Drivers of metacommunity structure diverge for common and rare Amazonian tree species.
journal contributionposted on 2018-01-09, 15:12 authored by Polyanna da Conceição Bispo, Heiko Balzter, Yadvinder Malhi, J. W. Ferry Slik, João Roberto Dos Santos, Camilo Daleles Rennó, Fernando D. Espírito-Santo, Luiz E. O. C. Aragão, Arimatéa C. Ximenes, Pitágoras da Conceição Bispo
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.
PCB was supported by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 660020. HB was supported by Royal Society Wolfson Research Merit Award (2011/R3) and by the Natural Environment Research Council’s National Centre for Earth Observation. PITCB, JRS and LEOCA were supported by CNPq National Council for Scientific and Technological Development) productivity fellowships (grants 305275/2014-3, 303228/2013-0 and 305054/2016-3, respectively). FDES was supported by Natural Environment Research Council (NERC) grants (BIO-RED NE/N012542/1 and AFIRE NE/P004512/1) and Newton Fund (The UK Academies/FAPESP Proc. N˚: 2015/50392-8 Fellowship and Research Mobility)
CitationPLoS One, 2017, 12 (11), e0188300.
Author affiliation/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment/GIS and Remote Sensing
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