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

Author(s)

Bispo, Polyanna da Conceicao ^{[1, 2]} ; Balzter, Heiko ^{[1, 2]} ; Malhi, Yadvinder ^[3] ; Slik, J. W. Ferry ^[4] ; dos Santos, Joao Roberto ^[5] ; Renno, Camilo Daleles ^[6] ; Espirito-Santo, Fernando D. ^[7] ; Aragao, Luiz E. O. C. ^{[8, 5]} ; Ximenes, Arimatea C. ^{[9, 10]} ; Bispo, Pitagoras da Conceicao ^[11]

Affiliation:Show less -

^[1] Univ Leicester, Dept Geog, Ctr Landscape & Climate Res, Leicester Inst Space & Earth Observ, Leicester, Leics - England

^[2] Univ Leicester, Natl Ctr Earth Observ, NERC, Leicester, Leics - England

^[3] Univ Oxford, Sch Geog & Environm, Environm Change Inst, Oxford - England

^[4] Univ Brunei Darussalam, Fac Sci, Gadong - Brunei

^[5] Natl Inst Space Res INPE, Remote Sensing Div, Sao Jose Dos Campos - Brazil

^[6] Natl Inst Space Res INPE, Image Proc Div, Sao Jose Dos Campos - Brazil

^[7] Univ Lancaster, Lancaster Environm Ctr, Lancaster - England

^[8] Univ Exeter, Coll Life & Environm Sci, Exeter, Devon - England

^[9] Univ Libre Bruxelles, Dept Biol Organisms, Lab Syst Ecol & Resource Management, Brussels - Belgium

^[10] Vrije Univ Brussel, Lab Plant Biol & Nat Management Ecol & Biodivers, Brussels - Belgium

^[11] State Univ Sao Paulo UNESP, Fac Sci & Languages Assis, Dept Biol Sci, Assis - Brazil

• Document type: Journal article
• Source: PLoS One; v. 12, n. 11 NOV 20 2017.
• Web of Science Citations: 4

Abstract

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. (AU)

• FAPESP's process: 15/50392-8 - Fernando Espírito Santo | Lancaster University - Inglaterra
• Grantee: Tomas Ferreira Domingues
• Support Opportunities: Research Grants - Visiting Researcher Grant - International