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.

Our research group has recently proposed a strategy to simulate net forest carbon fluxes based on the coupling of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC. The outputs of the two models are combined through the use of a proxy of ecosystem distance from equilibrium condition which accounts for the occurred disturbances. This modeling strategy is currently applied to all Italian forest areas using an available set of NDVI images and ancillary data descriptive of an 8-year period (1999–2006). The obtained estimates of forest net primary production (NPP) are first analyzed in order to assess the importance of the main model drivers on relevant spatial variability. This analysis indicates that growing stock is the most influential model driver, followed by forest type and meteorological variables. In particular, the positive influence of growing stock on NPP can be constrained by thermal and water limitations, which are most evident in the upper mountain and most southern zones, respectively. Next, the NPP estimates, aggregated over seven main forest types and twenty administrative regions in Italy, are converted into current annual increment of standing volume (CAI) by specific coefficients. The accuracy of these CAI estimates is finally assessed by comparison with the ground data collected during a recent national forest inventory. The results obtained indicate that the modeling approach tends to overestimate the ground CAI for most forest types. In particular, the overestimation is notable for forest types which are mostly managed as coppice, while it is negligible for high forests. The possible origins of these phenomena are investigated by examining the main model drivers together with the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis. © 2015, Springer-Verlag Berlin Heidelberg.

This review presents a multidisciplinary framework for integrating the ecological, regulatory, procedural and technical aspects of forest management for fires prevention under Mediterranean environments. The aims are to: i) provide a foreground of wildfire scenario; ii) illustrate the theoretical background of forest fuel management; iii) describe the available fuel management techniques and mechanical operations for fire prevention in forest and wildland-urban interfaces, with exemplification of case-studies; iv) allocate fire prevention activities under the hierarchy of forest planning. The review is conceived as an outline commentary discussion targeted to professionals, technicians and government personnel involved in forestry and environmental management.

Accurate estimates of leaf area index (L) are strongly required for modelling ecophysiological processes within urban forests. The majority of methods available for estimating L is ideally applicable at stand scale and is therefore poorly suitable in urban settings, where trees are typically sparse and isolated. In addition, accurate measurements in urban settings are hindered by proximity of trees to infrastructure elements, which can strongly affect the accuracy of tree canopy analysis.In this study we tested whether digital photography can be used to obtain indirect estimate of L of isolated trees. The sampled species were Platanus orientalis, Liquidambar styraciflua and Juglans regia. Upward-facing photography was used to estimate gap fraction and foliage clumping from images collected in unobstructed (open areas) and obstructed (nearby buildings) settings; two image classification methods provided accurate estimates of gap fraction, based on comparison with measurements obtained from a high quality quantum sensor (LAI-2000). Leveled photography was used to characterize the leaf angle distribution of the examined tree species. L estimates obtained combining the two photographic methods agreed well with direct L measurements obtained from harvesting. We conclude that digital photography is suitable for estimating leaf area in isolated urban trees, due to its simple, fast and cost-effective procedures. Use of vegetation indices allows extending significantly the applicability of the photographic method in urban settings, including green roofs and vertical greenery systems. © 2015 Elsevier GmbH.

This study analyses spatio-temporal patterns of wildfires in Greece using a multidimensional statistical framework based on non-parametric correlations, principal component analysis, clustering and stepwise discriminant analysis. Specifically, we assess the frequency, seasonal profile, severity and land-use type of 135 178 wildfires which occurred between 2000-2012 in Greece, one of the countries most affected by fire in Europe. Our results show that both the number of fires and the average size of the area covered by fire show a specific seasonal pattern with a marked increase during the dry season. Principal component analysis identifies three dimensions linked with the main type of land-use affected by the fires: (i) medium and large fires primarily affected landscapes composed of forests, mixed woodlands/shrublands and croplands; (ii) small fires mainly affected fragmented landscapes, i.e. those with mosaics of different crops, market gardens and non-vegetated, abandoned or marginal areas; (iii) fires affecting wetlands and pastures occurred particularly in late summer and showing medium-low severity. Hierarchical clustering highlights similarities in spatio-temporal patterns between fire indicators (ignition date, burnt land cover classes, fire size, fire density). K-means clustering allows us to distinguish between low-severity fires occurring in the wet season from intense and frequent fires occurring in the dry season but with distinct land-use selectivity. The research reported here contributes insight into the complexity of wild fires in the Mediterranean region and supports the design of more effective fire prevention measures including sustainable forest management practices and careful regional planning to minimise risk factors.

Today wood and nonwood forest resources management meets and often clashes with environment and biological diversity protection. A main problem is to understand relationships between the different roles of forest biodiversity, site, and management parameters. A multivariate statistical analysis has been carried out in order to interpret relationships between some forest biodiversity components and forest inventory data. Several indices of floristic diversity, species abundance, and structural heterogeneity at stand level have been calculated. The different components of forest biodiversity were separated by principal components analysis. Relations between forest biodiversity indices and site and management attributes have been investigated by two multivariate statistical techniques: bivariate correlation analysis and multiple linear regression. Results showed a high correlation between all the investigated components of forest biodiversity and some topographic and/or forest management attributes. Results also gave ancillary information to define sustainable forest management criteria. © 2014 Società Botanica Italiana.

This paper reviews the literature relating to the relationship between light availability in the understory and the main qualitative and quantitative attributes of stand overstory usually considered in forest management and planning (species composition, density, tree sizes, etc.) as well as their changes as consequences of harvesting. The paper is divided in two sections: the first one reviews studies which investigated the influence of species composition on understory light conditions; the second part examines research on the relationships among stand parameters determined from mensurational field data and the radiation on understory layer. The objective was to highlight which are the most significant stand traits and management features to build more practical models for predicting light regimes in any forest stand and, in more general terms, to support forest managers in planning and designing silvicultural treatments that retain structure in different way in order to meet different objectives.