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Avian Communities in the Amazonian Cangas Vegetation: Biogeographic Affinities, Components of Beta-Diversity and Conservation

Overview of attention for article published in Anais da Academia Brasileira de Ciências, August 2017
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Title
Avian Communities in the Amazonian Cangas Vegetation: Biogeographic Affinities, Components of Beta-Diversity and Conservation
Published in
Anais da Academia Brasileira de Ciências, August 2017
DOI 10.1590/0001-3765201720160048
Pubmed ID
Authors

SÉRGIO H. BORGES, MARCOS P.D. SANTOS, LEONARDO M.S. SOARES, ANTONITA S. DA SILVA

Abstract

The Amazonian cangas is a vegetation type distributed as patches of open vegetation embedded in a matrix of tropical forest and that grows over iron-rich soils in the Serra dos Carajás region. To characterize cangas avifauna, we surveyed birds in eight patches varying from 43 to 1,366 hectares. Cangas avifauna has compositional affinities with savannas widespread throughout the Amazon and other biomes, and we estimate that more than 200 bird species occurs in this habitat. Species composition was relatively homogeneous, and the similarity among cangas patches was the dominant component of the beta-diversity. Bird communities in cangas patches exhibited statistically significant nested structure in respect to species richness and patch size. In contrast, the nested site arrangement was not affected by the isolation of patches. Number of species and composition are moderately affected by the area of cangas patches but not by its degree of isolation. To conserve this unique habitat are necessary a strict protection of carefully chosen patches of cangas and an investigation of the conservation value of secondary vegetation recovered by the mining companies.

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Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Bachelor 5 19%
Student > Master 4 15%
Student > Doctoral Student 2 8%
Other 1 4%
Other 1 4%
Unknown 8 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 35%
Environmental Science 3 12%
Arts and Humanities 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Computer Science 1 4%
Other 2 8%
Unknown 9 35%