Key message: Trees outside forests (TOF) have crucial ecological and social-economic roles in rural and urban contexts around the world. We demonstrate that a large-scale estimation strategy, based on a two-phase inventory approach, effectively supports the assessment of TOF’s diversity and related climate change mitigation potential. Context: Although trees outside forest (TOF) affect the ecological quality and contribute to increase the social and economic developments at various scales, lack of data and difficulties to harmonize the known information currently limit their integration into national and global forest inventories. Aims: This study aims to develop and test a large-scale estimation framework to assess ecological diversity and above-ground carbon stock of TOF. Methods: This study adopts a two-phase inventory approach. Results: In the surveyed territory (Molise region, Central Italy), all the attributes considered (tree abundance, basal area, wood volume, above-ground carbon stock) are concentrated in a few dominant species. Furthermore, carbon stock in TOF above-ground biomass is non-negligible (on average: 28.6 t ha⁻¹). Compared with the low field sampling effort (0.08% out of 52,796 TOF elements), resulting uncertainty of the estimators are more than satisfactory, especially those regarding the diversity index estimators (relative standard errors < 10%). Conclusion: The proposed approach can be suitably applied on vast territories to support landscape planning and maximize ecosystem services balance from TOF. © 2018, INRA and Springer-Verlag France SAS, part of Springer Nature.

The present study investigates some sampling strategies for the estimation of abundance and canopy cover of trees outside forest (TOF) over large areas. A collection of about 53 000 TOF units in Central Italy was acquired by visual, on-screen interpretation of aerial orthophotos and was taken as the reference population with the purpose of investigating: (i) one-phase inventories with sample points located by means of the tessellation stratified sampling (TSS), which involves covering the study region by a grid of regular polygons of equal sizes and randomly and independently selecting a point in each of them; (ii) two-phase inventories with the one-per-stratum stratified sampling adopted in the second phase to select a sample of polygons from the grid and then visit only the points contained in those polygons. Uniform random sampling is also considered in the first phase as a benchmark for tessellation stratified sampling. The sampling schemes adopted to select TOF units at the sample points are as follows: (i) point sampling, (ii) centroid-based plot sampling with plot radius of 50m(CPLS50) or 100 m, and (iii) plot intersect sampling with plot radius of 50 or 100 m. CPLS50 under single-phase TSS proves to be a promising strategy to large-scale TOF inventories. © 2016, Canadian Science Publishing. All rights reserved.

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.

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.

Purpose of Review: This paper aims to retrace the most significant management strategies adopted across European beech forests over the last 25 years, highlighting those that are most efficient and promising. We investigate five main topics including forest management, forest models, species mixture, genetic, and regeneration. Recent Findings: European beech is one of the most widespread and important tree species for the European forest sector. In the light of the ongoing climate crisis, understanding the growth dynamics and the response of beech forests to climate change is crucial to identify advantageous management strategies. Ecology, growth, management, distribution, interaction with other species, genetic, and regeneration aspects of European beech were investigated in different geographical areas of Europe. Despite recent researches focusing on climate change issues, how adaptation and mitigation measures can be integrated into silvicultural guidelines to improve the resilience of European beech forests remains unclear. Summary: To answer this question, we collected and reviewed articles about the management of European beech facing climate change, which were published in peer-reviewed journals over the last 25 years. Articles were grouped into five geographic European areas, according to the classification used by the State of Europe’s forests. Obtained articles were further clustered into five main topics: management, mixed forest, modelling, genetic, and regeneration. The review highlighted the importance of using long-term monitoring plots to understand the effect of climate change on the stability of European beech forests, suggesting climate-smart measures that would help these forests adapt to climate change. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

The interest in tree phenology monitoring is increasing because this trait is a robust indicator of the impacts of climate change on natural and managed ecosystems. Different approaches to monitor phenology at different spatial scales, from in situ monitoring to remote sensing, are used to investigate spring and/or autumn phenological changes. In Mediterranean area, most of phenological changes occur during cloudy periods (spring and autumn), leading to a loss of information also for very high temporal resolution satellites. Instead, cloud-uninfluenced sensors, such as radar sensors, can allow to bypass this problem and produce a temporally continuous coverage. In this paper, we analyzed the spring phenology of two European beech (Fagus sylvatica L.) populations, located at different latitudes in Mediterranean area. Weekly in situ monitoring of leaf-out has been correlated with data collected by Synthetic Aperture Radar. Spring phenological phases were monitored in situ following a modified BBCH-code with a 5-scores scale (from 1 - buds closed and covered by scales, to 5 - leaf completely unfolded). The score 3 (young leaves starting to emerge from the bud) was considered the bud break. Different site conditions based on aspect (northern and southern) and altitudinal gradient (high and low altitude) have been considered. The aim was to test and implement a new methodology able to decrease the frequency of the field sampling, using remote data, to extend more detailed information on geographical scale, and to reconstruct past phenology. Results showed a statistically significant different length of the vegetative spring period, spanning from dormant buds, up to leaves completely unfolded, between sites. Through Synthetic Aperture Radar estimation, this study demonstrates that leaf-out can be monitored with an extreme accuracy. The phenophase score 4 and 5 estimation showed the best performance (RMSE < of 4 days), phenophases score 2 and 3 showed promising performances (4 days < RMSE <5 days), while phenophases score 1 seems to be not easily detectable, although it can be extrapolated with an RMSE <6 days. This radar approach fixes the cloud problem typical of multispectral approach and very frequent in phenophase change periods in Mediterranean climate. This study promotes the proposed remote sensing approach as a very useful tool to monitor growing season starting in remote areas, helping to reduce in situ observations and allowing past phenology reconstruction. © 2020 Elsevier Inc.

To support sustainable forest management, planning policies and environmental actions, it is essential to have available common and standardized geospatial information on forest structure, composition and distribution. In this paper we present a harmonized forest categories (HFCs) map of four administrative Regions located in central Italy (i.e. Marche, Abruzzo, Lazio and Molise) at a scale of 1:400,000. The study area extends over 42,246 km², 14,878 km² of which are covered by forests. Four regional forest maps were harmonized in order to produce common standardized information on composition, structure and the distribution of forests in central Italy. A forest category is a forest vegetation unit defined by the main tree species composition. In this study we adopted a nomenclature scheme composed of 16 forest and shrubland categories. This work represents the first HFCs map in Italy over a large area. The legend is also harmonized with the European Environment Agency forest types nomenclature. © 2016 Nicolò Camarretta.

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.

In last decades, numerous efforts have been carried out by the scientific community to assess the multifunctional role of forests in supporting the forest decision-making processes. Recently developed in Italy, the Forest Landscape Management Planning seems to be the most suitable tool to maintain the sustainability balance between forests and local populations. This research identifies and maps different forest ecosystem functions in a mountain Natura2000 Network site by performing a spatial estimation of forest inventory parameters, and implementing a multi-criteria and multi-level approach. Final results on mapping of forest functions show acceptable values of classification accuracy. © 2014 University of Newcastle upon Tyne.

The availability of common standardized geospatial information on composition, structure and distribution of forests is essential to support environmental actions, sustainable forest management and planning policies. Forest types maps are suitable tools for supporting both silvicultural and forest planning choices from local to global scale levels. For this reason local authorities may develop forest types maps independently, in which case a standardized/harmonized framework for their comparison and aggregation is essential. At the same time local forest types maps may not be directly related to pan-European forest resources assessments and classification systems. This paper presents results of the harmonization of four forest types maps available for central Italy. The process is based on a bottom-up approach aimed at maintaining the most detailed common nomenclature system across the different Regions. The final results, in terms of forest types area, are compared with several independent sources of information: (i) two forest maps, one developed at national level on the basis of the Corine Land Cover 2006, and one for high resolution forest/non forest classification developed at pan-European level; and (ii) two sample based inventories: the Italian National Forest Inventory (INFC) and the Italian Land Use Inventory (IUTI). The results show that the proposed bottomup harmonization approach is a suitable tool to guarantee the integrity and homogeneity of local forest types nomenclature systems, and to integrate such local data with European standards. ©iForest – Biogeosciences and Forestry

A spatially explicit knowledge of forest resources is essential to support the sustainable use of wood as a fuel for producing energy (firewood).This paper describes the integrated use of remotely sensed data and sample based forest inventories to derive a biomass map for coppice forest, resulted estimated potential biomass available is contrasted with local domestic consumptions at the municipality level. The test was carried out in an environmentally and socially homogeneous district of Apennine Mountains (Alto Molise, south-central Italy) coupling multispectral high resolution Landsat 7 ETM+ satellite imagery and a local forest inventory trough the application of the non-parametric estimation procedure k-Nearest Neighbours (k-NN). Several forest management scenarios were applied in order to evaluate their impact on the potential availability of firewood from coppice forests.The paper introduces data and methods used and presents the achieved results both in terms of the accuracy of the biomass map produced by k-NN and of the relationship between the potential availability and demand for firewood.These results demonstrated that k-NN is able to estimate the biomass of coppice forest in the test area with an accuracy level comparable with recent similar application of k-NN carried out in Boreal regions (RMSE of 25.6%).The application of different forest management scenarios have a significant impact on local estimated firewood balance between potential supply from coppice forests and demand for domestic consumption, depending of the scenarios the net balance changed up to 84%. © 2010 Elsevier Ltd.

The most commonly used old-growth forest indicators are structural attributes; nevertheless, they do not necessarily represent the biodiversity value of old-growth forests. The aim of this study is to analyse the relationships between species richness data of different taxa and structural indicators of old-growth and to identify taxonomic/functional groups, species and structural attributes that may be used as indicators of old growth. To achieve this goal we sampled forest structure, vascular plants, lichens, bryophytes, fungi, saproxylic beetles and birds in mature and old-growth stands in southern Italy. We calculated Spearman's correlation coefficients between species richness data and structural attributes. Analyses of indicator species, co-occurrences and two-way clusters were performed on the multi-taxonomic list. The group of vascular plants most significantly correlated with other groups in terms of species richness; furthermore, it displays the highest proportion of between-group co-occurrences. The resulting multi-taxonomic list of potential indicators may serve as an effective means of detecting and monitoring forest ecosystems; however, for this goal, structure-based indicators, such as forest structural attributes and vascular plant species composition, are of primary importance. © 2010 Società Botanica Italiana.

The fundamental ecological significance of deadwood decomposition in forests has been highlighted in several reviews, some conclusions regarding silviculture being drawn. Old-growth forests are natural centres of biodiversity. Saproxylic fungi and beetles, which are vital components of these ecosystems, occupy a variety of spatial and trophic niches. Fungal and beetle diversity on coarse woody debris (CWD) was analysed in 36 forest sites in the Cilento and Vallo di Diano National Park, Italy. The data were analysed by DCA and Spearman's rank correlation. The results provide empirical evidence of the existence of a pattern of joint colonization of the woody substrate by fungi and beetles, which includes an assemblage of reciprocal trophic roles within fungal/beetle communities. These organisms act together to form a dynamic taxonomical and functional ecosystem component within the complex set of processes involved in wood decay. The variables most predictive of correlations between management-related structural attributes and fungal/beetle species richness and their trophic roles for old-growth forest are: number of logs, number of decay classes and CWD total volume. Deadwood spatiotemporal continuity should be the main objective of forest planning to stop the loss of saproxylic fungal and insect biodiversity. © 2010 Società Botanica Italiana.

The maintenance of certain levels of old forest represents a cornerstone of the EU's biodiversity management strategy. A consensus on a single general ecological definition of old-growth is particularly difficult in Mediterranean Europe. The present paper deals with old-growth forests and persistent woodlands in the Cilento and Vallo di Diano National Park (PNCVD) to give an ecological understanding of forest complexity and dynamics under a multiscale and multidisciplinary perspective. The multiscale approach ranged from the identification and mapping of potential old-growth stands at landscape scale to a two-level field review of forest stand features. Field sampling involved a multidisciplinary team of researchers in forest structure, pedologic environment, soil microbial activity, flora and vegetation and deadwood components. The research provided sound knowledge about old-growthness features in the PNCVD that constitutes a unique case study in the whole Mediterranean basin. The integration of results allowed to: identify main ecosystem functions and the related services of the old-growth forests in the study area; distinguish persistent woodlands, multi-aged stands with old trees deriving from nineteenth-century management practices, from old-growth forests sensu strictu; recognize indicators of direct and indirect impacts of human activities; suggest effective practices for sustainable management in the Mediterranean context. © 2010 Società Botanica Italiana.

Stone pine stand of Castel Fusano (Rome) burnt on July the 4th 2000 during a huge wildfire. As a consequence of the fire an intensive natural sexual and asexual regeneration began. In order to monitor such a regeneration field surveys were carried out in 2003 and 2006 in sample plots. Remotely sensed high resolution images from Ikonos and Quick Bird were acquired for the same years. The purpose of this work is to test different methodologies for modeling existing relationships between remotely sensed images and ground collected data in order to estimate and to map both sexual and asexual regeneration. For such a purpose different methodologies were tested: step-wise Muliple Linear Regression, Neural Networks (Relevance-Vector-Machine and the Multi-Layered-Perceptron) and the k-Nearest-Neighbors. These activities were carried out within the framework of the GRINFOMED- MEDIFIRE also developing a specific software named Spatial Forest Modeler (SFM) able to analyze existing relationships between remotely sensed variables and data collected in the field in order to identify the best available models to map and estimate the studied variables acquired on the basis of a field sampling design. The present paper presents data collected in the field, analysis and modeling methods and achieved results. The SFM software is also presented.

Forest ecosystems for their important multifunctional value, need a complex and increasing amount of descriptive information to support their management. Ecological and environmental related attributes have became nowadays important as traditional ones, such as wood growing stock and basal area. The correct application of Sustainable Forest Management criteria is boosted by spatial contiguous knowledge of such attributes. For such a reason in the last years a huge number of scientific experiences in the forest area have been concentrated to study the relationship between data acquired in the field and remotely sensed multispectral images. Models based on such relationships can be used to estimate and map forest attributes acquired in the field on the basis of a statistical sampling design. can be sucould not take in consideration spatially structured data. In last years many researches have focused on possible relationships between field data and remote sensed informations derived from multispectral imagery. Modeling these relationships allows to extend inventory data to not explored surfaces. In this paper were discussed results on spatializing forest biometrical attributes, tree heterogeneity and dimensional heterogeneity assessed during an inventory of Mountain Community "Alto Molise" (IS) throw Spot 5 and Lansat TM 7 imagery. For this purpose a multilinear regression and a k-Nearest Neighbor classifier were used.