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Drivers of metacommunity structure diverge for common and rare Amazonian tree species

Bispo, Polyanna da Conceição ; Balzter, Heiko ; Malhi, Yadvinder ; Slik, J W Ferry ; Santos, João Roberto ; Rennó, Camilo Daleles ; Espírito-Santo, Fernando D ; Aragão, Luiz E O C ; Ximenes, Arimatéa C ; Bispo, Pitágoras da Conceição Zang, RunGuo

PloS one, 2017-11, Vol.12 (11), p.e0188300-e0188300 [Periódico revisado por pares]

United States: Public Library of Science

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Título:
Drivers of metacommunity structure diverge for common and rare Amazonian tree species
Autor: Bispo, Polyanna da Conceição ; Balzter, Heiko ; Malhi, Yadvinder ; Slik, J W Ferry ; Santos, João Roberto ; Rennó, Camilo Daleles ; Espírito-Santo, Fernando D ; Aragão, Luiz E O C ; Ximenes, Arimatéa C ; Bispo, Pitágoras da Conceição
Zang, RunGuo
Assuntos: Abundance ; Biodiversity ; Biology and Life Sciences ; Biomass ; Brazil ; Communities ; Composition effects ; Earth Sciences ; Ecology ; Ecology and Environmental Sciences ; Environmental conditions ; Flora ; Forest communities ; Forests ; Incidence ; Laboratories ; Matrix methods ; Multivariate analysis ; Old growth ; Old growth forests ; Partitions ; Plants ; Plants (Organisms) ; Rare species ; Redundancy ; Regression analysis ; Remote sensing ; Researchers ; Spatial Analysis ; Studies ; Theory ; Topographic effects ; Topography ; Trees ; Trees - physiology ; Tropical Climate ; Tropical forests ; Vegetation
É parte de: PloS one, 2017-11, Vol.12 (11), p.e0188300-e0188300
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Competing Interests: The authors have declared that no competing interests exist.
Descrição: We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.
Editor: United States: Public Library of Science
Idioma: Inglês

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Drivers of metacommunity structure diverge for common and rare Amazonian tree species

Bispo, Polyanna da Conceição ; Balzter, Heiko ; Malhi, Yadvinder ; Slik, J W Ferry ; Santos, João Roberto ; Rennó, Camilo Daleles ; Espírito-Santo, Fernando D ; Aragão, Luiz E O C ; Ximenes, Arimatéa C ; Bispo, Pitágoras da Conceição Zang, RunGuo

United States: Public Library of Science

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