Accepted author manuscript, 4.27 MB, PDF document
Available under license: CC BY-NC-ND
Final published version, 4.55 MB, PDF document
Available under license: CC BY: Creative Commons Attribution 4.0 International License
Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Drivers of metacommunity structure diverge for common and rare Amazonian tree species
AU - da Conceição Bispo, Polyanna
AU - Balzter, Heiko
AU - Malhi, Yadvinder
AU - Ferry Silk, J. W.
AU - Santos, João Roberto dos
AU - Renno, Camilo Daleles
AU - Espirito-Santo, Fernando
AU - Aragão, Luiz
AU - Ximenes, Arimatea C.
AU - da Conceição Bispo, Pitágoras
PY - 2017/11/20
Y1 - 2017/11/20
N2 - 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 vari- ables (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 (standard- ised 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 spe- cies. 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. How- ever, 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 pro- cesses underlying the diversity of tropical forest communities.
AB - 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 vari- ables (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 (standard- ised 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 spe- cies. 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. How- ever, 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 pro- cesses underlying the diversity of tropical forest communities.
KW - Amazon
KW - tropical forests
KW - remote sensing
KW - ecology
U2 - 10.1371/journal.pone.0188300
DO - 10.1371/journal.pone.0188300
M3 - Journal article
VL - 12
JO - PLoS ONE
JF - PLoS ONE
SN - 1932-6203
IS - 11
M1 - e0188300
ER -