Trends and biases in global scientific literature about ecological niche models
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842015000800017 |
Resumo: | Abstract Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P<0.001), with a sharp increase in recent years, highlighting the widespread use of the ENMs. There was an increase in the diversity of journals that published papers about ENMs (r=0.97, P<0.001). The research was conducted in different countries, predominantly the United States of America (550 papers), and the most commonly used method was the Maximum Entropy method (312 papers). Regarding the taxonomic group, most research has been conducted on plants (402 papers, or 28.36% of the total). There was no relationship between the modeling method used and the taxonomic group studied (χ2=4.8, P=0.15). Finally, the wide availability of biological, environmental and computational resources has elicited the broad use of tools for ENMs. Despite the conceptual discussions of the ENMs, this method is currently the most effective way to evaluate the potential geographical distribution of species, and to predict the distribution under different environmental conditions (i.e., future or past scenarios). |
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Trends and biases in global scientific literature about ecological niche modelsscientometricspecies distribution modelMaximum EntropyAbstract Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P<0.001), with a sharp increase in recent years, highlighting the widespread use of the ENMs. There was an increase in the diversity of journals that published papers about ENMs (r=0.97, P<0.001). The research was conducted in different countries, predominantly the United States of America (550 papers), and the most commonly used method was the Maximum Entropy method (312 papers). Regarding the taxonomic group, most research has been conducted on plants (402 papers, or 28.36% of the total). There was no relationship between the modeling method used and the taxonomic group studied (χ2=4.8, P=0.15). Finally, the wide availability of biological, environmental and computational resources has elicited the broad use of tools for ENMs. Despite the conceptual discussions of the ENMs, this method is currently the most effective way to evaluate the potential geographical distribution of species, and to predict the distribution under different environmental conditions (i.e., future or past scenarios).Instituto Internacional de Ecologia2015-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842015000800017Brazilian Journal of Biology v.75 n.4 suppl.1 2015reponame:Brazilian Journal of Biologyinstname:Instituto Internacional de Ecologia (IIE)instacron:IIE10.1590/1519-6984.22713info:eu-repo/semantics/openAccessVaz,U. L.Cunha,H. F.Nabout,J. C.eng2015-12-11T00:00:00Zoai:scielo:S1519-69842015000800017Revistahttps://www.scielo.br/j/bjb/https://old.scielo.br/oai/scielo-oai.phpbjb@bjb.com.br||bjb@bjb.com.br1678-43751519-6984opendoar:2015-12-11T00:00Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)false |
dc.title.none.fl_str_mv |
Trends and biases in global scientific literature about ecological niche models |
title |
Trends and biases in global scientific literature about ecological niche models |
spellingShingle |
Trends and biases in global scientific literature about ecological niche models Vaz,U. L. scientometric species distribution model Maximum Entropy |
title_short |
Trends and biases in global scientific literature about ecological niche models |
title_full |
Trends and biases in global scientific literature about ecological niche models |
title_fullStr |
Trends and biases in global scientific literature about ecological niche models |
title_full_unstemmed |
Trends and biases in global scientific literature about ecological niche models |
title_sort |
Trends and biases in global scientific literature about ecological niche models |
author |
Vaz,U. L. |
author_facet |
Vaz,U. L. Cunha,H. F. Nabout,J. C. |
author_role |
author |
author2 |
Cunha,H. F. Nabout,J. C. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Vaz,U. L. Cunha,H. F. Nabout,J. C. |
dc.subject.por.fl_str_mv |
scientometric species distribution model Maximum Entropy |
topic |
scientometric species distribution model Maximum Entropy |
description |
Abstract Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P<0.001), with a sharp increase in recent years, highlighting the widespread use of the ENMs. There was an increase in the diversity of journals that published papers about ENMs (r=0.97, P<0.001). The research was conducted in different countries, predominantly the United States of America (550 papers), and the most commonly used method was the Maximum Entropy method (312 papers). Regarding the taxonomic group, most research has been conducted on plants (402 papers, or 28.36% of the total). There was no relationship between the modeling method used and the taxonomic group studied (χ2=4.8, P=0.15). Finally, the wide availability of biological, environmental and computational resources has elicited the broad use of tools for ENMs. Despite the conceptual discussions of the ENMs, this method is currently the most effective way to evaluate the potential geographical distribution of species, and to predict the distribution under different environmental conditions (i.e., future or past scenarios). |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-11-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842015000800017 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842015000800017 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1519-6984.22713 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto Internacional de Ecologia |
publisher.none.fl_str_mv |
Instituto Internacional de Ecologia |
dc.source.none.fl_str_mv |
Brazilian Journal of Biology v.75 n.4 suppl.1 2015 reponame:Brazilian Journal of Biology instname:Instituto Internacional de Ecologia (IIE) instacron:IIE |
instname_str |
Instituto Internacional de Ecologia (IIE) |
instacron_str |
IIE |
institution |
IIE |
reponame_str |
Brazilian Journal of Biology |
collection |
Brazilian Journal of Biology |
repository.name.fl_str_mv |
Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE) |
repository.mail.fl_str_mv |
bjb@bjb.com.br||bjb@bjb.com.br |
_version_ |
1752129882042662912 |