Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach
| Main Author: | |
|---|---|
| Publication Date: | 2015 |
| Other Authors: | |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-12672015000200010 |
Summary: | Biological invasion by exotic organisms became a key issue, a concern associated to the deep impacts on several domains described as resultant from such processes. A better understanding of the processes, the identification of more susceptible areas, and the definition of preventive or mitigation measures are identified as critical for the purpose of reducing associated impacts. The use of species distribution modeling might help on the purpose of identifying areas that are more susceptible to invasion. This paper aims to present preliminary results on assessing the susceptibility to invasion by the exotic species Acacia dealbata Mill. in the Ceira river basin. The results are based on the maximum entropy modeling approach, considered one of the correlative modelling techniques with better predictive performance. Models which validation is based on independent data sets present better performance, an evaluation based on the AUC of ROC accuracy measure. |
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Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approachsusceptibility to invasionmaximum entropyspecies distribution modellingGISBiological invasion by exotic organisms became a key issue, a concern associated to the deep impacts on several domains described as resultant from such processes. A better understanding of the processes, the identification of more susceptible areas, and the definition of preventive or mitigation measures are identified as critical for the purpose of reducing associated impacts. The use of species distribution modeling might help on the purpose of identifying areas that are more susceptible to invasion. This paper aims to present preliminary results on assessing the susceptibility to invasion by the exotic species Acacia dealbata Mill. in the Ceira river basin. The results are based on the maximum entropy modeling approach, considered one of the correlative modelling techniques with better predictive performance. Models which validation is based on independent data sets present better performance, an evaluation based on the AUC of ROC accuracy measure.Universidade do Porto - Faculdade de Letras2015-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articletext/htmlhttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-12672015000200010GOT, Revista de Geografia e Ordenamento do Território n.8 2015reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAPenghttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-12672015000200010Pereira,JorgeFigueiredo,Albanoinfo:eu-repo/semantics/openAccess2024-02-06T17:25:57Zoai:scielo:S2182-12672015000200010Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:13:14.070721Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| title |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| spellingShingle |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach Pereira,Jorge susceptibility to invasion maximum entropy species distribution modelling GIS |
| title_short |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| title_full |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| title_fullStr |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| title_full_unstemmed |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| title_sort |
Assessing suitable area for Acacia dealbata Mill. in the Ceira River Basin (Central Portugal) based on maximum entropy modelling approach |
| author |
Pereira,Jorge |
| author_facet |
Pereira,Jorge Figueiredo,Albano |
| author_role |
author |
| author2 |
Figueiredo,Albano |
| author2_role |
author |
| dc.contributor.author.fl_str_mv |
Pereira,Jorge Figueiredo,Albano |
| dc.subject.por.fl_str_mv |
susceptibility to invasion maximum entropy species distribution modelling GIS |
| topic |
susceptibility to invasion maximum entropy species distribution modelling GIS |
| description |
Biological invasion by exotic organisms became a key issue, a concern associated to the deep impacts on several domains described as resultant from such processes. A better understanding of the processes, the identification of more susceptible areas, and the definition of preventive or mitigation measures are identified as critical for the purpose of reducing associated impacts. The use of species distribution modeling might help on the purpose of identifying areas that are more susceptible to invasion. This paper aims to present preliminary results on assessing the susceptibility to invasion by the exotic species Acacia dealbata Mill. in the Ceira river basin. The results are based on the maximum entropy modeling approach, considered one of the correlative modelling techniques with better predictive performance. Models which validation is based on independent data sets present better performance, an evaluation based on the AUC of ROC accuracy measure. |
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2015 |
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2015-12-01 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-12672015000200010 |
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eng |
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eng |
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http://scielo.pt/scielo.php?script=sci_arttext&pid=S2182-12672015000200010 |
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Universidade do Porto - Faculdade de Letras |
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Universidade do Porto - Faculdade de Letras |
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