dc.contributorUniversidade Federal de Alfenas
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade Federal de Goiás (UFG)
dc.contributorUniversidade Federal de Lavras (UFLA)
dc.contributorEstação de Hidrobiologia e Piscicultura de Furnas – EHPF
dc.date.accessioned2018-12-11T17:10:56Z
dc.date.available2018-12-11T17:10:56Z
dc.date.created2018-12-11T17:10:56Z
dc.date.issued2017-09-01
dc.identifierJournal of Forestry Research, v. 28, n. 5, p. 963-974, 2017.
dc.identifier1993-0607
dc.identifier1007-662X
dc.identifierhttp://hdl.handle.net/11449/174401
dc.identifier10.1007/s11676-017-0388-5
dc.identifier2-s2.0-85016560633
dc.identifier2-s2.0-85016560633.pdf
dc.description.abstractSpecies distribution models are used to aid our understanding of the processes driving the spatial patterns of species’ habitats. This approach has received criticism, however, largely because it neglects landscape metrics. We examined the relative impacts of landscape predictors on the accuracy of habitat models by constructing distribution models at regional scales incorporating environmental variables (climate, topography, vegetation, and soil types) and secondary species occurrence data, and using them to predict the occurrence of 36 species in 15 forest fragments where we conducted rapid surveys. We then selected six landscape predictors at the landscape scale and ran general linear models of species presence/absence with either a single scale predictor (the probabilities of occurrence of the distribution models or landscape variables) or multiple scale predictors (distribution models + one landscape variable). Our results indicated that distribution models alone had poor predictive abilities but were improved when landscape predictors were added; the species responses were not, however, similar to the multiple scale predictors. Our study thus highlights the importance of considering landscape metrics to generate more accurate habitat suitability models.
dc.languageeng
dc.relationJournal of Forestry Research
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectEcological niche model
dc.subjectGeneralized linear models
dc.subjectHabitat suitability
dc.subjectLandscape structure
dc.subjectMaxent
dc.titleAdditions of landscape metrics improve predictions of occurrence of species distribution models
dc.typeArtículos de revistas


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