Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil
Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence prob...
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| Format: | Article |
| Language: | English |
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Instituto Nacional de Pesquisas da Amazônia
2015-06-01
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| Series: | Acta Amazonica |
| Subjects: | |
| Online Access: | http://www.scielo.br/pdf/aa/v45n2/1809-4392-aa-45-02-00167.pdf |
| _version_ | 1828138075352465408 |
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| author | Symone Maria de Melo FIGUEIREDO Eduardo Martins VENTICINQUE Evandro Orfanó FIGUEIREDO Evandro José Linhares FERREIRA |
| author_facet | Symone Maria de Melo FIGUEIREDO Eduardo Martins VENTICINQUE Evandro Orfanó FIGUEIREDO Evandro José Linhares FERREIRA |
| author_sort | Symone Maria de Melo FIGUEIREDO |
| collection | DOAJ |
| description | Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging. |
| first_indexed | 2024-04-11T18:30:09Z |
| format | Article |
| id | doaj.art-c466d99e4db8440cbf0616dec3dbaec1 |
| institution | Directory Open Access Journal |
| issn | 0044-5967 |
| language | English |
| last_indexed | 2024-04-11T18:30:09Z |
| publishDate | 2015-06-01 |
| publisher | Instituto Nacional de Pesquisas da Amazônia |
| record_format | Article |
| series | Acta Amazonica |
| spelling | doaj.art-c466d99e4db8440cbf0616dec3dbaec12022-12-22T04:09:29ZengInstituto Nacional de Pesquisas da AmazôniaActa Amazonica0044-59672015-06-0145216717410.1590/1809-4392201402834Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, BrazilSymone Maria de Melo FIGUEIREDOEduardo Martins VENTICINQUEEvandro Orfanó FIGUEIREDOEvandro José Linhares FERREIRASpecies distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.http://www.scielo.br/pdf/aa/v45n2/1809-4392-aa-45-02-00167.pdfmodelingMaxentforest inventorymodefloraAmazon |
| spellingShingle | Symone Maria de Melo FIGUEIREDO Eduardo Martins VENTICINQUE Evandro Orfanó FIGUEIREDO Evandro José Linhares FERREIRA Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil Acta Amazonica modeling Maxent forest inventory modeflora Amazon |
| title | Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil |
| title_full | Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil |
| title_fullStr | Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil |
| title_full_unstemmed | Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil |
| title_short | Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil |
| title_sort | predicting the distribution of forest tree species using topographic variables and vegetation index in eastern acre brazil |
| topic | modeling Maxent forest inventory modeflora Amazon |
| url | http://www.scielo.br/pdf/aa/v45n2/1809-4392-aa-45-02-00167.pdf |
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