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Summary1. We attempted to elucidate the roles of b-diversity components and similarity in shaping Lobaria pulmonaria lichen communities in Italian forests to provide scientific tools for improving their longterm conservation. 2. A total of 20 sites were selected by stratified random sampling, including five chestnut forests, seven beech-silver fir forests and eight oak forests distributed across 10 administrative regions of Italy. Site selection was based on a national data base including all the available records of L. pulmonaria in Italy. In each forest, four plots were randomly placed, and in each plot, 5-6 trees were randomly selected for lichen sampling. For each forest and plot, meaningful predictors of lichen patterns were quantified. In particular, factors indicative of both geographic conditions and forests structure were considered. The SDR simplex approach was used to estimate the relative importance of similarity (S), relative species replacement (R) and relative richness difference (D) to b-diversity and similarity, while a hierarchical partitioning (HP) method was used to evaluate the relative importance of environmental predictors in explaining their patterns. 3. A total of 201 lichens and three nonlichenized fungi were found, including 51 species of conservation concern. The components of b-diversity and similarity contributed to shaping L. pulmonaria communities at both forest and plot scales across Italy, resulting in nearly random compositions, that is, the species set on each tree was a random sample from the available species pool. Species replacement and similarity were generally associated with forest structure predictors, while richness difference was mainly associated with geographic predictors. The implication of this is that the long-term conservation of L. pulmonaria communities could be promoted by maintaining scattered nodes and appropriate habitat traits, especially in large forested landscapes where species turnover is higher. 4. Synthesis. In this work, we used a new approach for analysing a countrywide data set improving the ecological understanding of the dynamics regulating epiphytic communities. In particular, this study improves the understanding of the contribution of different components of diversity across two spatial scales and evaluates the relative importance of environmental predictors in explaining variation of each diversity component.