Abstract

Mutualistic interactions are currently mapped by bipartite net- works with particular architecture and properties. The mycorrhizae con- nect the trees and permit them to share resources, therefore relaxing the competition. Ectomycorrhizal macrofungi associated with woody species (Quercus robur, Q. cerris, Q. petraea, Tilia tomentosa, Carpinus betulus, Corylus avellana, and Q. pubescens) growing in a temperate, broadleaved mixed forest, from a hilly area near the city of Cluj-Napoca, central Roma- nia were included in a bipartite mutualistic network. Community structure was investigated using several network metrics, modularity and nestedness algorithms in conjunction with C-score index cluster analysis and nonmet- ric multidimensional scaling (the Kulczynski similarity was index used as most appropriate metric selected by minimal stress criterion). The results indicate that the network presents high asymmetry (hosts are outnumbered by mycobionts at a great extent), high connectance, low modularity, and high nestedness, competition playing a secondary role in community as- semblage (non significant difference between simulated and observed C- score). The nestedness pattern is non-random and is comparable to previ- ously published results for other similar interactions containing plants. In the proposed network, woody species function exclusively as generalists. Modularity analysis is a finer tool were identifying species roles than cen- trality measures, however, the two types of algorithms permit the separation of species according to their roles as for example connectors (generalist spe- cies) and ultraperipheral species (specialists). Supergeneralist woody spe- cies function as hubs for the diverse ectomycorrhizal community while su- pergeneralist ectomycorrhizal fungi glue the hubs into a coherent aggregate. Keywords temperate broadleaved mixed forest, ectomycorrhizal fungi, mu- tualistic bipartite networks, nestedness, modularity, connectance, C-score cluster analysis, non metric multidimensional scaling.

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