Tra le principali innovazioni introdotte dal Testo Unico in materia di Foreste e Filiere forestali (TUFF), oltre alle opportunità di armonizzazione tecnica a livello nazionale degli strumenti di pianificazione forestale, c’è il riconoscimento del livello territoriale come scala di riferimento della pianificazione forestale, attuato attraverso i piani forestali di indirizzo territoriale (PFIT). I PFIT coordinano i piani di gestione forestale aziendali, favoriscono l’integrazione con gli altri strumenti di pianificazione territoriale e ambientale e definiscono, a scala vasta, le priorità d'intervento per la tutela, la gestione e la valorizzazione di boschi e pascoli sotto il profilo ambientale, economico e socio-culturale, promuovendo il coinvolgimento dei portatori di interesse. Il presente contributo propone una discussione critica dello stato di attuazione dei PFIT, evidenziandone criticità e opportunità alla luce delle esperienze dopo l’emanazione dei decreti attuativi del TUFF.

Forests and forestry sector need up-to-date, consistent, robust information for management, monitoring and planning, especially in Mediterranean environment where extreme events driven by climate change are increasing every year. In Italy, several Regions and Autonomous Provinces created local forest maps based on specific needs and regulations; however, a National Forest Map is still missing. The FORMIPAAF project aims, among different objectives, to develop the first Italian Forest Map Prototype (CFI2020), at a national scale of 1:10.000. Main objective of the project is to foster data advancement and updating in the forestry sector, by simplifying access to detailed information and to large-scale forest data, such as CFI2020. In order to realize CFI2020, available local maps, properly analyzed and harmonized, have been merged to achieve a first large-scale information layer that can be easily updated with existing information in the forestry sector. Following a modular and multiscale approach, the project establishes: 1. forest definitions, mapping three different definitions of forested areas: FAO-FRA 2000 (international standard), TUFF 2018 (national standard) and local/administrative definitions; 2. a homogenous and unique nomenclatural system for forest classification integrating local nomenclature with the most widely used systems at national and international scale (e.g.: European Forest Types, INFC category, national forest category sensu Del Favero). CFI2020 will also provide information about canopy cover, silvicultural system and disturbance type, if any. Finally, CFI2020 will be implemented in the upcoming National Forestry Information System, where all the information about forestry sector will be soon available.

Soil pollution is one of the main threats to soil ecosystem health, and the combination of microbial remediation with phytoremediation can promote contaminant degradation and contribute to the revitalization of ecosystem functions. Plant interactions with the surrounding physical and biological environments determine the formation of new ecosystems, which, similarly to natural ones, can provide several ecosystem services. Despite the increasing diffusion of phytoremediation and the large areas potentially suitable for the application of these technologies, the delivery of ecosystem services during phytoremediation interventions has rarely been investigated. In the framework of a bio-phytoremediation project, the present work explored the capacity of a new plant cover created at a site under bio-phytoremediation (area: 0.52 ha) to provide supporting, regulating, and cultural Ecosystem Services. The daily cumulative cooling effect due to plant transpiration during summer was 12.7 °C m−2 day−1, with species characterized by the highest Leaf Area Index and leaf transpiration rates (such as Chrysopogon zizanioides, evergreen shrub species, and Populus nigra) contributing the most to air cooling. Thanks to plant photosynthesis, 177 kg of C was sequestered each year, while the air pollution intercepted by the plant leaves amounted to 1.82 kg per year. After 30 months of phytoremediation, an increase in soil microbial activity indicated a progressive improvement in soil quality. Similarly, the cytometric analysis of hepatopancreatic cells from isopods indicated that the bioindicator organism actively and positively responded to the recovering environment, thus supporting the effectiveness of the ongoing remediation of soil quality. Finally, the implementation of the bio-phytoremediation intervention led to the creation of new habitats, increased ecological connectivity in the surrounding urban area, and generated an aesthetic value comparable to that of urban greenery. These analyses provided evidence that these techniques not only supported soil remediation and site securing but also contributed to improving citizen well-being in the proximity of the site and the environmental quality of the area. These significant positive externalities of phytoremediation should be considered when selecting technologies for environmental clean-up.

The European Natura 2000 network is composed by >50 % of forest, for about 37.5 million of hectares, hosting unvaluable biodiversity. Reporting the conservation status of the Natura 2000 network is mandatory. but the monitoring of sites is based on a variable approach among different countries; accurate spatially explicit data are scarce, and often derived by manual photo interpretation and dated surveys. The increasing climate change impacts on forests and biodiversity, especially in the Mediterranean area, calls for improved monitoring and EU-harmonized procedures. Furthermore, assessing the spatial distribution and extent of natural habitats is another urgent requirement, that can be framed into the wider concept of Essential Biodiversity Variables. Here hyperspectral PRISMA data are used, together with canopy height information from lidar, to map the ecosystem diversity of a Mediterranean Natura 2000 forest site, at very high thematic resolution. The task is not trivial, considering the presence in the study area of different Quercus spp. dominated forest types. The classification tests were conducted with different algorithms and number of classes, to detect optimal solutions. Random Forests was capable to map 14 classes (overall accuracy >80 %) after input features reduction, similarly to Partial Least Squares Discriminant Analysis that instead ingested the full dataset. Even if characterized by higher spatial resolution, models based on Sentinel 2 data provided much lower accuracy than PRISMA. Considerations about the use of this satellite hyperspectral and lidar data, in the framework of improved ecosystem monitoring, were provided. This research illustrates the potential of using hyperspectral and lidar data to assess the forest habitat diversity in the Natura 2000 network, thus supporting the adoption of innovative data and approaches, based on remote sensing, to monitor natural resources and Essential Biodiversity Variables.

The increasing availability of spaceborne hyperspectral satellite imagery opens new opportunities for forest habitat mapping and monitoring, but the limitation of its generally low temporal resolution must be considered. In this study, we compare the ability of single-date PRISMA (PRecursore IperSpettrale della Missione Applicativa), the hyperspectral satellite from the Italian Space Agency, with that of both single-date and multi-date Sentinel-2 (S2) and PlanetScope (PS) to detect and correctly classify various EUNIS habitat types distributed over a relatively small spatial extent (6000 ha) in a natural reserve in Central Italy. The case study deals with multiple levels of spectral similarity, as the dominant canopy species of the target forest habitat classes belong to the same genus (Quercus spp., both deciduous and evergreen species) as well as of different taxa (Pinus and Fraxinus spp.). We performed a pixel-based classification with the Random Forest algorithm using a set of 28 spectral indices computed on PRISMA bands, 22 on S2, and 12 on PS. A Canopy Height Model (CHM) was also used as an input variable for the classification. Our results showed that PRISMA considerably outperforms the two multispectral satellites in single-date classifications, with an overall accuracy of 84 % compared to PlanetScope's 69 % and Sentinel-2's 72 %. Regarding the comparison between multi-date multispectral and singledate hyperspectral, 10-fold cross-validation results revealed that S2 achieves an out-of-bag error rate of approximately 16 %, while PRISMA achieves 17 % and PS 19 %. This demonstrates that a combination of spectral indices calculated during the growing season can capture phenological or physiological differences among the target species, which consequently results in a significant improvement in the classification accuracy of the multispectral sensors. Ultimately, classification results from all three sensors were combined to create probability maps for each forest class, identifying areas classified with a higher degree of certainty by each satellite tested and potentially contributing to forest management by defining areas with varying conservation levels.

Urban green infrastructure, including street trees, plays a key role in providing ecosystem services to urban residents. However, to fully understand the effective role of trees in the urban context, it is also necessary to evaluate the disservices that they can produce in the development of their functions if not managed in an adequate and integrated way. This contribution aims to demonstrate an approach to assess three disservices (pavement damage, aesthetic damage, likelihood of tree failure) of street trees at the municipal level, starting from the existing municipal tree inventory. In this case study, from the street tree population, a sample of approximately 5% of the trees was drawn by stratified random sampling, where the strata were composed of groups of tree species. In particular, a sampling scheme is adapted in which the probability to select a tree in the sample is greater for bigger trees, under the assumption that the bigger the trees the greater are the disservices caused. In this way, a greater precision of the estimates of the considered disservices for the population of urban trees is expected. The results show a high variability of disservices provision among species groups. The results also confirmed a positive correlation between the considered disservices and tree diameter at breast height, while other tree attributes such as total height and crown diameter were found to be positively related only to pavement damages. Finally, severe pruning can lead to a high level of the aesthetic and functional disservices even for shorter and younger street trees.

Urban forests can provide essential environmental and social functions if properly planned and managed. Tree inventory and measurements are a critical part of assessing and monitoring the size, growth, and health condition of urban trees. In this context, the parameters usually collected are DBH and total height, but additional data about crown dimensions (width, length, and crown projection) are required for a comprehensive tree assessment. These data are generally collected by urban foresters through field surveys using tree caliper or diameter tape for DBH, and the electronic ipsometer/clinometer to measure tree height and crown size. Greater detail could be achieved using a digital instrument as Field-Map, a portable computer station to quickly realize dimensional and topographic surveys of trees and forest stands. Finally, the incorporation of the LIDAR scanner into smartphone, as the iPhone 12 Pro, has made this device able to measure tree attributes, as well as additional spatial data in the field. In this study, we tested these three different measurement systems in a field sampling of an urban forest and compared them in terms of measurable parameters, accuracy, cost, and time efficiency. Furthermore, we discussed the pros and cons of each measurement approach and how the resulted data can be used to evaluate ecosystem services of trees and provide guidance on tree management also to reduce potential risks or disservices.

The importance of mixed forests is increasingly recognized on a scientific level, due to their greater productivity and efficiency in resource use, compared to pure stands. However, a reliable quantification of the actual spatial extent of mixed stands on a fine spatial scale is still lacking. Indeed, classification and mapping of mixed populations, especially with semi-automatic procedures, has been a challenging issue up to date. The main objective of this study is to evaluate the potential of Object-Based Image Analysis (OBIA) and Very-High-Resolution imagery (VHR) to detect and map mixed forests of broadleaves and coniferous trees with a Minimum Mapping Unit (MMU) of 500 m2. This study evaluates segmentation-based classification paired with non-parametric method K- nearest-neighbors (K-NN), trained with a dataset independent from the validation one. The forest area mapped as mixed forest canopies in the study area amounts to 11%, with an overall accuracy being equal to 85% and K of 0.78. Better levels of user and producer accuracies (85–93%) are reached in conifer and broadleaved dominated stands. The study findings demonstrate that the very high resolution images (0.20 m of spatial resolutions) can be reliably used to detect the fine-grained pattern of rare mixed forests, thus supporting the monitoring and management of forest resources also on fine spatial scales.

According to the “Habitat” Directive 92/43/EEC, the conservation status of natural habitats depends on the occurrence of populations of their typical species. For some forest habitats, typical species do not occur as canopy dominant trees but are found in the understory. This is the case with the priority habitat ’‘Apennine beech forests with Taxus and Ilex’’ 9210*. Taxus baccata L. and Ilex aquifolium L. are evergreen tree species and occur as isolated trees or groups in the understory of beech dominated forests. Accordingly, the knowledge of the spatial pattern of populations of typical species is fundamental for habitat monitoring goals. In this perspective, this study aims to evaluate the potential of very high-resolution, true color, leaf-off imagery (pixel size = 0.11 m), supplied by Google Earth, for mapping these populations. Understory layer detection has been accomplished through an object-oriented approach, based on multiresolution segmentation. The classification was developed with thresholds based on spectral and geometric properties, as well as on textural and contextual information. The main critical issues are represented by site conditions, where shadowing can prevent crown detection. The thematic accuracy of the target species map resulted in a Producer Accuracy of 0.77 and a User Accuracy of 0.80. The proposed procedure offers a good methodological foundation with which to map the actual spatial extent of forest broadleaved deciduous habitat types, characterized by low abundance and patchily distributed populations of yew and holly.

Forests play a key role in the climate system thanks to their large carbon uptake and storage. On the other hand, forests are vulnerable to climate extremes and pest attacks, causing early tree mortality which in turn could reduce their carbon uptake capacity. Early tree mortality is often associated to a complex interaction of predisposing stress factors (poor site quality, unfavourable stand conditions), inciting factors (frost, drought, mechanical damage) and contributing factors (fungi, insect borers). In this context, the aim of the present work was to investigate the processes underlying the tree mortality observed in an evergreen mixed forest stand dominated by Quercus ilex, located in the Circeo National Park (central Italy). The forest has the typical structure of an old-coppice not more managed (actual rotation time about 2 times that the normal), and was recently (2016) affected by an outbreak of Asian ambrosia beetle (Xylosandrus compactus) and Granulate ambrosia beetle (Xylosandrus crassiusculus) that caused an extensive trees crown browning. In 2019, plots were set in the area to monitor the beetle population dynamic and their impact on tree mortality. In each plot, species, dimension (DBH), stage of dieback, stem origin (resprouts after coppicing or from seed), presence of epicormic shoots and subcortical fungi stroma, were recorded for each woody plant. The plot survey revealed a high frequency of stems classified in a declining stage or dead, on average 42% of the standing stems, with significant differences among the species: 97%, 85%, 74% and 47% for Arbutus unedo, Quercus ilex, Phyllirea latifolia and Fraxinus ornus respectively. The higher stem mortality of Q. ilex was recorded in the smaller diameter classes, suggesting that the self-thinning process played an important role on the observed mortality as typical in the old not more managed coppices. To disentangle the role of the interruption of the management from the climatic and biological drivers, time trends on NDVI index were constrained with the duration of the summer dry seasons and comparing our forest with similar Q. ilex forest coppices in the region and regularly managed. Furthermore, the contribution of recent ambrosia beetles attack was assessed identifying the presence of twigs with signs of previous beetle attack on healthy, declining and dead plants. Our findings point towards complex tree mortality dynamics, in which the competition generated by the stand abandonment predisposed the forest to the insect attack, leading to the general decline of the forest stand.

Forest attributes such as volume or basal area are concentrated at tree locations and are absent elsewhere. It is, therefore, more meaningful to consider the amount of forest attributes at a prefixed spatial grain, within regular plots of prefixed size centered at the points of the study area. In this way, the diversity of attributes within plots also can be considered and quantified by suitable indexes, giving rise to a diversity surface defined on the continuum of points constituting the area. We analyze the estimation of diversity surfaces when a sample of plots is selected by a probabilistic sampling scheme and diversity within nonsampled plots is estimated using an inverse distance weighting interpolator. We discuss the design-based asymptotic properties of the resulting maps when the survey area remains fixed and the number of sampled points increases. Because diversity surfaces share suitable mathematical properties, if the schemes adopted to select sample points ensure an even coverage of the study areas avoiding large portions of non-sampled zones, it can be proven that the estimated maps approach the true maps.

Forest canopy gaps are important to ecosystem dynamics. Depending on tree species, small canopy openings may be associated with intra-crown porosity and with space among crowns. Yet, literature on the relationships between very fine-scaled patterns of canopy openings and biodiversity features is limited. This research explores the possibility of: (1) mapping forest canopy gaps from a very high spatial resolution orthomosaic (10 cm), processed from a versatile unmanned aerial vehicle (UAV) imaging platform, and (2) deriving patch metrics that can be tested as covariates of variables of interest for forest biodiversity monitoring. The orthomosaic was imaged from a test area of 240 ha of temperate deciduous forest types in Central Italy, containing 50 forest inventory plots each of 529 m2 in size. Correlation and linear regression techniques were used to explore relationships between patch metrics and understory (density, development, and species diversity) or forest habitat biodiversity variables (density of micro-habitat bearing trees, vertical species profile, and tree species diversity). The results revealed that small openings in the canopy cover (75% smaller than 7 m2) can be faithfully extracted from UAV red, green, and blue bands (RGB) imagery, using the red band and contrast split segmentation. The strongest correlations were observed in the mixed forests (beech and turkey oak) followed by intermediate correlations in turkey oak forests, followed by the weakest correlations in beech forests. Moderate to strong linear relationships were found between gap metrics and understory variables in mixed forest types, with adjusted R2 from linear regression ranging from 0.52 to 0.87. Equally strong correlations in the same forest types were observed for forest habitat biodiversity variables (with adjusted R2 ranging from 0.52 to 0.79), with highest values found for density of trees with microhabitats and vertical species profile. In conclusion, this research highlights that UAV remote sensing can potentially provide covariate surfaces of variables of interest for forest biodiversity monitoring, conventionally collected in forest inventory plots. By integrating the two sources of data, these variables can be mapped over small forest areas with satisfactory levels of accuracy, at a much higher spatial resolution than would be possible by field-based forest inventory solely.

Since adequate information on the distribution of biodiversity is hardly achievable, biodiversity indicators are necessary to support the management of ecosystems. These surrogates assume that either some habitat features, or the biodiversity patterns observed in a well-known taxon, can be used as a proxy of the diversity of one or more target taxa. Nevertheless, at least for certain taxa, the validity of this assumption has not yet been sufficiently demonstrated.We investigated the effectiveness of both a habitat- and a taxa-based surrogate in six European beech forests in the Apennines. Particularly, we tested: (1) whether the stand structural complexity and the herb-layer species richness were good predictors of the fine-scale patterns of species richness of five groups of forest-dwelling organisms (beetles, saproxylic and epigeous fungi, birds and epiphytic lichens); and (2) the cross-taxon congruence in species complementarity and composition between herb-layer plants and the target taxa.We used Generalized Linear Mixed Models (GLMMs), accumulation curves and Procrustes analysis to evaluate the effectiveness of these surrogates when species richness, complementarity and composition were considered, respectively.Our results provided a limited support to the hypothesis that the herb-layer plants and the stand structural complexity were good surrogates of the target taxa. Although the richness of the herb-layer plants received a stronger support from the data than structural complexity as a predictor for the general patterns of species richness, the overall magnitude of this effect was weak and distinct taxa responded differently. For instance, for increasing levels of herb-layer richness, the richness of lichens showed a marked increase, while the richness of saproxylic fungi decreased. We also found significantly similar complementarity patterns between the herb-layer plants and beetles, as well as a significant congruence in species composition between herb-layer plants and saproxylic fungi. Finally, when different stand structural attributes were considered singularly, only the total amount of deadwood received support from the data as a predictor of the overall species richness.At the fine scale of this study, herb-layer plants and stand structural complexity did not prove to be effective surrogates of multi-taxon biodiversity in well-preserved southern European beech forests. Rather than on weak surrogates, these results suggest that sound conservation decisions should be supported by the information provided by comprehensive multi-taxonomic assessments of forest biodiversity. (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Since adequate information on the distribution of biodiversity is hardly achievable, biodiversity indicators are necessary to support the management of ecosystems. These surrogates assume that either some habitat features, or the biodiversity patterns observed in a well-known taxon, can be used as a proxy of the diversity of one or more target taxa. Nevertheless, at least for certain taxa, the validity of this assumption has not yet been sufficiently demonstrated. We investigated the effectiveness of both a habitatand a taxa-based surrogate in six European beech forests in the Apennines. Particularly, we tested: (1) whether the stand structural complexity and the herb-layer species richness were good predictors of the fine-scale patterns of species richness of five groups of forest-dwelling organisms (beetles, saproxylic and epigeous fungi, birds and epiphytic lichens); and (2) the cross-taxon congruence in species complementarity and composition between herb-layer plants and the target taxa. We used Generalized Linear Mixed Models (GLMMs), accumulation curves and Procrustes analysis to evaluate the effectiveness of these surrogates when species richness, complementarity and composition were considered, respectively. Our results provided a limited support to the hypothesis that the herb-layer plants and the stand structural complexity were good surrogates of the target taxa. Although the richness of the herb-layer plants received a stronger support from the data than structural complexity as a predictor for the general patterns of species richness, the overall magnitude of this effect was weak and distinct taxa responded differently. For instance, for increasing levels of herb-layer richness, the richness of lichens showed a marked increase, while the richness of saproxylic fungi decreased. We also found significantly similar complementarity patterns between the herb-layer plants and beetles, as well as a significant congruence in species composition between herb-layer plants and saproxylic fungi. Finally, when different stand structural attributes were considered singularly, only the total amount of deadwood received support from the data as a predictor of the overall species richness. At the fine scale of this study, herb-layer plants and stand structural complexity did not prove to be effective surrogates of mul Rather than on weak surroga supported by the informatio biodiversity. © 2016 The Authors. Publis ∗ Corresponding author. Current address: Department of Geography, Humboldt-Univer ax: +49 03020936848. E-mail address: francescomaria.sabatini@uniroma1.it (F.M. Sabatini). 1 These authors contributed equally. ttp://dx.doi.org/10.1016/j.ecolind.2016.04.012 470-160X/© 2016 The Authors. Published by Elsevier Ltd. This is an open access y-nc-nd/4.0/). ti-taxon biodiversity in well-preserved southern European beech forests. tes, these results suggest that sound conservation decisions should be n provided by comprehensive multi-taxonomic assessments of forest hed by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). sität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany. Tel.: +49 03020935394; article under the CC BY-NC-ND license (http://creativecommons.org/licenses/

Coppice management in Italy has traditionally focused on a single or few dominating tree species. Tree-oriented silviculture can represent an alternative management system to get high value timber production in mixed coppice forests. This study illustrates an application of the tree-oriented silvicultural approach in Turkey oak (Quercus cerris L.) coppice forests. The rationale behind the proposed silvicultural approach is to combine traditional coppicing and localized, single-tree practices to favor sporadic trees with valuable timber production. At this purpose, a limited number of target trees are selected and favored by localized thinning. In this study, the effectiveness of the proposed tree-oriented approach was compared with the customary coppice management by a financial evaluation. Results showed that the tree-oriented approach is a reliable silvicultural alternative for supporting valuable timber production in mixed oak coppice forests.

Valuable broadleaved tree species can play an important role in mixed-forest management; in these forests, silviculture may play an important role in getting high value timber. This paper illustrates a tree-oriented silviculture approach with an application in a Turkey oak coppice stand in Central Italy. This silvicultural approach has been developed in the last decades in France, Germany, Switzerland. The rationale behind the tree-oriented approach is to select a number of target sporadic tree species with valuable timber and to support their growth through repeated thinning from above. We tested the effectiveness of this silviculture approach as an alternative to customary coppice management in Italy, which is traditionally focused on the dominant tree species and does not consider valuable broadleaved tree species. The two silviculture approaches (tree-oriented and customary coppicing) were compared through a financial evaluation of the economic convenience of the two alternatives in a Turkey oak coppice stand in Central Italy

Land take due to the rapid growth of urban areas is an issue of global concern. It calls for sound monitoring methodologies to quantify the phenomenon, with a view to verify the effectiveness of urban growth management strategies. To this end, we propose an integrated statistical approach, coupling point sampling and mapping techniques, to estimate the number and size of urban areas, in a given territory, on successive occasions. Urban areas classification is based on all land cover classes contributing to urban structure, and is more comprehensive than assessments based on sealed surfaces only. The devised approach is here tested to quantify land take by urban expansion during 1990-2008 in the Metropolitan City of Rome (Central Italy). Urban areas coverage increased from 15.4% in 1990 to approximately 20.4% in 2008. During this period, 11,000 ha, mainly agricultural land, were taken by urban sprawl in Rome's municipality. This occurred despite the fact that population had remained stable. Our findings also indicate that the average land take per-capita in Rome municipality is about four times higher than the average value of urban residential area per capita of mid-to-large European cities. We therefore discuss the potential of the proposed method for a reliable monitoring of urban expansion, in order to support sustainable urban management and to highlight factors underpinning unregulated urban development. (C) 2015 Elsevier B.V. All rights reserved.

Urban trees are a source of ecosystem services and contribute to increase quality of life for many communities and their residents. At the same time they could also determine disservices, such as damages to structures and risk to human safety due to critical combination of tree defects and environmental factors. Although knowledge about tree structure and host-pathogen interactions has grown, the assessment of risk has not been fully explored yet. In particular, the multidimensionality of tree risk assessment as well as the concern about weighting techniques in the construction of indices to measure it need to be addressed.The aim of this paper is to develop a composite tree risk index (R) useful for the management of amenity trees, with a two-fold perspective. First, the multidimensionality issue is explored by considering three dimensions of the tree risk: the Hazard, that represents the likelihood of failure of the tree, the Contact factor, i.e. the nature and the value of the target, and the Damage factor, i.e. the potential for injury or damage. Each dimension is assessed as a function of a set of observed variables related to dendrometric attributes, health status, proximity to buildings and artifacts, tree esthetic value, derived both from field data and spatial analysis performed under GIS environment. Second, in the aggregation of variables into specific-dimension indicators we verify if and to what extent various positive and normative weighting techniques influence the construction of composite index. The R index, obtained as the product of the specific-dimension indicators, was computed for 130 trees located within the formal garden and the park of Villa Lante in Bagnaia, Viterbo (Central Italy), a well-known Renaissance monumental complex, where the needs of cultural heritage conservation and human safety have to be balanced with recreational uses. Sensitivity analyses were carried out in order to test the robustness of R with respect to the considered techniques. (C) 2015 Elsevier GmbH. All rights reserved.