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Fungal endophytes associated with three South American Myrtae (Myrtaceae) exhibit preferences in the colonization at leaf level
Authors:Aline BM Vaz  Andre GFC da Costa  Lucélia VV Raad  Aristóteles Góes-Neto
Institution:1. Laboratório de pesquisa em Microbiologia (LAPEM), Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil;2. Centro de Pesquisas René Rachou (CPqRR), Fundação Oswaldo Cruz (FIOCRUZ), Belo Horizonte, Minas Gerais, Brazil;3. Departamento de Estatística, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil;4. Instituto de Economia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
Abstract:Fungal endophytes associated with Myrtaceae from Brazil and Argentina were isolated at three levels of nesting: leaf, individual host trees, and site collection. The alternating logistic regression (ALR) was used to model the data because it offers a computationally convenient method for fitting regression structures involving large clusters. The objectives of this study were to determine: (i) whether the colonization pattern is influenced by environmental variables, (ii) if there is some leaf part they prefer to colonize; (iii) if there is some fungal endophyte aggregation between hierarchical levels; (iv) what the distance effect is on the fungal association. The environmental variables were statistically significant only for Xylaria, i.e., when the elevation and water precipitation increase and the temperature decreases, the odds ratio of finding another fungal endophyte of that genus previously found increases. Sordariomycetes, Xylariales, and Xylaria exhibited leaf fragment preference to petiole and tip. Fungal endophytes showed association within leaf. The horizontal transmission mode and the dispersal limitation may explain this association at the leaf level. Moreover, our results suggest that when a fungal endophyte infects a leaf or host tree individual, the odds ratio of dispersal inside them is greater.
Keywords:Alternating logistic regression  Clustered responses  Fungal distribution  Endophytic fungi  Statistical modelling
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