Summary bipartite networks: trees in Romanian forests – wood pathogenic and sapro-pathogenic fungi

The assembly of plant pathogenic communities is one of the central topics in community ecology. Based on collected metadata, a summary host-pathogen bipartite network was constructed, and network metrics such as connectance, node degree distribution, nestedness and modularity were employed to verify the non-random nature of host-pathogen interactions. The selected hosts ( Quercus robur, Q. cerris, Q. frainetto, Q. pubescens, Q. petraea, Fagus sylvatica and Picea abies ) are tree species characteristic for European forest ecosystems, covering large areas of Central and South-Eastern Europe including Romania. The selected tree species (based on their dominance in forest ecosystems) establish 109 forest ecosystem types in Romanian forest ecosystems’ typology. 105 species of wood pathogens and sapro-pathogens, covering whole area of Europe, were retrieved from published papers. The established bipartite network of wood pathogens and sapro-pathogens and their tree hosts was significantly modular, displaying four modules (Q network = 0.24) and significantly nested (N network = 0.67), presented power law degree distribution, a common topology with mutualistic networks. Network topological characteristics generally encountered in parasitic networks described in literature, confirm the non-random assembly of the wood and bark pathogenic communities. Non-metric Multidimensional Scaling (NMDS) performed on wood pathogens ‘matrix and forest types’ matrix showed high resemblance in the positioning pattern of trees in ordination space. Mantel test confirmed the NMDS result - a significant correlation between similarities in pathogen share and similarities in tree composition of the forest ecosystems in Romanian forest classification. The network architecture resembles other published networks depicting symbiotic interactions. As tree species assemble in distinct forest types, the transmission of emerging or invasive pathogens is expected to continue in the future due to modular nature of the networks, triggered by major climatic changes.