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Registro Completo |
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
19/10/2016 |
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Data da última atualização: |
04/11/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
WREGE, M. S.; SOUSA, V. A. de; FRITZSONS, E.; SOARES, M. T. S.; AGUIAR, A. V. de. |
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Afiliação: |
MARCOS SILVEIRA WREGE, CNPF; VALDERES APARECIDA DE SOUSA, CNPF; ELENICE FRITZSONS, CNPF; MARCIA TOFFANI SIMAO SOARES, CPAP; ANANDA VIRGINIA DE AGUIAR, CNPF. |
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Título: |
Predicting current and future geographical distribution of araucaria in Brazil for fundamental niche modeling. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Environment and Ecology Research v. 4, n. 5, p. 269-279, 2016. |
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DOI: |
0.13189/eer.2016.040506 |
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Idioma: |
Inglês |
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Conteúdo: |
Geographic distribution forecast of Araucaria angustifolia (Bertol.) O. Kuntze. was studied. This is a native species that occurs more frequently in the southern region of Brazil and, to a lesser extent, in the southeasthern region. The study was based on points of occurrence that were collected over several years by Embrapa Forests and complemented by points obtained from herbaria, banks and several educational institutions, including the biological collections database Reference Center Environmental Information (CRIA), which gathers information from various herbaria in Brazil. We used mathematical models occurrence prediction, including: Bioclim, and Niche Mosaic. The models were selected for best representing the regions of occurrence. In addition to the points of occurrence, to compose the spatial modeling environmental data, climate, soil, and topography were needed. In the study we used only climate data such as the average minimum air temperature, average maximum air temperature, accumulated rainfall, and average relative humidity. We didn?t use soil data because there was not a detailed survey available throughout the area of occurrence of the species. We conclude that the naturally occurring region of Araucaria was well represented using only the climate data and two models that well represented the occurrence of regions. With climate change, there is a strong tendency to reduce the potential area of Araucaria in Brazil, especially in regions at lower latitudes and altitudes. MenosGeographic distribution forecast of Araucaria angustifolia (Bertol.) O. Kuntze. was studied. This is a native species that occurs more frequently in the southern region of Brazil and, to a lesser extent, in the southeasthern region. The study was based on points of occurrence that were collected over several years by Embrapa Forests and complemented by points obtained from herbaria, banks and several educational institutions, including the biological collections database Reference Center Environmental Information (CRIA), which gathers information from various herbaria in Brazil. We used mathematical models occurrence prediction, including: Bioclim, and Niche Mosaic. The models were selected for best representing the regions of occurrence. In addition to the points of occurrence, to compose the spatial modeling environmental data, climate, soil, and topography were needed. In the study we used only climate data such as the average minimum air temperature, average maximum air temperature, accumulated rainfall, and average relative humidity. We didn?t use soil data because there was not a detailed survey available throughout the area of occurrence of the species. We conclude that the naturally occurring region of Araucaria was well represented using only the climate data and two models that well represented the occurrence of regions. With climate change, there is a strong tendency to reduce the potential area of Araucaria in Brazil, especially in regions at lower latitudes and ... Mostrar Tudo |
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Palavras-Chave: |
Conservação genética; Ecological modelling niche; Genetic conservation; Potential distribution model; Realized niche. |
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Thesagro: |
Araucaria; Mudança Climática. |
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Thesaurus Nal: |
climate change. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02367naa a2200277 a 4500
001 2054974
005 2016-11-04
008 2016 bl --- 0-- u #d
024 7 $a0.13189/eer.2016.040506$2DOI
100 1 $aWREGE, M. S.
245 $aPredicting current and future geographical distribution of araucaria in Brazil for fundamental niche modeling.
260 $c2016
520 $aGeographic distribution forecast of Araucaria angustifolia (Bertol.) O. Kuntze. was studied. This is a native species that occurs more frequently in the southern region of Brazil and, to a lesser extent, in the southeasthern region. The study was based on points of occurrence that were collected over several years by Embrapa Forests and complemented by points obtained from herbaria, banks and several educational institutions, including the biological collections database Reference Center Environmental Information (CRIA), which gathers information from various herbaria in Brazil. We used mathematical models occurrence prediction, including: Bioclim, and Niche Mosaic. The models were selected for best representing the regions of occurrence. In addition to the points of occurrence, to compose the spatial modeling environmental data, climate, soil, and topography were needed. In the study we used only climate data such as the average minimum air temperature, average maximum air temperature, accumulated rainfall, and average relative humidity. We didn?t use soil data because there was not a detailed survey available throughout the area of occurrence of the species. We conclude that the naturally occurring region of Araucaria was well represented using only the climate data and two models that well represented the occurrence of regions. With climate change, there is a strong tendency to reduce the potential area of Araucaria in Brazil, especially in regions at lower latitudes and altitudes.
650 $aclimate change
650 $aAraucaria
650 $aMudança Climática
653 $aConservação genética
653 $aEcological modelling niche
653 $aGenetic conservation
653 $aPotential distribution model
653 $aRealized niche
700 1 $aSOUSA, V. A. de
700 1 $aFRITZSONS, E.
700 1 $aSOARES, M. T. S.
700 1 $aAGUIAR, A. V. de
773 $tEnvironment and Ecology Research$gv. 4, n. 5, p. 269-279, 2016.
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Embrapa Pantanal (CPAP) |
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