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Structural equation modelling analysis of evolutionary and ecological patterns in Australian Banksia
Author(s) -
He Tianhua
Publication year - 2013
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/s10144-013-0376-3
Subject(s) - banksia , biology , genetic diversity , ecology , resistance (ecology) , range (aeronautics) , evolutionary ecology , evolutionary biology , host (biology) , demography , population , materials science , sociology , composite material , woodland
Evolutionary history of species, their geographic ranges, ecological ranges, genetic diversity, and resistance to pathogen infection, have been viewed as being mutually linked through a complex network of interactions. Previous studies have described simple correlations between pairs of these factors, while rarely separated the direct effects among multiple interacting factors. This study was to separate the effect of multiple interacting factors, to reveal the strength of the interactions among these factors, and to explore the mechanisms underlying the ecological and evolutionary processes shaping the geographic range, genetic diversity and fitness of species. I assembled comparative data on evolutionary history, geographic range, ecological range, genetic diversity, and resistance to pathogen infection for thirteen Banksia species from Australia. I used structural equation modelling to test multivariate hypotheses involving evolutionary history, geographic range, genetic diversity and fitness. Key results are: (1) Species with longer evolutionary times tend to occupy larger geographic ranges; (2) higher genetic diversity is directly associated with longer flowering duration in Banksia ; and (3) species with higher genotypic diversity have higher level of resistance to infection caused by the pathogen Phytophthora cinnamomi, whereas heterozygosity has the opposite relationship with capacity of resistance to the infections caused by this pathogen. These results revealed a mutually linked and complex network of interactions among gene, species, environment and pathogen in evolutionary and ecological scales. These findings also have great practical significance and help to provide preemptive management options in pathogen control.