Duas Abordagens na Modelagem da Distribuição de Aves na Amazônia: Áreas de Endemismo versus Variáveis Abióticas
The birds besides being one of the most representative taxonomic groups of the Amazon, are not yet known aspects related with its the distribution and ecological and historical factors that can determine it. In general, to model their distribution are used climatic and environmental variables dep...
| Autor principal: | Ruiz Ovalle, Juan Miguel |
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| Grau: | Dissertação |
| Idioma: | por |
| Publicado em: |
Instituto Nacional de Pesquisas da Amazônia - INPA
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/12027 http://lattes.cnpq.br/5570642353858083 |
| Resumo: |
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The birds besides being one of the most representative taxonomic groups of the Amazon, are
not yet known aspects related with its the distribution and ecological and historical factors
that can determine it. In general, to model their distribution are used climatic and
environmental variables depending on the scale, that can not clearly explain its distribution.
Thus, the aim of this study was to determine how models based on three different approaches,
predict the spatial distribution of species of Amazonian birds in areas with different
biogeographic characteristics. First was made species distribution models using layers of
polygons of Amazon Birds endemism areas and distribution of flooded environments. Later,
were built models with climate and topography variables, using the mathematical algorithm of
maximum entropy (MAXENT). There were no significant differences between the two
approaches to Topaza pyra, Rhegmatorhina gymnops, Touit huetii, Lophotriccus galeatus and
Knipoleugus orenocensis and could not identify a pattern to identify in general which the
predictions were the most likely. It was found that for T. pyra, R. gymnops and T. huetii
models made with areas of endemism (MAE) were more likely than models with abiotic
variables (MVA). In turn, the abiotic variables models (MVA) were more likely than
endemism areas models (MAE) for L. galeatus, T. pyra, R. melanosticta and Knipolegus
orenocensis. In general all models showed high performance values, and only for Heliodoxa
schreibersii and Synallaxis propinqua the failure rate was higher than the sensitivity. We
conclude that in general none of the two approaches were more likely than the other. Still you
need to understand how they interact the two approaches in traditional sets models, extending
the analysis to other species and achieve greater quantity and quality of data and
environmental information to make more accurate and reliable inferences about the
predictions of distribution and draw definitive conclusions. |