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Wood-inhabiting fungi are major decomposers of organic matter in forest systems, playing a crucial role for the maintenance of critical ecosystem processes. Despite their importance, very few studies have investigated wood-inhabiting fungi with biomolecular techniques, especially in Southern Europe. We studied deadwood quality along with stand structural attributes and local ecological parameters to disentangle the relationships between forest habitat characteristics and fungal community structure. Wood samples were collected from 72 lying dead logs in four forest reserves located along a latitudinal transect on the Italian Peninsula. The sites differed in tree species composition, management history and successional stage. The fungal community was investigated through fingerprinting analysis while physical properties of deadwood logs and structural attributes of the stands were assessed in the field. In addition, lignin, carbon and nitrogen content were analyzed for each sampled log. Our results indicate that the combination of structural and morphological aspects of the study areas played a great role in differentiating the fungal communities across these unmanaged forests. Among the wood chemical characteristics, only lignin content significantly affected the overall community structure, suggesting a role of decay stage and tree species in selecting specific fungal taxa. Climatic factors were found to be important only for fungal species diversity and was positively influenced by mean annual precipitation and negatively related to temperature annual range. Nevertheless, a mixed effect model showed a greater impact of living tree species richness in predicting fungal diversity within logs. Our findings suggest that decomposer communities respond to environmental changes at different spatial scales and that the structural and ecological heterogeneity of forest systems subjected to natural dynamics for a longer period support a more diverse fungal community. [ABSTRACT FROM AUTHOR]

A methodological approach based on detailed land-use map, high-resolution LiDAR data and field surveys was developed to categorize productive and non-productive mixed forests, both in term of stand attributes and structural diversity. In 2011, leaf-off dedicated airborne LiDAR data were collected in a 20,000 ha inland patchy area which was representative of soil land use in the Apennines mountains of southern Italy. By combining field and LiDAR data in 5574 ha of forests with coexisting evergreen and deciduous species, we modelled common forest stand variables (height, diameter, volume and biomass) with high accuracy (0.60 ≤ Adj.R 2 ≤ 0.89). Moreover, a moderate correlation (0.425 ≤ τ ≤ 0.462) between field- and LiDAR-derived diversity indices was found. About 3393 ha of forests are enclosed in protected areas of the Natura 2000 network, which in turn possesses 77% (~ 576,286 Mg) of total aboveground dry biomass. Overall, eight forest types were identified, one of which, the European beech, is only found in the Natura 2000 sites, while other forest types are also found elsewhere. This is the first study to undertake a LiDAR analysis of Mediterranean forests in the Campania Region and might help better evaluate trade-off, especially in protected areas, in order to enhance multiple benefits and support sustainable management of forests. [ABSTRACT FROM AUTHOR]