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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
11/11/2016 |
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Data da última atualização: |
02/07/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FIGUEIREDO, S. M. de M.; VENTICINQUE, E. M.; FIGUEIREDO, E. O. |
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Afiliação: |
Symone Maria de Melo Figueiredo, Universidade Federal do Acre; Eduardo Martins Venticinque, Universidade Federal do Rio Grande do Norte; EVANDRO ORFANO FIGUEIREDO, CPAF-Acre. |
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Título: |
Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Revista Árvore, Viçosa, v. 40, n. 4, p. 617-625, 2016. |
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ISSN: |
0100-6762 |
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DOI: |
10.1590/0100-67622016000400005 |
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Idioma: |
Inglês |
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Conteúdo: |
Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area. |
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Palavras-Chave: |
Escala espacial; Interpolação; Interpolación; Interpolation; Inventario forestal; Madera tropical; Modelo de distribuição de espécies; Modelos de distribución de especies; Simulación por computadora; Southwest Amazon; Spatial scale; Species distribution models; Sudoeste da Amazônia. |
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Thesagro: |
Essência florestal; Flora; Inventário florestal; Modelo de simulação; População de planta; Programa de computador. |
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Thesaurus Nal: |
Computer simulation; Forest inventory; Tropical wood. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/149950/1/26198.pdf
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Marc: |
LEADER 02858naa a2200433 a 4500
001 2056281
005 2021-07-02
008 2016 bl uuuu u00u1 u #d
022 $a0100-6762
024 7 $a10.1590/0100-67622016000400005$2DOI
100 1 $aFIGUEIREDO, S. M. de M.
245 $aSpatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.$h[electronic resource]
260 $c2016
520 $aKnowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.
650 $aComputer simulation
650 $aForest inventory
650 $aTropical wood
650 $aEssência florestal
650 $aFlora
650 $aInventário florestal
650 $aModelo de simulação
650 $aPopulação de planta
650 $aPrograma de computador
653 $aEscala espacial
653 $aInterpolação
653 $aInterpolación
653 $aInterpolation
653 $aInventario forestal
653 $aMadera tropical
653 $aModelo de distribuição de espécies
653 $aModelos de distribución de especies
653 $aSimulación por computadora
653 $aSouthwest Amazon
653 $aSpatial scale
653 $aSpecies distribution models
653 $aSudoeste da Amazônia
700 1 $aVENTICINQUE, E. M.
700 1 $aFIGUEIREDO, E. O.
773 $tRevista Árvore, Viçosa$gv. 40, n. 4, p. 617-625, 2016.
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Embrapa Acre (CPAF-AC) |
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