In this study, we tested two plotless sampling methods, the ordered distance method and point-centred quarter method, to estimate the tree density and basal area in some managed Alpine forests in northeastern Italy. We selected nine independent forest stands, classified according to the spatial distribution patterns of trees (cluster, random, regular). A plotless sampling survey was simulated within the selected stands and the tree density and basal area were estimated by applying both the ordered distance method and point-centred quarter method. We compared the estimates, in terms of accuracy and preci-sion, between the two methods and against estimates obtained from a simulated survey based on a plot-based sampling method. The point-centred quarter method outperformed the ordered distance method in terms of both accuracy and precision, showing higher robustness towards the bias related to non-random spatial patterns. However, both the plotless methods we tested can provide unbiased accuracy of estimates which, in addition, do not differ from estimates of plot-based sampling. The satisfactory results are encouraging for further tests over other Italian Alpine as well as Apennine forests. If con-firmed, the plotless sampling method, especially the point-centred quarter method, could represent an effective alternative whenever plot-based sampling is deemed redundant, or expensive. © SISEF.

Traditionally, taper equations are developed from measurements collected through a destructive sampling of trees. Terrestrial laser scanning (TLS) enables high levels of accuracy of individual tree parameters measurement avoiding tree felling. With this study, we wanted to assess the performance of two approaches to calibrate a taper function: using stem diameters extracted from TLS point clouds and measured at different tree heights with the traditional and usual forest instruments. We compared the performance of four taper equations built with data collected by TLS and traditional survey in a European beech (Fagus sylvatica L.) forests of mount Amiata (Tuscany Region, Italy). We computed the volume of stem sections 1.00 m long by integrating the most performing TLS-based taper equation and by the Huber, Smalian and cone formulas applied on the diameter and height values measured with the traditional field surveys. We conducted the analysis of error distribution in volume estimates computed integrating the most performing TLS-based taper function along the stem. We tested if the differences in the volume estimate of the two methods were significant. Schumacher and Hall (1933) equation was the most performing taper function both in case of using TLS and traditional surveyed data, being the TLS-based function more performant (rRMSE = 6.90% vs 9.17%). Its performance did not increase when diameter values were extracted from TLS point clouds with a higher frequency (i.e. 25.0 cm vs 1.00 m). By integrating the TLS-based Schumacher and Hall (1933) function, the sections with the highest error resulted from 5.00 to 7.00 m of stem height (i.e. RMSE from 14.72 to 19.14 dm³ and rRMSE from 13.00 to 17.76%). This study case represents the first attempts to develop a taper equation for European beech of mount Amiata using values of stem diameter and height extracted from the TLS point cloud. The results demonstrated that TLS produces the same stem volume estimates as traditional method avoiding falling trees. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.

This article contains tree rings data related to the research article entitled “An intra-stand approach to identify intra-annual growth responses to climate in Pinus nigra subsp. laricio Poiret trees from southern Italy” (Mazza et al., 2018). Most dendroclimatological studies on black pine have been conducted on the P. nigra subsp. nigra, while only few results on climate-growth relationships are available for other taxa such as P. nigra subsp. laricio, which has the narrowest distribution range of the collective species P. nigra. This data article provides tree rings data for the subsp. laricio at an intra-annual growth level, distinguishing early-wood (EW) and late-wood (LW), from an even aged forest stand from the Sila mountain area within the subspecies mesic to xeric distribution range. © 2018

The growth of Pinus nigra tree stands is known to be limited by spring-summer precipitation (P). We explored the intra-annual growth dynamics (early-wood EW and late-wood LW of tree-rings) and their responses to climate (in monthly, seasonal and annual scale) in Pinus nigra subsp. laricio at the intra-stand level in Calabria, at the pines' mesic to xeric distribution range. We used a variety of age detrending methods to assess how the adaptive potential to climate change of each tree varies within the even-aged forest stand. In years of wet climate, when precipitation (P) could infiltrate deeper below ground, higher growth rates occurred in 83% of trees, best explained by P accumulated over several previous years. The variability of EW increment was best explained by 3–5 previous year P (including the growth year) in 61% of trees, while LW increment was best explained by 1–3 year P in 78% of trees. This would suggest that in wet years most trees utilized not only surface but also deeper moisture pools using their taproot to produce both EW and LW. In contrast, during dry years, for 39% of trees the most significant predictor for EW was June rainfall. August P explained LW variability in 35% of the trees, while the influence of 1–3 year P on LW was reduced to 48%. Thus, under a drier climate ca. 1/3 of the trees within the stand significantly reduced their capacity to utilize deeper ground moisture, indicating higher vulnerability to drought stress. Multiple-year P appeared as the main climatic driver for growth in most trees, but only became evident through age detrending methods retaining low frequency growth variability. Our findings are the first to provide such insight into the wide spectrum of climatic factors that may drive P. laricio's inter-stand and inter-annual productivity. They also assist to identify the most vulnerable trees to drought stress within a forest stand. Such information could prove very useful in the application of silvicultural treatments (e.g., selective thinning) aiming to increase the resilience of tree stands to future drought intensification. © 2018 Elsevier B.V.

Urban soundscapes are increasingly recognized as fundamental for both ecological integrity and human well-being, yet the complex interplay between the vegetation structure, seasonal dynamics, and microclimatic factors in shaping these soundscapes remains poorly understood. This study tests the hypothesis that vegetation structure and seasonally driven biological activity mediate the balance and the quality of the urban acoustic environment. We investigated seasonal and spatial variations in five acoustic indices (NDSI, ACI, AEI, ADI, and BI) within a historical urban garden in Castelfranco Veneto, Italy. Using linear mixed-effects models, we analyzed the effects of season, microclimatic variables, and vegetation characteristics on soundscape composition. Non-parametric tests were used to assess spatial differences in vegetation metrics. Results revealed strong seasonal patterns, with spring showing increased NDSI (+0.17), ADI (+0.22), and BI (+1.15) values relative to winter, likely reflecting bird breeding phenology and enhanced biological productivity. Among microclimatic predictors, temperature (p < 0.001), humidity (p = 0.014), and solar radiation (p = 0.002) showed significant relationships with acoustic indices, confirming their influence on both animal behaviour and sound propagation. Spatial analyses showed significant differences in acoustic patterns across points (Kruskal–Wallis p < 0.01), with vegetation metrics such as tree density and evergreen proportion correlating with elevated biophonic activity. Although the canopy height model did not emerge as a significant predictor in the models, the observed spatial heterogeneity supports the role of vegetation in shaping urban sound environments. By integrating ecoacoustic indices, LiDAR-derived vegetation data, and microclimatic parameters, this study offers novel insights into how vegetational components should be considered to manage urban green areas to support biodiversity and foster acoustically restorative environments, advancing the evidence base for sound-informed urban planning. © 2025 by the authors.