There is increasing awareness that structure-based indicators should be considered for assessing the biological value of late successional forests. In order to increase the unique habitat features critical for old-growth associated species, it is important to identify and rank candidate potential forest sites on the basis of their distinctive structural features. Data on living and deadwood components for the identification of old-growth condition are usually acquired in the considered forest stands by two sampling survey: (i) census performed in relatively large monitoring sites; (ii) network of small sampling units, on which inventory practices are usually based. Several authors argued that choosing between these survey strategies might have substantial effects on the values of common indicators of old-growth condition. Our study aims at (i) assessing the total estimate differences among old-growth structural indicators measured in field plots with different sizes, and (ii) defining the optimal sample size for the reliable assessment of such indicators. The study was carried out in six beech dominated forest stands on the Apennines range in Italy. In each stand, living and deadwood components were surveyed and geocoded in 1-ha square areas. Based on these dataset, circular plots with radii ranging from 4m up to 20m were then considered in order to quantify the effect of sampling plot size on the estimation of four structural indicators: (1) number of living trees; (2) number of large trees (dbh≥50cm); (3) total deadwood volume; (4) number of deadwood elements (snags, dead standing trees; lying dead trees, lying deadwood) with dbh (or average diameter for lying deadwood) ≥ 30cm. We found that the size of the sampling plots should be at least 500 m² in order to establish a database for the assessment of the investigated indicators. The census approach should be preferred to the sampling plot approach for old-growth forest stands smaller than 3-5ha. The achieved results contribute to define assessment protocols for characterizing and ranking the degree to which forest stands approximate old-growth condition based on standardized indicators. © 2015 Elsevier B.V.

The "Bosco Fontana" natural reserve includes the last remaining mixed floodplain forest in northern Italy and one of the most endangered ecosystems in Europe. Its effective management is hindered by the complexity of interactions of mixed-tree species and the influence of environmental factors on understory plant diversity. In this study we analyzed the patterns of natural evolution in semi-natural floodplain forest stands at Bosco Fontana with the aim of better understanding its current natural processes and dynamics. Stand structure, taxonomic and functional diversity, species composition, and leaf area index (LAI) of overstory and understory layers were surveyed in permanent plots over two inventory years (1995, 2005). The influence of environmental factors on understory plant diversity was assessed using Ellenberg’s indices for light, soil moisture, soil nutrient and soil reaction. Results indicated that overstory species composition varies according to the soil moisture, with hornbeam prevailing in xeric sites and deciduous oak species in mesic sites. Xeric sites showed high functional dispersion in both drought and shade tolerant traits, while it was significantly lower in both overstory and understory in the moist site. Functional dispersion of drought tolerance in the overstory and understory layers was positively correlated, while species richness was negatively correlated between the two layers. Diversity in the understory was mainly correlated with soil conditions. Understory LAI was positively correlated with overstory LAI in xeric and mesic plots, while no correlations were found in the moist plot. Overall, our results suggest that site conditions (soil conditions and water availability) are the major drivers of understory and overstory dynamics in the study forest. Hence, local site conditions and the understory should be carefully considered in the management of mixed floodplain forests. © SISEF.