Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1056281
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dc.contributor.authorFIGUEIREDO, S. M. de M.pt_BR
dc.contributor.authorVENTICINQUE, E. M.pt_BR
dc.contributor.authorFIGUEIREDO, E. O.pt_BR
dc.date.accessioned2016-11-11T11:11:11Zpt_BR
dc.date.available2016-11-11T11:11:11Zpt_BR
dc.date.created2016-11-11pt_BR
dc.date.issued2016pt_BR
dc.identifier.citationRevista Árvore, Viçosa, v. 40, n. 4, p. 617-625, 2016.pt_BR
dc.identifier.issn0100-6762pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1056281pt_BR
dc.descriptionKnowledge 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.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectEscala espacialpt_BR
dc.subjectSpatial scalept_BR
dc.subjectInterpolaçãopt_BR
dc.subjectInterpolationpt_BR
dc.subjectInterpolaciónpt_BR
dc.subjectModelo de distribuição de espéciespt_BR
dc.subjectSpecies distribution modelspt_BR
dc.subjectModelos de distribución de especiespt_BR
dc.subjectSudoeste da Amazôniapt_BR
dc.subjectSouthwest Amazonpt_BR
dc.subjectSimulación por computadorapt_BR
dc.subjectMadera tropicalpt_BR
dc.subjectInventario forestalpt_BR
dc.titleSpatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2017-06-08T11:11:11Zpt_BR
dc.subject.thesagroEssência florestalpt_BR
dc.subject.thesagroInventário florestalpt_BR
dc.subject.thesagroPopulação de plantapt_BR
dc.subject.thesagroModelo de simulaçãopt_BR
dc.subject.thesagroPrograma de computadorpt_BR
dc.subject.thesagroFlorapt_BR
dc.subject.nalthesaurusTropical woodpt_BR
dc.subject.nalthesaurusForest inventorypt_BR
dc.subject.nalthesaurusComputer simulationpt_BR
riaa.ainfo.id1056281pt_BR
riaa.ainfo.lastupdate2017-06-08pt_BR
dc.identifier.doi10.1590/0100-67622016000400005pt_BR
dc.contributor.institutionSymone Maria de Melo Figueiredo, Universidade Federal do Acre; Eduardo Martins Venticinque, Universidade Federal do Rio Grande do Norte; EVANDRO ORFANO FIGUEIREDO, CPAF-Acre.pt_BR
Aparece nas coleções:Artigo em periódico indexado (CPAF-AC)

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