PurposeThis article aims to compare the LiDAR handheld mobile laser scanner (HMLS) scans with traditional survey methods, as the tree gauge and the hypsometer, to study the efficiency of the new technology in relation to the accuracy of structural forest attributes estimation useful to support a sustainable forest management.Design/methodology/approachA case study was carried out in a high forest located in Tuscany (Italy), by considering 5 forest types, in 20 different survey plots. A comparative analysis between two survey methods will be shown in order to verify the potential limits and the viability of the LiDAR HMLS in the forest field.FindingsThis research demonstrates that LiDAR HMLS technology allows to obtain a large amount of valuable data on forest structural parameters in a short span of time with a high level of accuracy and with obvious impact in terms of organisational efficiency.Practical implicationsFindings could be useful for forest owners highlighting the importance of investing in science and technology to improve the overall efficiency of forest resources management.Originality/valueThis article adds to the current knowledge on the precision forestry topic by providing insight on the feasibility and effectiveness of using precision technologies for monitoring forest ecosystems and dynamics. In particular, this study fills the gap in the literature linked to the need to have practical examples of the use of innovative technologies in forestry.

Betula aetnensis is an endemic tree of high conservation value, which thrives on the nutrient-poor volcanic soils of Mount Etna. Since plant–microbe interactions could play a crucial role in plant growth, resource uptake, and resistance to abiotic stresses, we aimed to characterize the root and rhizosphere microbial communities. Individuals from natural habitat (NAT) and forest nursery (NURS) were surveyed through microscopy observations and molecular tools: bacterial and fungal automated ribosomal intergenic spacer analysis (ARISA), fungal denaturing gradient gel electrophoresis (DGGE). B. aetnensis was found to be simultaneously colonized by arbuscular (AM), ectomycorrhizal (ECM), ericoid (ERM) fungi, and dark septate endophytes (DSE). A high diversity of the bacterial community was observed whilst the root fungal assemblage of NAT plants was richer than that of NURS. Root and rhizosphere fungal communities from NAT plants were characterized by Illumina MiSeq sequencing. Most of the identified sequences were affiliated to Helotiales, Pezizales, and Malasseziales. Ascomycota and Basidiomycota dominated roots and rhizosphere but differed in community structure and composition. ECM in the roots mainly belonged to Tylospora and Leccinum, while Rhizopogon was abundant in the rhizosphere. The Helotiales, including ERM (mostly Oidiodendron) and DSE (mostly Phialocephala), appeared the dominant component of the fungal community. B. aetnensis harbors an extraordinarily wide array of root-associated soil microorganisms, which are likely to be involved in the adaptation and resistance mechanisms to the extreme environmental conditions in volcano Etna. We argue that nursery-produced seedlings could lack the necessary microbiota for growth and development in natural conditions.

Abstract. Precision forestry is becoming a key sector for forest planning because it allows complex analyses of forest data to be carried out simply and economically. It contributes to the integration between technicians and operators in the sector by guaranteeing the transparency of the forest management operations (Corona et al., 2017). In the context of the progressive development of technology, we investigated the feasibility of using the hand-held mobile laser scanner (HMLS) system in different types of forest sites and comparison of the characteristics of individual trees (tree height, diameters at breast height) with traditional surveys, applied with the aim to validate the performance of the system for a future alternative methodology for forest planning thanks to the collaboration with the forestry company “Dimensione Ricerca Ecologia Ambiente Italia” (D.R.E.Am. Italia). GEOSLAM ZEB HORIZON ™ laser scanner is a hand-held mobile laser scanner containing SLAM technology that can be solved the problem of no GNSS signal or poor signal under the forest canopy making it more practical for forest investigations (Gollob et al., 2020). 15 forest sample plots are selected to reflect different stand conditions in Mediterranean forests taking into count the development stage and density of the sub-canopy vegetation, as well as the species composition in the forest stands. The aim of this study is to show the possible extrinsic circumstances that make the method fail by varying the ecological status of forest plots.

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