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SPECIES: A platform for the exploration of ecological data
The modeling of ecological data that include both abiotic and biotic factors is fundamental to our understanding of ecosystems. Repositories of biodiversity data, such as GBIF, iDigBio, Atlas of Living Australia, and SNIB (Mexico's National System of Biodiversity Information), contain a great d...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6392378/ https://www.ncbi.nlm.nih.gov/pubmed/30847061 http://dx.doi.org/10.1002/ece3.4800 |
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author | Stephens, Christopher R. Sierra‐Alcocer, Raúl González‐Salazar, Constantino Barrios, Juan M. Salazar Carrillo, Juan Carlos Robredo Ezquivelzeta, Everardo del Callejo Canal, Enrique |
author_facet | Stephens, Christopher R. Sierra‐Alcocer, Raúl González‐Salazar, Constantino Barrios, Juan M. Salazar Carrillo, Juan Carlos Robredo Ezquivelzeta, Everardo del Callejo Canal, Enrique |
author_sort | Stephens, Christopher R. |
collection | PubMed |
description | The modeling of ecological data that include both abiotic and biotic factors is fundamental to our understanding of ecosystems. Repositories of biodiversity data, such as GBIF, iDigBio, Atlas of Living Australia, and SNIB (Mexico's National System of Biodiversity Information), contain a great deal of information that can lead to knowledge discovery about ecosystems. However, there is a lack of tools with which to efficiently extract such knowledge. In this paper, we present SPECIES, an open, web‐based platform designed to extract implicit information contained in large scale sets of ecological data. SPECIES is based on a tested methodology, wherein the correlations of variables of arbitrary type and spatial resolution, both biotic and abiotic, discrete and continuous, may be explored from both niche and network perspectives. In distinction to other modeling systems, SPECIES is a full stack exploratory tool that integrates the three basic components: data (which is incrementally growing), a statistical modeling and analysis engine, and an interactive visualization front end. Combined, these components provide a powerful tool that may guide ecologists toward new insights. SPECIES is optimized to support fast hypothesis prototyping and testing, analyzing thousands of biotic and abiotic variables, and presenting descriptive results to the user at different levels of detail. SPECIES is an open‐access platform available online (http://species.conabio.gob.mx), that is, powerful, flexible, and easy to use. It allows for the exploration and incorporation of ecological data and its subsequent integration into predictive models for both potential ecological niche and geographic distribution. It also provides an ecosystemic, network‐based analysis that may guide the researcher in identifying relations between different biota, such as the relation between disease vectors and potential disease hosts. |
format | Online Article Text |
id | pubmed-6392378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63923782019-03-07 SPECIES: A platform for the exploration of ecological data Stephens, Christopher R. Sierra‐Alcocer, Raúl González‐Salazar, Constantino Barrios, Juan M. Salazar Carrillo, Juan Carlos Robredo Ezquivelzeta, Everardo del Callejo Canal, Enrique Ecol Evol Original Research The modeling of ecological data that include both abiotic and biotic factors is fundamental to our understanding of ecosystems. Repositories of biodiversity data, such as GBIF, iDigBio, Atlas of Living Australia, and SNIB (Mexico's National System of Biodiversity Information), contain a great deal of information that can lead to knowledge discovery about ecosystems. However, there is a lack of tools with which to efficiently extract such knowledge. In this paper, we present SPECIES, an open, web‐based platform designed to extract implicit information contained in large scale sets of ecological data. SPECIES is based on a tested methodology, wherein the correlations of variables of arbitrary type and spatial resolution, both biotic and abiotic, discrete and continuous, may be explored from both niche and network perspectives. In distinction to other modeling systems, SPECIES is a full stack exploratory tool that integrates the three basic components: data (which is incrementally growing), a statistical modeling and analysis engine, and an interactive visualization front end. Combined, these components provide a powerful tool that may guide ecologists toward new insights. SPECIES is optimized to support fast hypothesis prototyping and testing, analyzing thousands of biotic and abiotic variables, and presenting descriptive results to the user at different levels of detail. SPECIES is an open‐access platform available online (http://species.conabio.gob.mx), that is, powerful, flexible, and easy to use. It allows for the exploration and incorporation of ecological data and its subsequent integration into predictive models for both potential ecological niche and geographic distribution. It also provides an ecosystemic, network‐based analysis that may guide the researcher in identifying relations between different biota, such as the relation between disease vectors and potential disease hosts. John Wiley and Sons Inc. 2019-01-28 /pmc/articles/PMC6392378/ /pubmed/30847061 http://dx.doi.org/10.1002/ece3.4800 Text en © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Stephens, Christopher R. Sierra‐Alcocer, Raúl González‐Salazar, Constantino Barrios, Juan M. Salazar Carrillo, Juan Carlos Robredo Ezquivelzeta, Everardo del Callejo Canal, Enrique SPECIES: A platform for the exploration of ecological data |
title |
SPECIES: A platform for the exploration of ecological data |
title_full |
SPECIES: A platform for the exploration of ecological data |
title_fullStr |
SPECIES: A platform for the exploration of ecological data |
title_full_unstemmed |
SPECIES: A platform for the exploration of ecological data |
title_short |
SPECIES: A platform for the exploration of ecological data |
title_sort | species: a platform for the exploration of ecological data |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6392378/ https://www.ncbi.nlm.nih.gov/pubmed/30847061 http://dx.doi.org/10.1002/ece3.4800 |
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