred from co-occurrence patterns and previous experimental results and known life-history details.
The University of Kansas
2020-02-01 10:19:32
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/9798
Biodiversity Informatics; Vol. 15 No. 1 (2020): Debate: Ecological Interactions and Geographic Co-occurrence
eng
Copyright (c) 2020 A. Townsend Peterson, Jorge Soberón, Janine Ramsey, Luis Osorio-Olvera
oai:ojs.pkp.sfu.ca:article/9815
2020-07-15T15:29:58Z
jbi:ART
nmb a2200000Iu 4500
"200131 2020 eng "
1546-9735
10.17161/bi.v15i1.9815
doi
dc
Can Ecological Interactions be Inferred from Spatial Data?
Stephens, Christopher Rhodes
C3 Centro de Ciencias de la Complejidad,
Gonzalez-Salazar, Constantino
Villalobos, Maricarmen
Marquet, Pablo
The characterisation and quantication of ecological interactions, and the construction
of species distributions and their associated ecological niches, is of fundamental
theoretical and practical importance. In this paper we give an overview of a Bayesian
inference framework, developed over the last 10 years, which, using spatial data, offers
a general formalism within which ecological interactions may be characterised and
quantied. Interactions are identied through deviations of the spatial distribution
of co-occurrences of spatial variables relative to a benchmark for the non-interacting
system, and based on a statistical ensemble of spatial cells. The formalism allows for
the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate
on the conceptual and mathematical underpinnings of the formalism, showing
how, using the Naive Bayes approximation, it can be used to not only compare and
contrast the relative contribution from each variable, but also to construct species
distributions and niches based on arbitrary variable type. We show how the formalism
can be used to quantify confounding and therefore help disentangle the complex
causal chains that are present in ecosystems. We also show species distributions and
their associated niches can be used to infer standard "micro" ecological interactions,
such as predation and parasitism. We present several representative use cases that
validate our framework, both in terms of being consistent with present knowledge of
a set of known interactions, as well as making and validating predictions about new,
previously unknown interactions in the case of zoonoses.
The University of Kansas
2020-02-01 10:19:32
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/9815
Biodiversity Informatics; Vol. 15 No. 1 (2020): Debate: Ecological Interactions and Geographic Co-occurrence
eng
Copyright (c) 2020 Christopher Rhodes Stephens, Constantino Gonzalez-Salazar, Maricarmen Villalobos, Pablo Marquet
oai:ojs.pkp.sfu.ca:article/11989
2020-11-18T00:22:08Z
jbi:ART
nmb a2200000Iu 4500
"201117 2020 eng "
1546-9735
10.17161/bi.v15i3.11989
doi
dc
Weighing the Evidence for the Abundant-Center Hypothesis
Dallas, Tad A.
Department of Biological Sciences, Louisiana State University, Baton Rouge, USA
Santini, Luca
Department of Environmental Science, Institute for Wetland and Water Research, Faculty of Science, Radboud University, The Netherlands
Decker, Robin
Department of Integrative Biology, University of Texas, Austin, USA
Hastings, Alan
Department of Environmental Science and Policy, University of California, Davis, USA
The abundant-center hypothesis posits that species density should be highest in the center of the geographic range or climatic niche of a species, based on the idea that the center of either will be the area with the highest demographic performance (e.g., greater fecundity, survival, or carrying capacity). While intuitive, current support for the hypothesis is quite mixed. Here, we discuss the current state of the abundant-center hypothesis, highlighting the relatively low level of support for the relationship. We then discuss the potential reasons for this lack of empirical support, emphasizing the inherent ecological complexity which may prevent the observation of the abundant-center in natural systems. This includes the role of non-equilibrial population dynamics, species interactions, landscape structure, and dispersal processes, as well as variable data quality and inconsistent methodology. The incorporation of this complexity into studies of the distribution of species densities in geographic or niche space may underlie the limited empirical support for the abundant-center hypothesis. We end by discussing potentially fruitful research avenues. Most notably, we highlight the need for theoretical development and controlled experimental testing of the abundant-center hypothesis.
The University of Kansas
2020-11-17 18:22:07
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/11989
Biodiversity Informatics; Vol. 15 No. 3 (2020): Niche-centroid
eng
Copyright (c) 2020 Tad A. Dallas, Luca Santini, Robin Decker, Alan Hastings
oai:ojs.pkp.sfu.ca:article/12060
2020-07-15T15:34:50Z
jbi:ART
nmb a2200000Iu 4500
"200131 2020 eng "
1546-9735
10.17161/bi.v15i1.12060
doi
dc
Response to Stephens et al. (2019)
Peterson, A. Townsend
University of Kansas
Soberón, Jorge
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Ramsey, Janine
Instituto Nacional de Salud Pública, Tapachula, Chiapas, México
Osorio-Olvera, Luis
Centro del Cambio Global y la Sustentabilidad en el Sureste AC, CP 86080, Villahermosa, Tabasco, Mexico
Rebuttal to Stephens et al. (2019), as part of a debate format.
The University of Kansas
2020-02-01 10:19:32
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/12060
Biodiversity Informatics; Vol. 15 No. 1 (2020): Debate: Ecological Interactions and Geographic Co-occurrence
eng
Copyright (c) 2020 A. Townsend Peterson, Jorge Soberón, Janine Ramsey, Luis Osorio-Olvera
oai:ojs.pkp.sfu.ca:article/13218
2020-11-18T00:22:07Z
jbi:ART
nmb a2200000Iu 4500
"201117 2020 eng "
1546-9735
10.17161/bi.v15i2.13218
doi
dc
The Abundant Niche-centroid Hypothesis: Key Points About Unfilled Niches and the Potential Use of Supraspecfic Modeling Units
Yañez, Carlos
UNAM
Martín, Gerardo
MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, UK
Osorio-Olvera, Luis
Biodiversity Institute, University of Kansas, Lawrence, USA
Escobar-Luján, Jazmín
Laboratorio de Ecología Geográfica, Unidad de Biología de la Conservación, Parque Científico y Tecnológico de Yucatán, Universidad Nacional Autónoma de México, Sierra Papacal, Yucatán, México
Castaño-Quintero, Sandra
Laboratorio de Ecología Geográfica, Unidad de Biología de la Conservación, Parque Científico y Tecnológico de Yucatán, Universidad Nacional Autónoma de México, Sierra Papacal, Yucatán, México
Chiappa-Carrara, Xavier
Laboratorio de Ecología Geográfica, Unidad de Biología de la Conservación, Parque Científico y Tecnológico de Yucatán, Universidad Nacional Autónoma de México, Sierra Papacal, Yucatán, México.
Martínez-Meyer, Enrique
Departmento de Zoología, Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Mexico City, México
Correlative estimates of fundamental niches are gaining momentum as an alternative to predict species’ abundances, particularly via the abundant niche-centroid hypothesis (an expected inverse relationship between species’ abundance variation across its range and the distance to the geometric centroid of its multidimensional ecological niche). The main goal of this review is to recapitulate what has been done, where we are now, and where should we move towards in regards to this hypothesis. Despite evidence in support of the abundance-distance to niche centroid relationship, its usefulness has been highly debated, although with little consideration of the underlying theory regarding the circumstances that might break down the relationship. We address some key points about the conditions needed to test the hypothesis in correlative studies, specifically in relation to niche
characterization and configurations of the Biotic-Abiotic-Mobility (BAM) framework to illustrate the problem of unfilled niches. Using a created supraspecific modeling unit, we show that species for which only a portion of their fundamental niche is represented in their area of historical accessibility (M)—i.e., when the environmental equilibrium condition is violated—it is impossible to characterize their true niche centroid. Therefore, we strongly recommend to analyze this assumption prior to
assess the abundant niche-centroid hypothesis. Finally, we discuss the potential of using modeling units above the species level for cases in which environmental conditions associated with species’ occurrences may not be sufficient to fully characterize their fundamental niches.
The University of Kansas
2020-11-17 18:22:07
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/13218
Biodiversity Informatics; Vol. 15 No. 3 (2020): Niche-centroid
eng
Copyright (c) 2020 Carlos Yañez, Gerardo Martín, Luis Osorio-Olvera, Jazmín Escobar-Luján, Sandra Castaño-Quintero, Xavier Chiappa-Carrara, Enrique Martínez-Meyer
oai:ojs.pkp.sfu.ca:article/13302
2020-07-15T15:28:07Z
jbi:ART
nmb a2200000Iu 4500
"200131 2020 eng "
1546-9735
10.17161/bi.v15i1.13302
doi
dc
Some thoughts about the challenge of inferring ecological interactions from spatial data.
Holt, Robert D.
University of Florida
Dr. Luis Escobar asked me to provide a joint review of the submissions by Stephens et al. (2019, this issue) and Peterson et al. (2019, this issue). I pulled thoughts together, but by the time I sent them along, he had received other reviews and made an editorial decision. He felt my perspective might nevertheless warrant publishing as a commentary alongside these two pieces. My review was of the original submissions, which are now appearing with minor, mainly cosmetic changes. I have only lightly edited the text of my review, and added a few additional thoughts and pertinent references. Neither group of authors has seen my commentary, and so I am responsible for any omissions or lapses in interpretation. The protocol developed by Stephens seems to me a potentially valuable exploratory tool in describing patterns of co-occurrence, but I note several potential problems in identifying interactions usingsolely this protocol. I also gently disagree with Peterson et al., who state flatly that co-occurrence data can shed no light at all on interspecific interactions. I suggest there are a number of counter-examples to this claim in the literature. I argue that spatiotemporal data, when available, iprovide a much more powerful tool for discerning interactions, than do staticspatial data. Finally, I use a simple thought experiment to point out that biotic drivers could be playing a key causal role in limitnig distributions, even in equisitlvely accurate SDMs that use only abiotic (scenopoetic) data as input data.
The University of Kansas
2020-02-01 10:19:32
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/13302
Biodiversity Informatics; Vol. 15 No. 1 (2020): Debate: Ecological Interactions and Geographic Co-occurrence
eng
Copyright (c) 2020 Robert D. Holt
oai:ojs.pkp.sfu.ca:article/13376
2020-07-20T14:28:49Z
jbi:TM
nmb a2200000Iu 4500
"200420 2020 eng "
1546-9735
10.17161/bi.v15i2.13376
doi
dc
General Theory and Good Practices in Ecological Niche Modeling: A Basic Guide
Simoes, Marianna
https://orcid.org/0000-0003-4401-5530
Romero-Alvarez, Daniel
University of Kansas https://orcid.org/0000-0002-6762-6046
Nuñez-Penichet, Claudia
https://orcid.org/0000-0001-7442-8593
Jiménez, Laura
University of Kansas https://orcid.org/0000-0002-6683-9576
E. Cobos, Marlon
https://orcid.org/0000-0002-2611-1767
Ecological niche modeling (ENM) and species distribution modeling (SDM) are sets of tools that allow the estimation of distributional areas on the basis of establishing relationships among known occurrences and environmental variables. These tools have a wide range of applications, particularly in biogeography, macroecology, and conservation biology, granting prediction of species potential distributional patterns in the present and dynamics of these areas in different periods or scenarios. Due to their relevance and practical applications, the usage of these methodologies has significantly increased throughout the years. Here, we provide a manual with the basic routines used in this field and a practical example of its implementation to promote good practices and guidance for new users.
The University of Kansas
2020-04-20 17:39:26
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/13376
Biodiversity Informatics; Vol. 15 No. 2 (2020)
eng
Copyright (c) 2020 Marianna Simoes, Daniel Romero-Alvarez, Claudia Nuñez-Penichet, Laura Jiménez, Marlon E. Cobos
oai:ojs.pkp.sfu.ca:article/13384
2020-09-30T18:19:15Z
jbi:ART
nmb a2200000Iu 4500
"200722 2020 eng "
1546-9735
10.17161/bi.v15i2.13384
doi
dc
Presence-only and Presence-absence Data for Comparing Species Distribution Modeling Methods
Elith, Jane
University of Melbourne
Graham, Catherine
Valavi, Roozbeh
Abegg, Meinrad
Bruce, Caroline
Ferrier, Simon
Ford, Andrew
Guisan, Antoine
Hijmans, Robert J.
Huettmann, Falk
Lohmann, Lucia
Loiselle, Bette
Moritz, Craig
Overton, Jake
Peterson, A. Townsend
Phillips, Steven
Richardson, Karen
Williams, Stephen
Wiser, Susan K.
Wohlgemuth, Thomas
Zimmermann, Niklaus E.
Species distribution models (SDMs) are widely used to predict and study distributions of species. Many different modeling methods and associated algorithms are used and continue to emerge. It is important to understand how different approaches perform, particularly when applied to species occurrence records that were not gathered in structured surveys (e.g. opportunistic records). This need motivated a large-scale, collaborative effort, published in 2006, that aimed to create objective comparisons of algorithm performance. As a benchmark, and to facilitate future comparisons of approaches, here we publish that dataset: point location records for 226 anonymized species from six regions of the world, with accompanying predictor variables in raster (grid) and point formats. A particularly interesting characteristic of this dataset is that independent presence-absence survey data are available for evaluation alongside the presence-only species occurrence data intended for modeling. The dataset is available on Open Science Framework and as an R package and can be used as a benchmark for modeling approaches and for testing new ways to evaluate the accuracy of SDMs.
The University of Kansas
2020-04-20 17:39:26
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/13384
Biodiversity Informatics; Vol. 15 No. 2 (2020)
eng
Copyright (c) 2020 Jane Elith, Catherine Graham, Roozbeh Valavi, Meinrad Abegg, Caroline Bruce, Simon Ferrier, Andrew Ford, Antoine Guisan, Robert J. Hijmans, Falk Huettmann, Lucia Lohmann, Bette Loiselle, Craig Moritz, Jake Overton, A. Townsend Peterson, Steven Phillips, Karen Richardson, Stephen Williams, Susan K. Wiser, Thomas Wohlgemuth, Niklaus E. Zimmermann
oai:ojs.pkp.sfu.ca:article/13402
2020-07-15T15:35:44Z
jbi:ART
nmb a2200000Iu 4500
"200131 2020 eng "
1546-9735
10.17161/bi.v15i1.13402
doi
dc
Can We Infer Species Interactions from Co-occurrence Patterns? A Reply to Peterson et al. (2020)
Stephens, Christopher Rhodes
C3 Centro de Ciencias de la Complejidad,
No abstract.
The University of Kansas
2020-02-01 10:19:32
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/13402
Biodiversity Informatics; Vol. 15 No. 1 (2020): Debate: Ecological Interactions and Geographic Co-occurrence
eng
Copyright (c) 2020 Christopher Rhodes Stephens
oai:ojs.pkp.sfu.ca:article/14758
2021-09-24T18:51:02Z
jbi:ART
nmb a2200000Iu 4500
"210703 2021 eng "
1546-9735
10.17161/bi.v16i1.14758
doi
dc
Predicting multi-species bark beetle (Coleoptera: Curculionidae: Scolytinae) occurrence in Alaska: First use of open access big data mining and open source GIS to provide robust inference and a role model for progress in forest conservation
Zabihi, Khodabakhsh
University of Alaska Fairbanks (UAF)
Huettmann, Falk
University of Alaska Fairbanks (UAF)
Young, Brian
Landmark College
Native bark beetles (Coleoptera: Curculionidae: Scolytinae) are a multi-species complex that rank among the key disturbances of coniferous forests of western North America. Many landscape-level variables are known to influence beetle outbreaks, such as suitable climatic conditions, spatial arrangement of incipient populations, topography, abundance of mature host trees, and disturbance history that include former outbreaks and fire. We assembled the first open access data, which can be used in open source GIS platforms, for understanding the ecology of the bark beetle organism in Alaska. We used boosted classification and regression tree as a machine learning data mining algorithm to model-predict the relationship between 14 environmental variables, as model predictors, and 838 occurrence records of 68 bark beetle species compared to pseudo-absence locations across the state of Alaska. The model predictors include topography- and climate-related predictors as well as feature proximities and anthropogenic factors. We were able to model, predict, and map the multi-species bark beetle occurrences across the state of Alaska on a 1-km spatial resolution in addition to providing a good quality environmental dataset freely accessible for the public. About 16% of the mixed forest and 59% of evergreen forest are expected to be occupied by the bark beetles based on current climatic conditions and biophysical attributes of the landscape. The open access dataset that we prepared, and the machine learning modeling approach that we used, can provide a foundation for future research not only on scolytines but for other multi-species questions of concern, such as forest defoliators, and small and big game wildlife species worldwide.
The University of Kansas
2021-09-15 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/14758
Biodiversity Informatics; Vol. 16 No. 1 (2021)
eng
Copyright (c) 2021 Khodabakhsh Zabihi, Falk Huettmann, Brian Young
oai:ojs.pkp.sfu.ca:article/14782
2021-09-24T18:51:02Z
jbi:ART
nmb a2200000Iu 4500
"210703 2021 eng "
1546-9735
10.17161/bi.v16i1.14782
doi
dc
Visualizing species richness and site similarity from presence-absence matrices
Soberón, Jorge
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Cobos, Marlon E.
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Nuñez-Penichet, Claudia
Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045 USA
Species richness and similarity of biotas among distinct sites are important quantities in biogeography. Indices derived from presence-absence matrices are used to represent these quantities in so-called diversity-range plots. The most commonly used diversity-range plot, however, has multiple special cases and its interpretation is cumbersome. Here we present an equivalent formulation that is geometrically simpler and has no special cases. In addition, we introduce a method to identify the statistical significance of the dispersion field, an index that represents how similar species composition is in a cell with respect to the whole area. The new diversity-range plot is a promising tool to explore biodiversity and endemism in a region as the values shown in this plot and whether they are statistically significant or not can also be represented in geography.
The University of Kansas
2021-09-15 00:00:00
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/14782
Biodiversity Informatics; Vol. 16 No. 1 (2021)
eng
Copyright (c) 2021 Jorge Soberon, Marlon E. Cobos, Claudia Nuñez-Penichet
oai:ojs.pkp.sfu.ca:article/15016
2022-10-10T19:35:38Z
jbi:TM
nmb a2200000Iu 4500
"220306 2022 eng "
1546-9735
10.17161/bi.v17i.15016
doi
dc
ENM2020: A Free Online Course and Set of Resources on Modeling Species' Niches and Distributions
Peterson, A. Townsend
University of Kansas https://orcid.org/0000-0003-0243-2379
Aiello-Lammens, Matthew
https://orcid.org/0000-0002-6180-5959
Amatulli, Giuseppe
Anderson, Robert
https://orcid.org/0000-0002-7706-4649
Cobos, Marlon
https://orcid.org/0000-0002-2611-1767
Diniz-Filho, José Alexandre
Escobar, Luis
https://orcid.org/0000-0001-5735-2750
Feng, Xiao
https://orcid.org/0000-0003-4638-3927
Franklin, Janet
https://orcid.org/0000-0003-0314-4598
Gadelha, Luiz
https://orcid.org/0000-0002-8122-9522
Georges, Damien
https://orcid.org/0000-0003-2425-7591
Guéguen, M
https://orcid.org/0000-0002-1045-2997
Gueta, Tomer
Ingenloff, Kate
https://orcid.org/0000-0001-5942-9053
Jarvie, Scott
Jiménez, Laura
https://orcid.org/0000-0002-6683-9576
Karger, Dirk
https://orcid.org/0000-0001-7770-6229
Kass, Jamie
https://orcid.org/0000-0002-9432-895X
Kearney, Michael
https://orcid.org/0000-0002-3349-8744
Loyola, Rafael
Machado-Stredel, Fernando
https://orcid.org/0000-0002-8378-3172
Martínez-Meyer, Enrique
https://orcid.org/0000-0003-1184-9264
Merow, Cory
Mondelli, Maria Luiza
https://orcid.org/0000-0003-1572-2084
Mortara, Sara
Muscarella, Robert
https://orcid.org/0000-0003-3039-1076
Myers, Corinne
https://orcid.org/0000-0003-1490-7378
Naimi, Babak
Noesgaard, Daniel
Ondo, Ian
https://orcid.org/0000-0001-7816-5882
Osorio-Olvera, Luis
Owens, Hannah
https://orcid.org/0000-0003-0071-1745
Pearson, Richard
https://orcid.org/0000-0002-3458-0539
Pinilla-Buitrago, Gonzalo
https://orcid.org/0000-0002-0065-945X
Sánchez-Tapia, Andrea
https://orcid.org/0000-0002-3521-4338
Saupe, Erin
https://orcid.org/0000-0002-0370-9897
Thuiller, Wilfried
https://orcid.org/0000-0002-5388-5274
Varela, Sara
Warren, Dan
https://orcid.org/0000-0002-8747-2451
Wieczorek, John
https://orcid.org/0000-0003-1144-0290
Yates, Katherine
Zhu, Gengping
https://orcid.org/0000-0001-6823-5840
Zuquim, Gabriela
https://orcid.org/0000-0003-0932-2308
Zurell, Damaris
https://orcid.org/0000-0002-4628-3558
The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.
The University of Kansas
2022-03-06 09:30:08
Peer-reviewed training modules
application/pdf
https://journals.ku.edu/jbi/article/view/15016
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 A. Townsend Peterson, Matthew Aiello-Lammens, Giuseppe Amatulli, Robert Anderson, Marlon Cobos, José Alexandre Diniz-Filho, Luis Escobar, Xiao Feng, Janet Franklin, Luiz Gadelha, Damien Georges, M Guéguen, Tomer Gueta, Kate Ingenloff, Scott Jarvie, Laura Jiménez, Dirk Karger, Jamie Kass, Michael Kearney, Rafael Loyola, Fernando Machado-Stredel, Enrique Martínez-Meyer, Cory Merow, Maria Luiza Mondelli, Sara Mortara, Robert Muscarella, Corinne Myers, Babak Naimi, Daniel Noesgaard, Ian Ondo, Luis Osorio-Olvera, Hannah Owens, Richard Pearson, Gonzalo Pinilla-Buitrago, Andrea Sánchez-Tapia, Erin Saupe, Wilfried Thuiller, Sara Varela, Dan Warren, John Wieczorek, Katherine Yates, Gengping Zhu, Gabriela Zuquim, Damaris Zurell
oai:ojs.pkp.sfu.ca:article/15483
2022-10-12T14:57:19Z
jbi:ART
nmb a2200000Iu 4500
"210804 2021 eng "
1546-9735
10.17161/bi.v16i1.15483
doi
dc
Global land-use and land-cover data for ecologists: Historical, current, and future scenarios
Rocha, Tainá
Botanical Garden Research Institute of Rio de Janeiro, Rio de Janeiro, Brazil
Vale, Mariana M.
Lima-Ribeiro, Matheus S.
Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25o spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.
The University of Kansas
2021-09-15 00:00:00
Peer-reviewed Article
application/pdf
application/vnd.openxmlformats-officedocument.wordprocessingml.document
https://journals.ku.edu/jbi/article/view/15483
Biodiversity Informatics; Vol. 16 No. 1 (2021)
eng
Copyright (c) 2021 Tainá Rocha, Mariana M. Vale, Matheus S. Lima-Ribeiro
oai:ojs.pkp.sfu.ca:article/15581
2022-10-10T19:47:33Z
jbi:ART
nmb a2200000Iu 4500
"220306 2022 eng "
1546-9735
10.17161/bi.v17i.15581
doi
dc
Biodiversity and distribution of Isopoda and Polychaeta along the Northwestern Pacific and the Arctic Ocean
Saeedi, Hanieh
Senckenberg Research Institute and Natural History Museum";} https://orcid.org/0000-0002-4845-0241
Brandt, Angelika
Jacobsen, Nils L.
https://orcid.org/0000-0001-9626-0963
The northwestern Pacific Ocean is one of the hotspots of species richness and one of the high endemicity areas of the World Ocean. However, large-scale biodiversity patterns of major deep‑sea taxa such as Isopoda and Polychaeta are still poorly studied. The goal of this research is to study the distribution, biodiversity, and community composition of Isopoda and Polychaeta (including Siboglinidae and Echiura) across the northwestern Pacific Ocean and the adjacent Arctic Ocean. The study area was divided into equal-sized hexagonal cells (c. 700,000 km²), ecoregions, 5° latitudinal bands, and 200 m depth intervals as unit of analysis. Our results revealed that the area around the Philippines and the Laptev Sea had the highest isopod and polychaete’s species richness compared to the other geographic regions of our study, with a latitudinal decline of species richness in shallow waters in both taxa. In the deep sea, maximum species richness increased towards the temperate latitudes. Gamma species richness (number of species per 200 m depth interval) also declined with depth. Rarefied species richness of isopods peaked around 5000 m depth. Rarefaction curves demonstrated a great potential for undiscovered richness across 5° latitudinal bands and depth intervals. In shallow waters, polychaetes with a pelagic larval phase had a wider distribution range compared to brooding isopods, but, in the deep sea, isopods had slightly wider distribution ranges compared to polychaetes. These results thus demonstrated that shallow water taxa with pelagic larvae and polychaete species with a wide vertical distribution range could potentially invade higher latitudes, such as species from the Northwest Pacific invading the Arctic Ocean under the rapid climate change and catastrophic reduction of sea ice cover. These changes might dramatically change the benthic communities of the Arctic Ocean and management of such should take an adaptive approach and apply measures that take potential extension and invasion of species into account.
The University of Kansas
2022-03-06 09:30:08
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/15581
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Hanieh Saeedi, Nils L. Jacobsen, Angelika Brandt
oai:ojs.pkp.sfu.ca:article/15985
2022-10-10T19:44:29Z
jbi:SP
nmb a2200000Iu 4500
"220512 2022 eng "
1546-9735
10.17161/bi.v17i.15985
doi
dc
Detecting Signals of Species’ Ecological Niches in Results of Studies with Defined Sampling Protocols: Example Application to Pathogen Niches
Cobos, Marlon E.
Department of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas https://orcid.org/0000-0002-2611-1767
Peterson, A. Townsend
Department of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas https://orcid.org/0000-0003-0243-2379
Ecological niches are increasingly appreciated as a long-term stable constraint on the geographic and temporal distributions of species, including species involved in disease transmission cycles (pathogens, vectors, hosts). Although considerable research effort has used correlative methodologies for characterizing niches, sampling effort (and the biases that this effort may or may not carry with it) considerations have generally not been incorporated explicitly into ecological niche modeling. In some cases, however, the sampling effort can be characterized explicitly, such as when hosts are tested for pathogens, as well as comparable situations such as when traps are deployed to capture particular species, etc. Here, we present simple methods for testing the hypothesis that non-randomness in occurrence or detection exists with respect to environmental dimensions (= a detectable signal of ecological niche); i.e., whether a pathogen occurs nonrandomly with respect to environment, given the occurrence and sampling of its host. We have implemented a set of R functions that presents an overall test for nonrandom occurrence with respect to a set of environmental dimensions, and, a posteriori, a set of exploratory tests that identify in which dimension(s) and in which direction or form the nonrandom occurrence is manifested. Our tools correctly detected signals of niche in most of our example cases. Although such signal may not be detectable in cases in which the niche of interest is broader than the universe sampled, such a possibility was correctly discarded in our analyses, preventing further interpretations. This kind of testing can constitute an initial step in a process that would conclude with development of a more typical ecological niche model. The particular advantage of the analyses proposed is that they consider the biases involved in sampling, testing, and reporting, in the context of nonrandom occurrence with respect to environment before proceeding to inferential and predictive steps.
The University of Kansas
2022-03-06 09:30:08
Software and Protocols
application/pdf
https://journals.ku.edu/jbi/article/view/15985
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Marlon E. Cobos, A. Townsend Peterson
oai:ojs.pkp.sfu.ca:article/16271
2022-10-10T19:45:19Z
jbi:SP
nmb a2200000Iu 4500
"220519 2022 eng "
1546-9735
10.17161/bi.v17i.16271
doi
dc
rangemap: An R Package to Explore Species' Geographic Ranges
Cobos, Marlon E.
University of Kansas
Barve, Vijay
Florida Museum of Natural History, University of Florida, Gainesville, Florida 32611, USA https://orcid.org/0000-0002-4852-2567
Barve, Narayani
Florida Museum of Natural History, University of Florida, Gainesville, Florida 32611, USA https://orcid.org/0000-0002-7893-8774
Jiménez-Valverde, Alberto
https://orcid.org/0000-0001-9962-2106
Nuñez-Penichet, Claudia
https://orcid.org/0000-0001-7442-8593
Data exploration is a critical step in understanding patterns and biases in information about species’ geographic distributions. We present rangemap, an R package that implements tools to explore species’ ranges based on simple analyses and visualizations. The rangemap package uses species occurrence coordinates, spatial polygons, and raster layers as input data. Its analysis tools help to generate simple spatial polygons summarizing ranges based on distinct approaches, including spatial buffers, convex and concave (alpha) hulls, trend-surface analysis, and raster reclassification. Visualization tools included in the package help to produce simple, high-quality representations of occurrence data and figures summarizing resulting ranges in geographic and environmental spaces. Functions that create ranges also allow generating extents of occurrence (using convex hulls) and areas of occupancy according to IUCN criteria. A broad community of researchers and students could find in rangemap an interesting means by which to explore species’ geographic distributions.
The University of Kansas
2022-03-06 09:30:08
Software and Protocols
application/pdf
https://journals.ku.edu/jbi/article/view/16271
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Marlon E. Cobos, Vijay Barve, Narayani Barve, Alberto Jiménez-Valverde, Claudia Nuñez-Penichet
oai:ojs.pkp.sfu.ca:article/16441
2022-10-10T19:47:33Z
jbi:ART
nmb a2200000Iu 4500
"220412 2022 eng "
1546-9735
10.17161/bi.v17i.16441
doi
dc
Best Practices for Data Management in Citizen Science - An Indian Outlook
Vattakaven, Thomas
Strand Life Sciences https://orcid.org/0000-0002-2337-3825
Barve, Vijay
Nature Mates Nature Club https://orcid.org/0000-0002-4852-2567
Ramaswami, Geetha
Nature Conservation Foundation https://orcid.org/0000-0002-1806-4032
Singh, Priya
Researchers for Wildlife Conservation (RWC), National Centre for Biological Sciences https://orcid.org/0000-0001-6069-3257
Jagannathan, Suneha
Dakshin Foundation https://orcid.org/0000-0002-1175-337X
Dhandapani, Balasubramanian
French Institute of Pondicherry https://orcid.org/0000-0002-2078-1858
Citizen science has been in practice since the 1800s and is an important source of data for scientists and other applied users. It plays a vital role in democratizing science, providing equitable access to scientific participation and data, helps build the capacity of its participants, inculcates the spirit of scientific endeavor and discovery and sensitizes participants towards species and habitat conservation, creating a sense of stewardship towards nature. In recent years, citizen science, especially in biodiversity, has rapidly developed with the rising popularity of smartphones, and widespread access to the internet, leading to wider adoption globally. India has also witnessed a surge in the number of new citizen science projects being initiated and increased participation in these projects. With more proponents looking at initiating such projects, there is little documentation from an Indian perspective on setting up, collecting, managing, and maintaining biodiversity-focused citizen science projects, especially in a data-management context. We have attempted to fill this void by examining the best practices across the data life cycle of citizen science projects while keeping in mind sensitivities and scenarios in India. We hope this will prove to be an important reference for citizen science practitioners looking to better manage their data in their projects.
The University of Kansas
2022-03-06 09:30:08
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/16441
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Thomas Vattakaven, Vijay Barve, Geetha Ramaswami, Priya Singh, Suneha Jagannathan, Balasubramanian Dhandapani
oai:ojs.pkp.sfu.ca:article/17593
2022-10-10T19:47:32Z
jbi:ART
nmb a2200000Iu 4500
"220721 2022 eng "
1546-9735
10.17161/bi.v17i.17593
doi
dc
Guide francophone pour la modélisation de niches écologiques
Vignoles, Anais
(english)
Correlational ecological niche modeling (ENM) is a popular group of methods in the field of distributional ecology and is employed for a variety of applications. Although the conceptual and methodological framework of ENM has been widely described in the literature, there is still no exhaustive synthesis of it in the French language. In this article, theoretical bases of ENM are exposed through a history of the concept of ecological niche as well as its implications for the study of species macroscale distributions. Then, the different steps of ENM are described, emphasizing on the importance of controlling the quality of input data. Various recommendations concerning algorithm choice, model calibration and evaluation as well post-modeling analyses, such as niche comparison and transfer to other periods/regions, are presented. Particular emphasis is placed on 1/ the operation of Maxent and the need for parameter tuning prior modeling, 2/ the importance of the choice of the M calibration area, 3/ the need to take into account accessible environments (M) for model transfer and comparison, and 4/ the importance of evaluating and presenting the variability of models resulting from methodological choices at different stages (occurrence data partitioning, choice of a climate model, choice of algorithm, choice of the calibration area, etc.). To conclude, contextualizing any ENM study in a clear and explicit theoretical and methodological framework is paramount to ensure the pertinence of subsequent interpretations.
Key-words: ecological niche modeling ; good practices ; conceptual framework ; model calibration and evaluation ; model transfer ; model comparison
(french)
La modélisation corrélationnelle de niches écologiques (ENM) est un ensemble de méthodes populaire dans le champ de l’écologie de la distribution d’espèces et est employée pour une multitude d’applications. Si le cadre conceptuel et méthodologique de l’ENM a été largement décrit dans la littérature, il n’existe pas de synthèse exhaustive en langue française. Dans cet article, nous exposons les bases théoriques de l’ENM à travers un historique du concept de niche écologique et ses implications pour l’étude de la distribution macro-géographique des espèces. Nous décrivons ensuite les différentes étapes d’une étude ENM, en insistant tout d’abord sur l’importance de contrôler la qualité des données d’entrées. Différentes préconisations concernant le choix des algorithmes, la calibration et l’évaluation des modèles ainsi que les analyses postérieures, telles que les comparaisons de niches ou le transfert à d’autres périodes/régions, sont présentées. Nous insistons en particulier sur 1/ le fonctionnement de l’algorithme Maxent et la nécessité d’un processus de réglage de ses paramètres, 2/ l’importance du choix de l’aire de calibration M, 3/ la nécessité de prendre en compte les environnements accessibles (M) dans le transfert et la comparaison des modèles, et 4/ l’importance d’évaluer et de présenter la variabilité des résultats en fonction de choix méthodologiques à différentes étapes (partitionnement des données d’occurrences, choix d’un modèle climatique, choix de l’algorithme, choix de l’aire de calibration, etc.). En conclusion, nous rappelons l’importance d’ancrer toute étude employant l’ENM dans un cadre théorique et méthodologique clair et explicite afin de garantir la pertinence des interprétations ultérieures.
Mots-clés : modélisation de niches écologiques ; bonnes pratiques ; cadre conceptuel ; calibration et évaluation des modèles ; transfert de modèles ; comparaison de modèles
The University of Kansas
2022-03-06 09:30:08
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/17593
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Anais Vignoles
oai:ojs.pkp.sfu.ca:article/18270
2022-12-20T18:14:54Z
jbi:ART
nmb a2200000Iu 4500
"221220 2022 eng "
1546-9735
10.17161/bi.v17i.18270
doi
dc
Biodiversity Informatics for Public Policy. The case of CONABIO in Mexico
Soberón, Jorge
In this work I present an overview of the development of the system of biodiversity information that was developed for the federal government of Mexico. I describe briefly the organization that made the system possible and some of its history. Then I focus on the principles of design of the information system, and a few of its major uses. I provide data on costs and usage, and finish reflecting on the institutional fragility of such systems.
The University of Kansas
2022-03-06 09:30:08
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/18270
Biodiversity Informatics; Vol. 17 (2022): Biodiversity Informatics
eng
Copyright (c) 2022 Jorge Soberon
oai:ojs.pkp.sfu.ca:article/20516
2024-02-02T04:34:10Z
jbi:ART
nmb a2200000Iu 4500
"240201 2024 eng "
1546-9735
10.17161/bi.v18i.20516
doi
dc
The IBdata Web System for Biological Collections: Design Focused on Usability
Murguía-Romero, Miguel
Universidad Nacional Autónoma de México
Serrano-Estrada, Bernardo
https://orcid.org/orcid-search/search?searchQuery=bernardo%20serrano%20estrada
Salazar, Gerardo A.
Sánchez-González, Gerardo E.
Melo Samper Palacios, Ubaldo
Gernandt, David S.
Magallón, Susana
Sánchez-Cordero, Víctor
The software design process must put users at the core of the process to enable them to meet their specific objectives effectively, efficiently, and successfully. Thus, a software design for a computing system to consult biological collections guided by the concept of usability will result in an effective and efficient biodiversity informatics tool. Here, we introduce IBdata, a web system to consult biological collections, developed using a design approach based on the architecture of three layers: database, business rules, and user interface. The user interface design was guided by the concept of usability focused on four core concepts: simplicity, adaptability, guide the user through the journey, and feedback. The IBdata web system that we developed is composed of three modules (query, capture and editing, and administration), permitting it to query a database with about 1.7 million specimen records. Biodiversity data query systems must be effective and efficient and should meet the user’s expectations. Software design methodologies play a central role in achieving these goals, and, in this context, interface design techniques that put the user at the core of development are valuable, as in the development of the IBdata web system.
The University of Kansas
2024-02-01 15:01:53
Peer-reviewed Article
application/pdf
https://journals.ku.edu/jbi/article/view/20516
Biodiversity Informatics; Vol. 18 (2024)
eng
Copyright (c) 2024 Miguel Murguía-Romero, Bernardo Serrano-Estrada, Gerardo A. Salazar, Gerardo E. Sánchez-González, Ubaldo Melo Samper Palacios, David S. Gernandt, Susana Magallón, Víctor Sánchez-Cordero