AUTHOR=Xiang Ganju , Jiang Yunyi , Lan Jinmao , Huang Liuying , Hao Lijun , Liu Zhiqian , Xia Jing 

TITLE=Different influences of phylogenetically conserved and independent floral traits on plant functional specialization and pollination network structure

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1084995

DOI=10.3389/fpls.2023.1084995

ISSN=1664-462X

ABSTRACT=Plant specialization and pollination network structure play important roles in community assembly. Floral traits, such as floral size, floral shape and flower density, are considered to have important impacts on structure of plant-pollinator network. Some floral traits are phylogenetically conserved, some are phylogenetically independent. However, whether these two types of floral traits have different effects on plant-pollinator the network need to be explored. Here, we collected data about the 66 plants species in a grassland-dominant community during three field seasons to evaluate the effect of phylogeny on floral traits (floral size, floral shape and flower density). Then, we used phylogenetic structural equation models (PSEMs) to illustrate the pattern through floral trait(s), which had phylogenetic constraints, affected the network metrics (species’ specialization: species’ strength, weighted closeness and d’ ,and species’ contribution to network: nestedness and modularity contribution). Results of PSEM revealed phylogenetic conserved floral size had much more complexed influences, being important in all network metrics measured as pollination specialization and having a direct influence on influence on species’ specialization and modularity contribution. Our results demonstrated that phylogenetically conserved traits which share evolutionary history with their pollinators (pollination syndrome) are important divers of local network structure. This study may improve the understanding how the evolutionary history and ecological process drive local network structure and dynamics.