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Forest structure and understory functional diversity at multiple scales: The importance of median tree height
de Benedictis , Luciano Ludovico Maria , Chelli , Stefano , Zhu , Zhengxue , Cervellini , Marco , Canullo , R. , Chianucci , Francesco , Puletti , Nicola , Tsakalos , James L. , Bartha , Sándor , Campetella , Giandiego
beech forest forest structural traits forest understorey functional diversity functional redundancy scale-dependent diversity terrestrial laser scanning
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2026
Rivista
Ecological Indicators
Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR-species20K dataset
Puliti , Stefano , Lines , Emily R. , Müllerová , Jana , Frey , Julian , Schindler , Zoe , Straker , Adrian , Allen , Matthew J. , Winiwarter , Lukas , Rehush , Nataliia , Hristova , Hristina S. , Murray , Brent A. , Calders , Kim , Coops , Nicholas C. , Höfle , Bernhard , Irwin , Liam A.K. , Junttila , Samuli , Kruček , Martin , Krok , G. , Král , Kamil , Levick , Shaun R. , Lück , Linda , Missarov , Azim , Mokroš , M. , Owen , Harry Jon Foord , Stereńczak , Krzysztof Jan , Pitkänen , Timo P. , Puletti , Nicola , Saarinen , Ninni , Hopkinson , Chris Dennis , Terryn , Louise , Torresan , C. , Tomelleri , Enrico , Weiser , Hannah , Astrup , Rasmus
lidar remote sensing biodiversity deep learning point cloud classification single-tree inventory
Mostra abstract
Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5). 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods. © 2025 The Author(s). Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
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2025
Rivista
Methods in Ecology and Evolution
Dettagli
Vol. 16 (4) pp. 801 - 818
DOI
Multiple drivers of functional diversity in temperate forest understories: Climate, soil, and forest structure effects
Chelli , Stefano , Bricca , Alessandro , Tsakalos , James L. , Andreetta , Anna , Bonari , Gianmaria , Campetella , Giandiego , Carnicelli , Stefano , Cervellini , Marco , Puletti , Nicola , Wellstein , Camilla , Canullo , R.
climate change functional diversity bud bank forest management plant height seed mass specific leaf area
Mostra abstract
In macroecology, shifting from coarse- to local-scale explanatory factors is crucial for understanding how global change impacts functional diversity (FD). Plants possess diverse traits allowing them to differentially respond across a spectrum of environmental conditions. We aim to assess how macro- to microclimate, stand-scale measured soil properties, forest structure, and management type, influence forest understorey FD at the macroecological scale. Our study covers Italian forests, using thirteen predictors categorized into climate, soil, forest structure, and management. We analyzed five traits (i.e., specific leaf area, plant size, seed mass, belowground bud bank size, and clonal lateral spread) capturing independent functional dimensions to calculate the standardized effect size of functional diversity (SES-FD) for all traits (multi-trait) and for single traits. Multiple regression models were applied to assess the effect of predictors on SES-FD. We revealed that climate, soil, and forest structure significantly drive SES-FD of specific leaf area, plant size, seed mass, and bud bank. Forest management had a limited effect. However, differences emerged between herbaceous and woody growth forms of the understorey layer, with herbaceous species mainly responding to climate and soil features, while woody species were mainly affected by forest structure. Future warmer and more seasonal climate could reduce the diversity of resource economics, plant size, and persistence strategies of the forest understorey. Soil eutrophication and acidification may impact the diversity of regeneration strategies; canopy closure affects the diversity of above- and belowground traits, with a larger effect on woody species. Multifunctional approaches are vital to disentangle the effect of global changes on functional diversity since independent functional specialization axes are modulated by different drivers. © 2024 The Authors
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2024
Rivista
Science of the Total Environment
Dettagli
Vol. 916
DOI
Plant functional traits are correlated with species persistence in the herb layer of old-growth beech forests
Campetella , Giandiego , Chelli , Stefano , Simonetti , Enrico , Damiani , Claudia , Bartha , Sándor , Wellstein , Camilla , Giorgini , Daniele , Puletti , Nicola , Mucina , Ladislav , Cervellini , Marco , Canullo , R.
beech forest genetics plant leaf plant seed quantitative trait fagus forests plant leaves heritable seeds
Mostra abstract
This paper explores which traits are correlated with fine-scale (0.25 m<sup>2</sup>) species persistence patterns in the herb layer of old-growth forests. Four old-growth beech forests representing different climatic contexts (presence or absence of summer drought period) were selected along a north–south gradient in Italy. Eight surveys were conducted in each of the sites during the period spanning 1999–2011. We found that fine-scale species persistence was correlated with different sets of plant functional traits, depending on local ecological context. Seed mass was found to be as important for the fine-scale species persistence in the northern sites, while clonal and bud-bank traits were markedly correlated with the southern sites characterised by summer drought. Leaf traits appeared to correlate with species persistence in the drier and wetter sites. However, we found that different attributes, i.e. helomorphic vs scleromorphic leaves, were correlated to species persistence in the northernmost and southernmost sites, respectively. These differences appear to be dependent on local trait adaptation rather than plant phylogenetic history. Our findings suggest that the persistent species in the old-growth forests might adopt an acquisitive resource-use strategy (i.e. helomorphic leaves with high SLA) with higher seed mass in sites without summer drought, while under water-stressed conditions persistent species have a conservative resource-use strategy (i.e. scleromorphic leaves with low SLA) with an increased importance of clonal and resprouting ability. © 2020, The Author(s).
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2020
Rivista
Scientific Reports
Dettagli
Vol. 10 (1)
DOI
Assessment of UAV photogrammetric DTM-independent variables for modelling and mapping forest structural indices in mixed temperate forests
Giannetti , Francesca , Puletti , Nicola , Puliti , Stefano , Travaglini , Davide , Chirici , Gherardo
biodiversity precision forestry forest structure forest inventory airborne laser scanning drone dtm-independent structure from motion
Mostra abstract
In the EU 2020 biodiversity strategy, maintaining and enhancing forest biodiversity is essential. Forest managers and technicians should include biodiversity monitoring as support for sustainible forest management and conservation issues, through the adoption of forest biodiversity indices. The present study investigates the potential of a new type of Structure from Motion (SfM) photogrammetry derived variables for modelling forest structure indicies, which do not require the availability of a digital terrain model (DTM) such as those obtainable from Airborne Laser Scanning (ALS) surveys. The DTM-independent variables were calculated using raw 3D UAV photogrammetric data for modeling eight forest structure indices which are commonly used for forest biodiversity monitoring, namely: basal area (G); quadratic mean diameter (DBH<inf>mean</inf>); the standard deviation of Diameter at Breast Height (DBH<inf>σ</inf>); DBH Gini coefficient (Gini); the standard deviation of tree heights (H<inf>σ</inf>); dominant tree height (H<inf>dom</inf>); Lorey's height (H<inf>l</inf>); and growing stock volume (V). The study included two mixed temperate forests areas with a different type of management, with one area, left unmanaged for the past 50 years while the other being actively managed. A total of 30 field sample plots were measured in the unmanaged forest, and 50 field plots were measured in the actively managed forest. The accuracy of UAV DTM-independent predictions was compared with a benchmark approach based on traditional explanatory variables calculated from ALS data. Finally, DTM-independent variables were used to produce wall-to-wall maps of the forest structure indices in the two test areas and to estimate the mean value and its uncertainty according to a model-assisted regression estimators. DTM-independent variables led to similar predictive accuracy in terms of root mean square error compared to ALS in both study areas for the eight structure indices (DTM-independent average RMSE<inf>%</inf> = 20.5 and ALS average RMSE<inf>%</inf> = 19.8). Moreover, we found that the model-assisted estimation, with both DTM-independet and ALS, obtained lower standar errors (SE) compared to the one obtained by model-based estimation using only field plots. Relative efficiency coefficient (RE) revealed that ALS-based estimates were, on average, more efficient (average RE ALS = 3.7) than DTM-independent, (average RE DTM-independent = 3.3). However, the RE for the DTM-independent models was consistently larger than the one from the ALS models for the DBH-related variables (i.e. G, DBH<inf>mean</inf>, and DBH<inf>σ</inf>) and for V. This highlights the potential of DTM-independent variables, which not only can be used virtually on any forests (i.e., no need of a DTM), but also can produce as precise estimates as those from ALS data for key forest structural variables and substantially improve the efficiency of forest inventories. © 2020 Elsevier Ltd
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2020
Rivista
Ecological Indicators
Dettagli
Vol. 117
DOI
Effects of climate, soil, forest structure and land use on the functional composition of the understorey in Italian forests
Chelli , Stefano , Simonetti , Enrico , Wellstein , Camilla , Campetella , Giandiego , Carnicelli , Stefano , Andreetta , Anna , Giorgini , Daniele , Puletti , Nicola , Bartha , Sándor , Canullo , R.
plant height seed mass specific leaf area climate–soil interactions community-weighted mean functional biogeography temperature seasonality trait–environment relationship
Mostra abstract
Question: In functional biogeography studies, generalizable patterns in the relationship between plant traits and the environment have yet to emerge. Local drivers (i.e., soil, land use, vegetation structure) can increase our understanding of the trait–environment relationship. What is the role of climate and local drivers in shaping abundance-weighted trait patterns of forest understories at biogeographic scales?. Location: Italian forests. Methods: We selected 201 sites that are statistically representative for the heterogeneity of Italian forests across three biogeographic regions (alpine, continental, and mediterranean). Understorey vegetation was recorded for each site on an area of 400 m<sup>2</sup>, together with 25 environmental variables related to climate, soil, land use and forest structure. Specific leaf area (SLA), plant height (H) and seed mass (SM) were obtained from databases. Community-weighted mean (CWM) values were calculated. Variance partitioning was used to identify the relative role of groups of environmental variables on the CWM of traits. Generalized Additive Models were used to assess the relationship between traits and single variables. Results: Climate alone and climate–soil interactions explained the largest proportion of the variation of all the traits (13.7% to 22.8%). Temperature-related factors as well as soil N and P availability were the climatic and edaphic explanatory variables most correlated to trait variation. Forest structure and land use accounted for a smaller percentage of the variation in traits. Land-use factors alone were important in explaining only SLA variation. Conclusions: While climate plays a major role in trait–environment relationships in forest understories, our results highlighted the need to integrate at least soil properties as local drivers of trait variation in broad scale functional biogeography studies of these systems. © 2019 International Association for Vegetation Science
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2019
Rivista
Journal of Vegetation Science
Dettagli
Vol. 30 (6) pp. 1110 - 1121
DOI
Climate is the main driver of clonal and bud bank traits in Italian forest understories
Chelli , Stefano , Ottaviani , Gianluigi , Simonetti , Enrico , Wellstein , Camilla , Canullo , R. , Carnicelli , Stefano , Andreetta , Anna , Puletti , Nicola , Bartha , Sándor , Cervellini , Marco , Campetella , Giandiego
clonality community weighted mean (cwm) plant-environment linkages resprouting soil properties trait-based ecology
Mostra abstract
The study of plant trait-environment links is rarely focused on traits that inform on space occupancy and resprouting (both affecting plant persistence), especially in forest understories. Traits that can effectively capture such key functions are associated with clonality and bud banks. We hypothesized that: 1) climate is the main driver of clonal and bud bank traits, 2) traits related to space occupancy (e.g., greater lateral spread) are more important in more mesic, richer soils forests, and 3) traits related to resprouting ability (e.g., larger bud bank) are more important in more intensively and recently managed forests. We addressed these hypotheses by analysing a unique dataset that is statistically representative of Italian forests heterogeneity and includes three biogeographic regions (Alpine, Continental, Mediterranean). We recorded data for sixteen climatic, soil and management variables. We calculated community weighted mean (CWM) values of seven clonal and bud bank traits for the forest understory vegetation. We used i) redundancy analysis to assess trait-environment relations, and ii) variance partitioning analyses to identifying the relative role of different groups of abiotic variables on CWM variation of all traits combined together, as well as clonal and bud bank traits taken separately. Climate alone had a pervasive effect in determining patterns of clonal and bud bank traits in Italian forest understories, mainly related to the effects of temperature extremes and seasonality. Unexpectedly, soil and management factors alone showed marginal effects on clonal and bud bank traits. However, soil features influenced trait patterns when joined with climate. Our results confirmed that, at the biogeographic scale, climate played a lion-share role in determining persistence-related traits of forest-floor plants. At the local-scale, other interplaying factors (e.g., management, soil variables) may come into play in shaping patterns of the studied plant traits. This study stressed the importance of examining functional trait patterns along complex environmental gradients. © 2019 Elsevier GmbH
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2019
Rivista
Perspectives in Plant Ecology, Evolution and Systematics
Dettagli
Vol. 40
DOI
Testing an expanded set of sustainable forest management indicators in Mediterranean coppice area
Cutini , Andrea , Ferretti , Marco , Bertini , Giada , Brunialti , Giorgio , Bagella , Simonetta , Chianucci , Francesco , Fabbio , Gianfranco , Fratini , Roberto , Riccioli , Francesco , Caddeo , C. , Calderisi , Marco , Ciucchi , B. , Corradini , Stefano , Cristofolini , Fabiana , Cristofori , Antonella , Di Salvatore , Umberto , Ferrara , Carlotta , Frati , Luisa , Landi , Sara , Marchino , Luca , Patteri , Giacomo , Piovosi , Maurizio , Roggero , Pier Paolo , Seddaiu , Giovanna , Gottardini , Elena
silviculture coppice conversion coppice natural evolution coppice system environmental monitoring sfm criteria
Mostra abstract
Although coppice forests represent a significant part of the European forest area, especially across southern Countries, they received little attention within the Sustainable Forest Management (SFM) processes and scenarios, whose guidelines have been mainly designed to high forests and national scale. In order to obtain “tailored” information on the degree of sustainability of coppices on the scale of the stand, we evaluated (i) whether the main coppice management options result in different responses of the SFM indicators, and (ii) the degree to which the considered SFM indicators were appropriate in their application at stand level. The study considered three different management options (Traditional Coppice TC, coppice under Natural Evolution NE, and coppice under Conversion to high forest by means of periodical thinning CO). In each of the 43 plots considered in the study, which covered three different European Forest Types, we applied a set of eighteen “consolidated” SFM indicators, covering all the six SFM Criteria (FOREST EUROPE, 2020) and, additionally, tested other sixteen novel indicators shaped for agamic forests and/or applicable at stand level. Results confirmed that several consolidated indicators related to resources status (Growing stock and Carbon stock), health (Defoliation and Forest damage), and socio-economic functions (Net revenue, Energy and Accessibility) were highly appropriate for evaluating the sustainability of coppice at stand level. In addition, some novel indicators related to resources status (Total above ground tree biomass), health (Stand growth) and protective functions (Overstorey cover and Understorey cover) proved to be highly appropriate and able to support the information obtained by the consolidated ones. As a consequence, a subset of consolidated SFM indicators, complemented with the most appropriate novel ones, may represent a valid option to support the evaluation of coppice sustainability at stand level. An integrated analysis of the SFM indicators showed that NE and CO display significant higher environmental performances as compared with TC. In addition, CO has positive effects also on socio-economic issues, while TC -which is an important cultural heritage and a silvicultural option that may help to keep local communities engaged in forestry – combines high wood harvesting rates with dense understory cover. Overall, each of the three management options showed specific sustainability values; as a consequence, their coexistence at a local scale and in accordance with the specific environmental conditions and the social-economic context, is greatly recommended since it may fulfill a wider array of sustainability issues. © 2021
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2021
Rivista
Ecological Indicators
Dettagli
Vol. 130
DOI
Roe deer (Capreolus capreolus L.) browsing effects and use of chestnut and Turkey oak coppiced areas
Cutini , Andrea , Bongi , Paolo , Chianucci , Francesco , Pagon , Nives , Grignolio , Stefano , Amorini , Emilio , Apollonio , Marco
castanea sativa coppice deer forest damages quercus cerris
Mostra abstract
Introduction: Roe deer (Capreolus capreolus) browsing pressure on vegetative regeneration of Turkey oak (Quercus cerris) and chestnut (Castanea sativa) and roe deer use of coppiced areas were investigated. Methods: In the Apennines, Central Italy, six experimental areas were chosen, where fenced (ungulate access excluded, protected P) and non-fenced (ungulate influence present, non-protected NP) plots were established after coppicing. From 2002 to 2005, each plot was surveyed twice a year, and number, biomass, collar diameter, and total height of the sprouts were measured. Results:Roe deer had a different effect on the re-growth of Turkey oak and chestnut sprouts. After 4 years, chestnut did not show any browsing-related damage, while in Turkey oak, biomass and height of the sprouts in fenced plots significantly differed from those in non-fenced plots. The results agreed with an experimental browsing index. The outcome is relevant because it represents a quick and reliable field tool to assess the impact on a larger scale, where analytic and quantitative approaches cannot be applied. The locations of 62 adult radiocollared roe deer confirmed an increase in the use of coppiced areas. A utilisation index showed more frequent use of these areas during and after forest work. Contrary to common opinion, logging seemed to attract roe deer in coppiced areas as the vegetation biomass at their disposal increased. © INRA and Springer Science+Business Media B.V. 2011.
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2011
Rivista
Annals of Forest Science
Dettagli
Vol. 68 (4) pp. 667 - 674
DOI