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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
Wall-to-Wall Mapping of Forest Biomass and Wood Volume Increment in Italy
Giannetti , Francesca , Chirici , Gherardo , Vangi , Elia , Corona , P. , Maselli , Fabio , Chiesi , Marta , D'Amico , Giovanni , Puletti , Nicola
remote sensing forest biomass forest increment mediterranean forest national forest inventories
Mostra abstract
Several political initiatives aim to achieve net-zero emissions by the middle of the twenty-first century. In this context, forests are crucial as a carbon sink to store unavoidable emissions. Assessing the carbon sequestration potential of forest ecosystems is pivotal to the availability of accurate forest variable estimates for supporting international reporting and appropriate forest management strategies. Spatially explicit estimates are even more important for Mediterranean countries such as Italy, where the capacity of forests to act as sinks is decreasing due to climate change. This study aimed to develop a spatial approach to obtain high-resolution maps of Italian forest above-ground biomass (ITA-BIO) and current annual volume increment (ITA-CAI), based on remotely sensed and meteorological data. The ITA-BIO estimates were compared with those obtained with two available biomass maps developed in the framework of two international projects (i.e., the Joint Research Center and the European Space Agency biomass maps, namely, JRC-BIO and ESA-BIO). The estimates from ITA-BIO, JRC-BIO, ESA-BIO, and ITA-CAI were compared with the 2nd Italian NFI (INFC) official estimates at regional level (NUT2). The estimates from ITA-BIO are in good agreement with the INFC estimates (R<sup>2</sup> = 0.95, mean difference = 3.8 t ha<sup>−1</sup>), while for JRC-BIO and ESA-BIO, the estimates show R<sup>2</sup> of 0.90 and 0.70, respectively, and mean differences of 13.5 and of 21.8 t ha<sup>−1</sup> with respect to the INFC estimates. ITA-CAI estimates are also in good agreement with the INFC estimates (R<sup>2</sup> = 0.93), even if they tend to be slightly biased. The produced maps are hosted on a web-based forest resources management Decision Support System developed under the project AGRIDIGIT (ForestView) and represent a key element in supporting the new Green Deal in Italy, the European Forest Strategy 2030 and the Italian Forest Strategy. © 2022 by the authors.
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2022
Rivista
Forests
Dettagli
Vol. 13 (12)
DOI
From model selection to maps: A completely design-based data-driven inference for mapping forest resources
Di Biase , Rosa Maria , Fattorini , Lorenzo , Franceschi , Sara , Grotti , Mirko , Puletti , Nicola , Corona , P.
density estimation harmonization model selection predictions pseudopopulation bootstrap regression estimator residuals smoothing parameter spatial interpolation
Mostra abstract
A completely data-driven, design-based sampling strategy is proposed for mapping a forest attribute within the spatial units tessellating a survey region. Based on sample data, a model is selected, and model parameters are estimated using least-squares criteria for predicting the attribute of interest within units as a linear function of a set of auxiliary variables. The spatial interpolation of residuals arising from model predictions is performed by inverse distance weighting. The leave-one-out cross validation procedure is adopted for selecting the smoothing parameter used for interpolation. The densities of the attributes of interest within units are estimated by summing predictions and interpolated residuals. Finally, density estimates are rescaled to match the total estimate over the survey region obtained by the traditional regression estimator with the total estimate obtained from the map as the sum of the density estimates within units. A bootstrap procedure accounts for the uncertainty. The consistency of the strategy is proven by incorporating previous results. A simulation study is performed and an application for mapping wood volume densities in the forest estate of Rincine (Central Italy) is described. © 2022 John Wiley & Sons Ltd.
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2022
Rivista
Environmetrics
Dettagli
Vol. 33 (7)
DOI
A deep learning approach for automatic mapping of poplar plantations using Sentinel-2 imagery
D'Amico , Giovanni , Francini , Saverio , Giannetti , Francesca , Vangi , Elia , Travaglini , Davide , Chianucci , Francesco , Mattioli , Walter , Grotti , Mirko , Puletti , Nicola , Corona , P. , Chirici , Gherardo
deep learning big data forest tree crops fully connected neural networks multitemporal classification tree species mapping
Mostra abstract
Poplars are one of the most widespread fast-growing tree species used for forest plantations. Owing to their distinct features (fast growth and short rotation) and the dependency on the timber price market, poplar plantations are characterized by large inter-annual fluctuations in their extent and distribution. Therefore, monitoring poplar plantations requires a frequent update of information–not feasible by National Forest Inventories due to their periodicity–achievable by remote sensing systems applications. In particular, the new Sentinel-2 mission, with a revisiting period of 5 days, represents a potentially efficient tool for meeting this need. In this paper, we present a deep learning approach for mapping poplar plantations using Sentinel-2 time series. A reference dataset of poplar plantations was available for a large study area of more than 46,000 km<sup>2</sup> in Northern Italy and served as training and testing data. Two classification methods were compared: (1) a fully connected neural network (also called multilayer perceptron), and (2) a traditional logistic regression. The performance of the two approaches was estimated through bootstrapping procedure with a confidence interval of 99%. Results indicated for deep learning an omission error rate of 2.77%±2.76%, showing improvements compared to logistic regression, omission error rate = 8.91%±4.79%. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
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2021
Rivista
GIScience and Remote Sensing
Dettagli
Vol. 58 (8) pp. 1352 - 1368
DOI
Influence of image pixel resolution on canopy cover estimation in poplar plantations from field, aerial and satellite optical imagery
Chianucci , Francesco , Puletti , Nicola , Grotti , Mirko , Bisaglia , Carlo , Giannetti , Francesca , Romano , Elio , Brambilla , Massimo , Mattioli , Walter , Cabassi , Giovanni , Bajocco , Sofia , Li , Linyuan , Chirici , Gherardo , Corona , P. , Tattoni , Clara
canopy photography crown cover foliage cover sentinel-2 unmanned aerial vehicles
Mostra abstract
Accurate estimates of canopy cover (CC) are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used to estimate CC from the complement of gap fraction measurements obtained with restricted-view sensors. In this short note we evaluated the influence of the image pixel resolution (ground sampling distance; GSD) on CC estimation in poplar plantations obtained from field (cover photography; GSD < 1 cm), unmanned aerial (UAV; GSD <10 cm) and satellite (Sentinel-2; GSD = 10 m) imagery. The trial was conducted in poplar tree plantations in Northern Italy, with varying age and canopy cover. Results indicated that the coarser resolution available from satellite data is suitable to obtain estimates of canopy cover, as compared with field measurements obtained from cover photography; therefore, S2 is recommended for larger scale monitoring and routine assessment of canopy cover in poplar plantations. The higher resolution of UAV compared with Sentinel-2 allows finer assessment of canopy structure, which could also be used for calibrating metrics obtained from coarser-scale remote sensing products, avoiding the need of ground measurements. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.
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2021
Rivista
Annals of Silvicultural Research
Dettagli
Vol. 46 (1) pp. 8 - 13
DOI
Probabilistic sampling and estimation for large-scale assessment of poplar plantations in Northern Italy
Corona , P. , Chianucci , Francesco , Marcelli , Agnese , Gianelle , Damiano , Fattorini , Lorenzo , Grotti , Mirko , Puletti , Nicola , Mattioli , Walter
forest inventory hybrid poplar populus spp tessellation stratified sampling two-phase sampling
Mostra abstract
In the recent decades, growing demand for wood products, combined with efforts to conserve natural forests, has supported a steady increase in the global extent of planted forests. In this paper, a two-phase sampling strategy for large-scale assessment of hybrid poplar plantations in Northern Italy was implemented. The first phase was performed by means of tessellation stratified sampling on high-resolution remotely sensed imagery, covering the survey area by a grid of regular polygons of equal size and randomly and independently selecting one point per quadrat. All the plantations spotted by at least one sample point were selected. In the second phase, we randomly chosen a subset of plantations by stratified sampling that were visited on the ground to collect qualitative and quantitative attributes. The resulting estimates were reliable, and the survey demonstrated relatively easy to be implemented and replicated. These considerations support the use of the proposed sampling strategy to frequently update information on fast-growing forest plantations within agricultural farms, like hybrid poplar crops. Moreover, the results of the case study here presented highlight the relevance of hybrid poplar plantations in Italy, in the context of sustainable development strategies under a green economy perspective. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
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2020
Rivista
European Journal of Forest Research
Dettagli
Vol. 139 (6) pp. 981 - 988
DOI
Large-scale two-phase estimation of wood production by poplar plantations exploiting sentinel-2 data as auxiliary information
Marcelli , Agnese , Mattioli , Walter , Puletti , Nicola , Chianucci , Francesco , Gianelle , Damiano , Grotti , Mirko , Chirici , Gherardo , D'Amico , Giovanni , Francini , Saverio , Travaglini , Davide , Fattorini , Lorenzo , Corona , P.
national forest inventories regression estimator sentinel-2 design-based inference first-phase tessellation stratified sampling second-phase stratified sampling simulation study
Mostra abstract
Growing demand for wood products, combined with efforts to conserve natural forests, have supported a steady increase in the global extent of planted forests. Here, a two-phase sampling strategy for large-scale assessment of the total area and the total wood volume of fast-growing forest tree crops within agricultural land is presented. The first phase is performed using tessellation stratified sampling on high-resolution remotely sensed imagery and is sufficient for estimating the total area of plantations by means of a Monte Carlo integration estimator. The second phase is performed using stratified sampling of the plantations selected in the first phase and is aimed at estimating total wood volume by means of an approximation of the first-phase Horvitz-Thompson estimator. Vegetation indices from Sentinel-2 are exploited as freely available auxiliary information in a linear regression estimator to improve the design-based precision of the estimator based on the sole sample data. Estimators of the totals and of the design-based variances of total estimators are presented. A simulation study is developed in order to check the design-based performance of the two alternative estimators under several artificial distributions supposed for poplar plantations (random, clustered, spatially trended). An application in Northern Italy is also reported. The regression estimator turns out to be invariably better than that based on the sole sample information. Possible integrations of the proposed sampling scheme with conventional national forest inventories adopting tessellation stratified sampling in the first phase are discussed. © 2020, Finnish Society of Forest Science. All rights reserved.
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2020
Rivista
Silva Fennica
Dettagli
Vol. 54 (2)
DOI
A dataset of forest volume deadwood estimates for Europe
Puletti , Nicola , Canullo , R. , Mattioli , Walter , Gawryś , Radosław , Corona , P. , Czerepko , Janusz
deadwood decay classes european forest types icp forests monitoring programme stand age stand management
Mostra abstract
Key message: ICP Forests relies on a representative pan-European network based on a 16 × 16 km grid-net covering around 6000 plots. Dead wood volumes for 3243 plots, related to 19 European Countries, are presented in this data paper as a result of harmonised sampling procedure, and under compliance with FAIR Data Principles. Dataset access is at https://zenodo.org/record/1467784. Associated metadata are available athttps://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/a27d2a8f-1a2d-4a1c-b932-86ec5f4bd8a6(link to geo-network provided after acceptance). Context: ICP-Forests dataset represents unique opportunity for the assessment of forest resources sustainability and biodiversity in Europe because it monitors the status of forests under a coordinated Pan-European umbrella by standardised methods. Aims: The main goal of this paper is to provide standardized estimates of deadwood volume at European scale for a broader use among forest scientists. Methods: After quality checks, calculations of deadwood volumes distinguished by deadwood types (standing and lying dead trees, snags, coarse woody debris, stumps) have been performed. The obtained plot level data have been joined to available forest stand information (namely: forest type, forest management, and stand age) over 3,243 plots among Europe. Results: The database provides a basis for the evaluation of combined relationships between deadwood volume and forest type, deadwood type, decay status, forest management, and stand age classes at European level. Conclusion: Deadwood volume and quality is recognized as one of the most important source of information for forest biodiversity. Here, first results of a systematic and standardized European survey scheme for assessing deadwood volume are presented. This ICP Forests datasets analysis represents the base for further analysis and relationships. © 2019, INRA and Springer-Verlag France SAS, part of Springer Nature.
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2019
Rivista
Annals of Forest Science
Dettagli
Vol. 76 (3)
DOI
Spatio-temporal variability in structure and diversity in a semi-natural mixed oak-hornbeam floodplain forest
Grotti , Mirko , Chianucci , Francesco , Puletti , Nicola , Fardusi , Most Jannatul , Castaldi , Cristiano , Corona , P.
functional diversity mixed-forests non-spatial diversity spatial diversity temporal forest analysis
Mostra abstract
Mixed forests are particularly interesting for forest structure and diversity analyses, as higher complexity and diversity can be expected in these forests compared to pure ones. Integrating different approaches in the analyses of structure and diversity in these forests can provide complementary information on non-spatial, spatial and functional diversity patterns. The study aimed at evaluating the spatio-temporal dynamics in forest structure and diversity in a semi-natural mixed oak-hornbeam floodplain forest. All standing trees were mapped and inventoried in 1995, 2005 and 2016 in three 1-ha mixed forest stands, with different soil moisture regime (xeric, mesic, moist conditions). Traditional, non-spatial structure and diversity measures were coupled with spatially-explicit and functional diversity measures. Results indicated that the three stands showed limited variation in stand structure and similar non-spatial diversity attributes, despite the different species composition. Only the extension to spatial and functional analyses was able to reveal more pronounced differences of diversity patterns, as higher complexity, species mingling, and functional tree complementarity was observed in the moister stand. These findings support use of spatially-explicit measurements in traditional inventory measurement protocols to allow more refined analysis of diversity patterns. On the other hand, functional diversity can be easily implemented in diversity analyses, as it requires species abundance information (which is traditionally collected in forest inventory) and species-specific tree traits which can be inferred from literature. © 2019 Elsevier Ltd
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2019
Rivista
Ecological Indicators
Dettagli
Vol. 104 pp. 576 - 587
DOI
Estimating tree diversity in forest ecosystems by two-phase inventories
Corona , P. , Fattorini , Lorenzo , Franceschi , Sara , Marcheselli , Marzia , Pisani , Caterina , Chiavetta , U. , Puletti , Nicola
biodiversity tessellation stratified sampling two-phase sampling
Mostra abstract
Several studies reveal that there is a strong interconnection between climate change and biodiversity. Indeed, estimating plant biodiversity is an important issue under forest ecosystem monitoring, which allows the evaluation of carbon storage and sequestration capacity. To this end, a two-phase strategy, suitably compatible with the most adopted sampling designs in large-scale forest inventories, is proposed. In the first phase, tessellation stratified sampling is performed by partitioning the study area into a grid of quadrats and by randomly selecting a point in each quadrat. The first-phase points are classified as forest or nonforest using remotely sensed imagery. In the second phase, a sample of points is selected from those classified as forest by means of simple random sampling without replacement. The second-phase points constitute the centers of circular plots that are visited in the field to record plant species (usually trees) and their abundance. Estimators of abundance and diversity and estimators of their variances are presented. The proposed strategy is applied in a forest area from Central Italy, as a case study. With respect to the sampling effort, the resulting estimates of relative standard errors are satisfactory, especially those regarding the overall total and diversity index estimators. The proposed statistical approach represents a suitable reference for integrated forest inventory frameworks effectively supporting biodiversity monitoring and assessment. © 2018 John Wiley & Sons, Ltd.
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2019
Rivista
Environmetrics
Dettagli
Vol. 30 (2)
DOI
A PLOT SAMPLING STRATEGY FOR ESTIMATING THE AREA OF OLIVE TREE CROPS AND OLIVE TREE ABUNDANCE IN A MEDITERRANEAN ENVIRONMENT
Grotti , Mirko , Puletti , Nicola , Chianucci , Francesco , Mattioli , Walter , Floris , Antonio , Clementel , Fabrizio , Torresan , C. , Marchi , Maurizio , Gentile , Alessandra , Pisante , Michele , Marcelli , Agnese , Corona , P.
tessellation stratified sampling olea europaea olive crops inventory
Mostra abstract
Accurate inventory and mapping of olive (Olea europaea L.) tree attributes represents a central issue to support the olive production system. With reference to the cultivation, there is a high heterogeneity and complexity in the cultivation of olive trees, which is reflected in the large variability in olive grove surfaces. This poses some challenge in accurately estimating olive tree attributes via traditional inventory approaches, as commonly adopted in national forest inventory. From a methodological point of view, the complexity and heterogeneity of olive tree groves can be comparable to the problem of accurately estimating tree outside forests (TOF) attributes. In this study, we tested whether a plot sampling approach formerly developed for TOF is suitable for estimating olive tree attributes at large scale. We tested this approach in a case study where the census of the olive crop area and the number of olive groves was conducted from photo-interpretation of high resolution aerial orthoimagery, used as benchmark to test the effectiveness of the plot sampling approach. The main result of this study is that the plot sampling method can be applied for estimating olive tree attributes. Our obtained RSEs were below 20%, with a limited sampling effort of about 6% of the studied population; the obtained RSEs were below 6% when increasing sampling up to about 21% the studied population. Using robust statistical procedures among countries, should allow obtaining harmonized and comparable information, which can increase the knowledge of olive geographical distribution and structure at its relevant Mediterranean scale. © 2019, Italian Society of Remote Sensing. All rights reserved.
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2019
Rivista
Trends in Earth Observation
Dettagli
Vol. 1 pp. 11 - 14
Towards the economic valuation of ecosystem production from cork oak forests in sardinia (Italy)
Corona , P. , Quatrini , Valerio , Schirru , Matilde Silvia , Dettori , Sandro , Puletti , Nicola
forest management carbon sequestration cork production fodder production water yield
Mostra abstract
A spatially explicit approach for stand-scale economic valuation of current and future potential of cork forests with respect to ecosystem production is developed and presented. The approach, which relies in large part on the mensura-tion of stand top height and number of trees as main drivers, has been tested on the pure cork forests of Sardinia (Italy). The test was conducted to assess the effects of alternative silvicultural options on cork and fodder production, carbon sequestration, and water yield. Under current conditions, the surveyed pure cork oak forest stands in Sardinia are characterized, on average, by an annual economic production of 93 euro ha<sup>-1</sup> yr<sup>-1</sup> as concerns cork, 37 euro ha<sup>-1</sup> yr<sup>-1</sup> as concerns carbon sequestration and 261 euro ha<sup>-1</sup> yr<sup>-1</sup> as concerns water yield. The value of cork production on an 11-year cycle equals 1023 euro ha<sup>-1</sup> on average. The total economic production values among the tested silvicultural alternatives have proven to be characterized by relatively small differences, due to the trade-offs among the considered goods and services. Therefore, at least under conditions similar to those surveyed, managers may safely rely on different stand density options, without any relevant detrimental effect on total economic production. The tested spatial visualization of the economic values of goods and services production can be useful in supporting forest management planning, e.g., to identify priority areas in order to maximize ecosystem production for local communities. The approach proposed here and tested to this end proves to be readily applicable to other cork contexts with similar characteristics under Mediterranean conditions. © SISEF.
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2018
Rivista
IForest
Dettagli
Vol. 11 (5) pp. 660 - 667
DOI
Quantitative changes of forest landscapes over the last century across Italy
Camarretta , Nicolò , Puletti , Nicola , Chiavetta , U. , Corona , P.
forest fragmentation forest patchiness land cover change landscape metrics spatial pattern analysis
Mostra abstract
A key topic in landscape ecology and vegetation science is the quantitative analysis of changes in forest cover over time, through the use of geomatics monitoring tools. Ecologists and landscape researchers are pointing out that a full understanding of ecosystems and landscapes should be based on the analysis of their functioning over long time series. Under this perspective, a long-term historical reconstruction of forest cover is essential. This study has aimed at examining the long-term dynamics of forest landscapes in Italy, over the last century, using recent remote-sensing based map (2012) and an accurate historical map (1936). A forest-non forest approach has been followed by the computation of a variety of landscape metrics using two analysis tools, with the final objective of quantifying changes in forest cover patterns and in the composition of specific landscape elements. Results show that forest landscape structure has significantly changed across Italy, resulting in a general trend of decreasing fragmentation and patchiness, mainly through enlargement of existing forest patches, which have also assumed a more geometrically regular shape. In relative terms, the greatest expansion of forest areas has occurred mainly in lowland districts characterised by the highest level of human pressure in the country. © 2017 Società Botanica Italiana.
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2018
Rivista
Plant Biosystems
Dettagli
Vol. 152 (5) pp. 1011 - 1019
DOI
Inference on forest attributes and ecological diversity of trees outside forest by a two-phase inventory
Marchetti , Marco , Garfì , Vittorio , Pisani , Caterina , Franceschi , Sara , Marcheselli , Marzia , Corona , P. , Puletti , Nicola , Vizzarri , Matteo , Di Cristofaro , Marco , Ottaviano , Marco , Fattorini , Lorenzo
carbon stock diversity estimation field survey molise region (italy) sampling tree inventory
Mostra abstract
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<sup>−1</sup>). 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.
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2018
Rivista
Annals of Forest Science
Dettagli
Vol. 75 (2)
DOI
A spatio-temporal dataset of forest mensuration for the analysis of tree species structure and diversity in semi-natural mixed floodplain forests
Fardusi , Most Jannatul , Castaldi , Cristiano , Chianucci , Francesco , Corona , P. , Mason , Franco , Minari , Emma , Puletti , Nicola
spatial diversity point pattern analysis spatio-temporal analysis tree diversity tree-level forest inventory
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2018
Rivista
Annals of Forest Science
Dettagli
Vol. 75 (1)
DOI
Integrating terrestrial and airborne laser scanning for the assessment of single-tree attributes in Mediterranean forest stands
Giannetti , Francesca , Puletti , Nicola , Quatrini , Valerio , Travaglini , Davide , Bottalico , Francesca , Corona , P. , Chirici , Gherardo
lidar remote sensing precision forestry forest structure forest inventories proximal sensing
Mostra abstract
The development of laser scanning technologies has gradually modified methods for forest mensuration and inventory. The main objective of this study is to assess the potential of integrating ALS and TLS data in a complex mixed Mediterranean forest for assessing a set of five single-tree attributes: tree position (TP), stem diameter at breast height (DBH), tree height (TH), crown base height (CBH) and crown projection area radii (CPAR). Four different point clouds were used: from ZEB1, a hand-held mobile laser scanner (HMLS), and from FARO® FOCUS 3D, a static terrestrial laser scanner (TLS), both alone or in combination with ALS. The precision of single-tree predictions, in terms of bias and root mean square error, was evaluated against data recorded manually in the field with traditional instruments. We found that: (i) TLS and HMLS have excellent comparable performances for the estimation of TP, DBH and CPAR; (ii) TH was correctly assessed by TLS, while the accuracy by HMLS was lower; (iii) CBH was the most difficult attribute to be reliably assessed and (iv) the integration with ALS increased the performance of the assessment of TH and CPAR with both HMLS and TLS. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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2018
Rivista
European Journal of Remote Sensing
Dettagli
Vol. 51 (1) pp. 795 - 807
DOI
Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data
Vaglio Laurin , Gaia , Balling , Johannes , Corona , P. , Mattioli , Walter , Papale , Dario , Puletti , Nicola , Rizzo , Maria , Truckenbrodt , John , Urban , Marcel
sentinel-1 alos2 forest above-ground biomass
Mostra abstract
The objective of this research is to test Sentinel-1 SAR multitemporal data, supported by multispectral and SAR data at other wavelengths, for fine-scale mapping of above-ground biomass (AGB) at the provincial level in a Mediterranean forested landscape. The regression results indicate good accuracy of prediction (R2=0.7) using integrated sensors when an upper bound of 400Mg ha-1 is used in modeling. Multitemporal SAR information was relevant, allowing the selection of optimal Sentinel-1 data, as broadleaf forests showed a different response in backscatter throughout the year. Similar accuracy in predictions was obtained when using SAR multifrequency data or joint SAR and optical data. Predictions based on SAR data were more conservative, and in line with those from an independent sample from the National Forest Inventory, than those based on joint data types. The potential of S1 data in predicting AGB can possibly be improved if models are developed per specific groups (deciduous or evergreen species) or forest types and using a larger range of ground data. Overall, this research shows the usefulness of Sentinel-1 data to map biomass at very high resolution for local study and at considerable carbon density. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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2018
Rivista
Journal of Applied Remote Sensing
Dettagli
Vol. 12 (1)
DOI
Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests
Vaglio Laurin , Gaia , Puletti , Nicola , Chen , Qi , Corona , P. , Papale , Dario , Valentini , Riccardo
lidar biomass species richness carbon monitoring tropical forests west africa
Mostra abstract
Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R<sup>2</sup> = 0.72) and species richness (R<sup>2</sup> = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment. © 2016 Elsevier B.V.
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2016
Rivista
International Journal of Applied Earth Observation and Geoinformation
Dettagli
Vol. 52 pp. 371 - 379
DOI
Checking the performance of point and plot sampling on aerial photoimagery of a large-scale population of trees outside forests
Fattorini , Lorenzo , Puletti , Nicola , Chirici , Gherardo , Corona , P. , Gazzarri , C. , Mura , Matteo , Marchetti , Marco
tessellation stratified sampling two-phase sampling design-based estimation one-per-stratum stratified sampling
Mostra abstract
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.
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2016
Rivista
Canadian Journal of Forest Research
Dettagli
Vol. 46 (11) pp. 1264 - 1274
DOI
Evaluating EO1-Hyperion capability for mapping conifer and broadleaved forests
Puletti , Nicola , Camarretta , Nicolò , Corona , P.
random forest mediterranean areas hyperspectral images image classification multivariate adaptive regression splines support vector machine
Mostra abstract
The objective of the present study is the comparison of the combined use of Earth Observation-1 (EO-1) Hyperion Hyperspectral images with the Random Forest (RF), Support Vector Machines (SVM) and Multivariate Adaptive Regression Splines (MARS) classifiers for discriminating forest cover groups, namely broadleaved and coniferous forests. Statistics derived from classification confusion matrix were used to assess the accuracy of the derived thematic maps. We demonstrated that Hyperion data can be effectively used to obtain rapid and accurate large-scale mapping of main forest types (conifers-broadleaved). We also verified higher capability of Hyperion imagery with respect to Landsat data to such an end. Results demonstrate the ability of the three tested classification methods, with small improvements given by SVM in terms of overall accuracy and kappa statistic. © 2016 by the authors; licensee Italian Society of Remote Sensing (AIT).
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2016
Rivista
European Journal of Remote Sensing
Dettagli
Vol. 49 pp. 157 - 169
DOI
Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data
Vaglio Laurin , Gaia , Puletti , Nicola , Hawthorne , William D. , Liesenberg , Veraldo , Corona , P. , Papale , Dario , Chen , Qi , Valentini , Riccardo
forest sentinel-2 dominant species forest type functional composition guilds hyperspectral tropical
Mostra abstract
To answer new scientific and ecological questions and monitor multiple forest changes, a fine scale characterization of these ecosystems is needed, and could imply the mapping of specific species, of detailed forest types, and of functional composition. This characterization can be now provided by the novel Earth Observation tools. This study aims to contribute to understanding the innovation in forest and ecological research that can be brought in by advanced remote sensing instruments, and proposes the guild mapping approach as a tool to efficiently monitor the varied tropical forest resources. We evaluated, in tropical Ghanaian forests, the ability of airborne hyperspectral and simulated multispectral Sentinel-2 data, and derived vegetation indices and textures, to: distinguish between two different forest types; to discriminate among selected dominant species; and to separate trees species grouped according to their functional guilds: Pioneer, Non Pioneer Light Demanding, and Shade Bearer. We then produced guild classification maps for each area using hyperspectral data. Our results showed that with both hyperspectral and simulated Sentinel-2 data these discrimination tasks can be successfully accomplished. Results also stressed the importance of texture features, especially if using the lower spectral and spatial Sentinel-2 resolution data, and highlighted the important role of the new Sentinel-2 data for ecological monitoring. Classification results showed a statistically significant improvement in overall accuracy using Support Vector Machine, over Maximum Likelihood approach. We proposed the functional guilds mapping as an innovative approach to: (i) monitor compositional changes, especially with respect to the effects of global climate change on forests, and particularly in the tropical biome where the occurrence of hundreds of species prevents mapping activities at species level; (ii) support large-scale forest inventories. The imminent Sentinel-2 data could serve to open the road for the development of new concepts and methods in forestry and ecological research. © 2016 Elsevier Inc.
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2016
Rivista
Remote Sensing of Environment
Dettagli
Vol. 176 pp. 163 - 176
DOI
Quantifying the effect of sampling plot size on the estimation of structural indicators in old-growth forest stands
Lombardi , Fabio , Marchetti , Marco , Corona , P. , Merlini , Paolo , Chirici , Gherardo , Tognetti , Roberto , Burrascano , Sabina , Alivernini , Alessandro , Puletti , Nicola
beech forests forest structure italy deadwood survey simulation
Mostra abstract
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 m<sup>2</sup> 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.
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2015
Rivista
Forest Ecology and Management
Dettagli
Vol. 346 pp. 89 - 97
DOI
Prediction of forest NPP in Italy by the combination of ground and remote sensing data
Chirici , Gherardo , Chiesi , Marta , Corona , P. , Puletti , Nicola , Mura , Matteo , Maselli , Fabio
italy forest inventory biome-bgc current annual increment modified c-fix regional estimates
Mostra abstract
Our research group has recently proposed a strategy to simulate net forest carbon fluxes based on the coupling of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC. The outputs of the two models are combined through the use of a proxy of ecosystem distance from equilibrium condition which accounts for the occurred disturbances. This modeling strategy is currently applied to all Italian forest areas using an available set of NDVI images and ancillary data descriptive of an 8-year period (1999–2006). The obtained estimates of forest net primary production (NPP) are first analyzed in order to assess the importance of the main model drivers on relevant spatial variability. This analysis indicates that growing stock is the most influential model driver, followed by forest type and meteorological variables. In particular, the positive influence of growing stock on NPP can be constrained by thermal and water limitations, which are most evident in the upper mountain and most southern zones, respectively. Next, the NPP estimates, aggregated over seven main forest types and twenty administrative regions in Italy, are converted into current annual increment of standing volume (CAI) by specific coefficients. The accuracy of these CAI estimates is finally assessed by comparison with the ground data collected during a recent national forest inventory. The results obtained indicate that the modeling approach tends to overestimate the ground CAI for most forest types. In particular, the overestimation is notable for forest types which are mostly managed as coppice, while it is negligible for high forests. The possible origins of these phenomena are investigated by examining the main model drivers together with the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis. © 2015, Springer-Verlag Berlin Heidelberg.
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2015
Rivista
European Journal of Forest Research
Dettagli
Vol. 134 (3) pp. 453 - 467
DOI
Integrated forest management to prevent wildfires under mediterranean environments
Corona , P. , Ascoli , Davide , Barbati , Anna , Bovio , Giovanni , Colangelo , Giuseppe , Elia , Mario , Garfì , Vittorio , Iovino , Francesco , Lafortezza , Raffaele , Leone , Vittorio , Lovreglio , Raffella , Marchetti , Marco , Marchi , Enrico , Menguzzato , Giuliano , Nocentini , Susanna , Picchio , Rodolfo , Portoghesi , Luigi , Puletti , Nicola , Sanesi , Giovanni , Chianucci , Francesco
forest fuel management prescribed burning wildfuire prevention wildland-urban interface
Mostra abstract
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.
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2015
Rivista
Annals of Silvicultural Research
Dettagli
Vol. 39 (1) pp. 1 - 22
DOI
Estimation of leaf area index in isolated trees with digital photography and its application to urban forestry
Chianucci , Francesco , Puletti , Nicola , Giacomello , Elena , Cutini , Andrea , Corona , P.
leaf area index image analysis urban greening urban tree vegetation index
Mostra abstract
Accurate estimates of leaf area index (L) are strongly required for modelling ecophysiological processes within urban forests. The majority of methods available for estimating L is ideally applicable at stand scale and is therefore poorly suitable in urban settings, where trees are typically sparse and isolated. In addition, accurate measurements in urban settings are hindered by proximity of trees to infrastructure elements, which can strongly affect the accuracy of tree canopy analysis.In this study we tested whether digital photography can be used to obtain indirect estimate of L of isolated trees. The sampled species were Platanus orientalis, Liquidambar styraciflua and Juglans regia. Upward-facing photography was used to estimate gap fraction and foliage clumping from images collected in unobstructed (open areas) and obstructed (nearby buildings) settings; two image classification methods provided accurate estimates of gap fraction, based on comparison with measurements obtained from a high quality quantum sensor (LAI-2000). Leveled photography was used to characterize the leaf angle distribution of the examined tree species. L estimates obtained combining the two photographic methods agreed well with direct L measurements obtained from harvesting. We conclude that digital photography is suitable for estimating leaf area in isolated urban trees, due to its simple, fast and cost-effective procedures. Use of vegetation indices allows extending significantly the applicability of the photographic method in urban settings, including green roofs and vertical greenery systems. © 2015 Elsevier GmbH.
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2015
Rivista
Urban Forestry and Urban Greening
Dettagli
Vol. 14 (2) pp. 377 - 382
DOI
Estimation of leaf area index in understory deciduous trees using digital photography
Chianucci , Francesco , Cutini , Andrea , Corona , P. , Puletti , Nicola
foliage cover digital nadir photography foliage projection coefficient leaf angle distribution leveled camera
Mostra abstract
Fast and accurate estimates of understory leaf area are essential to a wide range of ecological applications. Indirect methods have mainly been used to estimate leaf area of overstory but their application in understory remains largely unexplored. In this study we described a combination of digital photographic methods to obtain rapid, reliable and non-destructive estimate of leaf area index of understory deciduous trees. Nadir photography was used to estimate foliage cover, vertical gap fraction and foliage clumping index. Leveled photography was used to characterize the leaf angle distribution of the examined tree species. Leaf area index estimates obtained combining the two photographic methods were compared with direct measurements obtained from harvesting (. L).We applied these methods in Quercus cerris, Carpinus betulus and Fagus sylvatica stands. Foliage cover estimates derived from two nadir image classification methods were significantly correlated with leaf area index measurements obtained from harvesting. The leveled digital photographic method, previously tested in tall trees and field crops, provided reliable leaf angle measurements in understory tree species. Digital photography provided good indirect estimates of L. We conclude that digital photography is suitable for routine estimate and monitoring of understory leaf area, on account of its fast and cost-effective procedure. © 2014 Elsevier B.V.
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2014
Rivista
Agricultural and Forest Meteorology
Dettagli
Vol. 198 pp. 259 - 264
DOI
Is randomized branch sampling suitable to assess wood volume of temperate broadleaved old-growth forests?
Chirici , Gherardo , Puletti , Nicola , Salvati , Riccardo , Arbi , Francesco , Zolli , Catherine , Corona , P.
precision horvitz-thompson estimation old-growth randomized branch sampling simulation tree climbing
Mostra abstract
Old-growth forests are characterized by the presence of large and very large trees. The estimation of their wood volume and biomass is essential in order to monitor the ecological processes in these stands and their contribution to carbon cycle. However, conventional wood volume estimation techniques based on mensuration of stem diameter at breast height and tree height is most often unfeasible for large and very large trees in old-growth forests because volume models or tables are usually elaborated from trees of smaller size grown up in regularly managed forest stands. Random Branch Sampling (RBS) is often proposed as a possible estimation alternative under such conditions. Starting from the ground level some of the parts of the main trunk and of the branches are sampled and measured to estimate the overall wood volume (or other biophysical variables). The application of RBS in old-growth forests, where tree cutting is usually forbidden or very difficult, requires that the crown of the tree can physically be reached to measure the sampled parts. We argue that under such conditions it is usually preferable to fully measure all the components of the tree crown because RBS estimates are not precise if based on only one sampling path and that, on the other hand, measuring the main trunk and all the branches by tree-climbing consumes the same time as replicating several RBS paths on the same tree. To demonstrate our hypothesis we selected 16 large beech trees located in the old-growth forest of Mount Cimini in Central Italy. Using a modern tree-climbing approach the main trunk and all the branches were measured and recorded in the field. The database was used to simulate RBS paths. Real values from volume census were contrasted with estimates based on RBS. On the whole, RBS estimates based on one single path prove to be highly imprecise. Even for trees characterized by a rather regular form, at least three RBS paths should be repeated on the same tree to maintain the relative standard error under or near 15%. This paper introduces the problem and describes the experimental test. The results are discussed under the perspective of standardized application of the proposed methodology. © 2013 Elsevier B.V.
🔗 Vai alla pubblicazione
2014
Rivista
Forest Ecology and Management
Dettagli
Vol. 312 pp. 225 - 230
DOI
Evaluating the effects of environmental changes on the gross primary production of Italian forests
Maselli , Fabio , Moriondo , Marco , Chiesi , Marta , Chirici , Gherardo , Puletti , Nicola , Barbati , Anna , Corona , P.
mediterranean forest modified c-fix environmental change gpp
Mostra abstract
A ten-year data-set descriptive of Italian forest gross primary production (GPP) has been recently constructed by the application of Modified C-Fix, a parametric model driven by remote sensing and ancillary data. That data-set is currently being used to develop multivariate regression models which link the inter-year GPP variations of five forest types (white fir, beech, chestnut, deciduous and evergreen oaks) to seasonal values of temperature and precipitation. The five models obtained, which explain from 52% to 88% of the interyear GPP variability, are then applied to predict the effects of expected environmental changes (+2 °C and increased CO<inf>2</inf> concentration). The results show a variable response of forest GPP to the simulated climate change, depending on the main ecosystem features. In contrast, the effects of increasing CO<inf>2</inf> concentration are always positive and similar to those given by a combination of the two environmental factors. These findings are analyzed with reference to previous studies on the subject, particularly concerning Mediterranean environments. The analysis confirms the plausibility of the scenarios obtained, which can cast light on the important issue of forest carbon pool variations under expected global changes. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
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2009
Rivista
Remote Sensing
Dettagli
Vol. 1 (4) pp. 1108 - 1124
DOI
Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems
Maselli , Fabio , Papale , Dario , Puletti , Nicola , Chirici , Gherardo , Corona , P.
ndvi forest gpp c-fix fapar
Mostra abstract
This paper describes the development and testing of a procedure which combines remotely sensed and ancillary data to monitor forest productivity in Italy. The procedure is based on a straightforward parametric model (C-Fix) that uses the relationship between the fraction of photosynthetically active radiation absorbed by plant canopies (fAPAR) and relevant gross primary productivity (GPP). Estimates of forest fAPAR are derived from Spot-VGT NDVI images and are combined with spatially consistent data layers obtained by the elaboration of ground meteorological measurements. The original version of C-Fix is first applied to estimate monthly GPP of Italian forests during eight years (1999-2006). Next, a modification of the model is proposed in order to simulate the short-term effect of summer water stress more efficiently. The accuracy of the original and modified C-Fix versions is evaluated by comparison with GPP data taken at eight Italian eddy covariance flux tower sites. The experimental results confirm the capacity of C-Fix to monitor national forest GPP patterns and indicate the utility of considering the short-term effect of water stress during Mediterranean dry months. © 2008 Elsevier Inc. All rights reserved.
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2009
Rivista
Remote Sensing of Environment
Dettagli
Vol. 113 (3) pp. 657 - 667
DOI
Indicators for the assessment and certification of cork oak management sustainability in Italy
Pollastrini , M. , Chiavetta , U. , Cutini , Andrea , Casula , Antonio , Maltoni , Sara , Dettori , Sandro , Corona , P.
italy forest management planning non-wood forest products quercus suber sardinia sustainable forest management
Mostra abstract
Sustainable forest management (SFM) is crucial for forest ecosystem productivity and conservation, especially in systems such as cork oak (Quercus suber L.) threatened by human activities and biotic and abiotic factors. In this study SFM indicators with particular reference to cork oak forests in the region of Sardinia (Italy) are proposed and tested. Sustainable and responsible management options specifically aimed at cork oak forest management and chain of custody certification are also provided. A set of ten indicators was proposed and assessed by an expert panel in cork oak management. Five indicators were also tested against data on structure, origin, health condition and management in 285 forest compartments managed by FoReSTAS (Regional Forest Agency for Land and Environment of Sardinia, Italy), including 361 sampling plots and 5345 trees. In order to investigate the priorities and perceptions of SFM experts and stakeholders, a survey was also carried out by completion of a questionnaire on the technical issues of cork oak woodland management. The survey results highlighted a need to improve environmental and economic performance by means of SFM and certification. The indicators tested in Sardinian cork oak woodlands showed that about 80% of the stands fulfilled management sustainability requirements. The suggested SFM indicators can effectively support proactive management and conservation measures, representing a valuable tool in the current context of growing environmental and socioeconomic awareness. © SISEF.
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2018
Rivista
IForest
Dettagli
Vol. 11 (5) pp. 668 - 674
DOI
Forest-food nexus: A topical opportunity for human well-being and silviculture
P. Corona , A. Cutini , U. Chiavetta , E. Paoletti
forest silviculture food safety security
Mostra abstract
As population will reach over 9 billion by 2050, interest in the forest-food nexus is rising. Forests play an important role in food production and nutrition. Forests can provide nutritionally-balanced diets, woodfuel for cooking and a broad set of ecosystem services. A large body of evidence recommends multi-functional and integrated landscape approaches to reimagine forestry and agriculture systems. Here, after an in-depth commented discussion of the literature produced in the last decade about the role for forests with respect to the food security global emergency, we summarize the state of the art in Italy as a country-case-study. This commentary aims to increase awareness about the potential of silviculture in Italy for combining ecological resilience with economic resilience, and for reasonably increasing non-wood products supply by means of a sustainable intensification of forest management at national level. Chain-supply fragmentation, landowner inertia, and lack of governance and cooperation may hamper an effective exploitation of non-wood products. The strategies to guarantee an effective supply of non-wood products require appropriate business skills and the presence of a structured business service. A transparent market is also essential; therefore, the introduction of standards (e.g. grading rules and forest certification schemes) is important since they can add value to products and services, and emphasize the importance and complexity of the forest sector. However, the implementation of sustainable forest management for an effective supply of non-wood products is affected by the availability of appropriate planning tools, and the public officers need a new mindset to stimulate and support the business capacity of forest owners.
🔗 Vai alla pubblicazione
2016
Rivista
Annals of Silvicultural Research
Dettagli
Vol. 40
DOI
ISSN
2284354X
Trends of ungulate species in Europe: not all stories are equal
Cerri , Jacopo , Chirichella , Roberta , Arnold , Walter , Bartoš , Luděk , Borowik , Tomasz , Carranza , Juan , Chianucci , Francesco , Csányi , Sándor , Ericsson , Göran , Heurich , Marco , Kojola , Ilpo , Mysterud , Atle , Pokorny , Boštjan , Schmidt , Krzysztof , Šprem , Nikica , Vicente , Joaquín , Alagić , Ajša , Balčiauskas , Linas , Casaer , Jim , Cellina , Sandra , Done , Gundega , Find’o , Slavomír , Fonseca , Carlos M.M.S. , Gačić , Dragan P. , Melovski , Dime , Ozoliņš , Jânis , Papaioannou , Haritakis I. , Pusenius , Jyrki , Randveer , Tiit , Ruusila , Vesa , Saint-Andrieux , Christine , Veeroja , Rauno , Apollonio , Marco
hunting bags reforestation rural abandonment time-series analysis wild ungulates wildlife management
Mostra abstract
Wild ungulates have deep impacts on socio-ecological systems, and analyzing large-scale population trends in a multispecies set can identify their environmental and socio-economic drivers. We collected annual hunting bags (n = 11,046, period 1975–2018) of European roe deer, red deer, wild boar, fallow deer, mouflon, northern chamois and moose, across Europe. We identified different temporal trends in their hunting bags and evaluated the social and environmental drivers of their relative abundances. The number of harvested red deer and fallow deer, increased steadily across Europe, with minor differences among countries, despite variations in land use and climate. On the contrary, European roe deer harvests have decreased in six European countries since the late 1990s, probably due to landscape changes and locally also due to predation, interspecific competition, and/or increasing temperatures. Northern chamois harvests in Austria and Switzerland have decreased markedly, probably due to increasing temperatures, which decrease the survival of kids at high altitudes. Wild boar harvests have decreased in Poland, Estonia, Latvia, and Lithuania since the African Swine Fever outbreak in 2013–2014. Minor differences emerged between countries adopting different management regimes for wild ungulates. While many studies pointed out landscape changes as the cornerstone for the increase in wild ungulates across Europe, our research emphasizes important species-specific differences. There is a need to predict how landscape dynamics, climate change and recovering large carnivores will affect populations of species already showing signs of decline, like the European roe deer or the northern chamois. © The Author(s), under exclusive licence to Mammal Research Institute Polish Academy of Sciences 2026.
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2026
Rivista
Mammal Research
Dettagli
Vol. 71 (2)
DOI
Testing Removal of Carbon Dioxide, Ozone, and Atmospheric Particles by Urban Parks in Italy
Fares , Silvano , Conte , Adriano , Alivernini , Alessandro , Chianucci , Francesco , Grotti , Mirko , Zappitelli , Ilaria , Petrella , Fabio , Corona , P.
italy forestry carbon dioxide carbon dioxide process ecosystems gas emissions greenhouse gases ozone particles (particulate matter) atmospheric concentration atmospheric particles ecosystem services in-situ measurement multilayer canopy model particulate matter tree characteristics tropospheric ozone air pollution aerosol greenspace pollutant removal testing method urban area air quality article canopy dry deposition particulate matter 10 recreational park tree air pollutant city ecosystem air pollutants cities parks recreational trees
Mostra abstract
Cities are responsible for more than 80% of global greenhouse gas emissions. Sequestration of air pollutants is one of the main ecosystem services that urban forests provide to the citizens. The atmospheric concentration of several pollutants such as carbon dioxide (CO2), tropospheric ozone (O3), and particulate matter (PM) can be reduced by urban trees through processes of adsorption and deposition. We predict the quantity of CO2, O3, and PM removed by urban tree species with the multilayer canopy model AIRTREE in two representative urban parks in Italy: Park of Castel di Guido, a 3673 ha reforested area located northwest of Rome, and Park of Valentino, a 42 ha urban park in downtown Turin. We estimated a total annual removal of 1005 and 500 kg of carbon per hectare, 8.1 and 1.42 kg of ozone per hectare, and 8.4 and 8 kg of PM10 per hectare. We highlighted differences in pollutant sequestration between urban areas and between species, shedding light on the importance to perform extensive in situ measurements and modeling analysis of tree characteristics to provide realistic estimates of urban parks to deliver ecosystem services. ©
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2020
Rivista
Environmental Science and Technology
Dettagli
Vol. 54 (23) pp. 14910 - 14922
DOI
TRY plant trait database – enhanced coverage and open access
Kattge , Jens , Bönisch , Gerhard , Díaz , Sandra M. , Lavorel , Sandra , Prentice , Iain Colin , Leadley , Paul W. , Tautenhahn , Susanne , Werner , Gijsbert , Aakala , Tuomas , Abedi , Mehdi , Acosta , Alicia Teresa Rosario , Adamidis , George C. , Adamson , Kairi , Aiba , Masahiro , Albert , Cécile Hélène , Alcántara , Julio M. , Alcázar C , Carolina , Aleixo , Izabela , Ali , Hamada E. , Amiaud , Bernard , Ammer , Christian , Amoroso , Mariano Martín , Anand , Madhur , Anderson , Carolyn G. , Anten , Niels P.R. , Antos , Joseph A. , Apgaua , Deborah Mattos Guimarães , Ashman , Tia Lynn , Asmara , Degi Harja , Asner , Gregory P. , Aspinwall , Michael J. , Atkin , Owen K. , Aubin , Isabelle , Baastrup-Spohr , Lars , Bahalkeh , Khadijeh , Bahn , Michael , Baker , Timothy R. , Baker , William J. , Bakker , Jan P. , Baldocchi , Dennis D. , Baltzer , Jennifer L. , Banerjee , Arindam , Baranger , Anne , Barlow , Jos B. , Barneche , Diego R. , Baruch , Zdravko , Bastianelli , Denis , Battles , John J. , Bauerle , William L. , Bauters , Marijn , Bazzato , Erika , Beckmann , Michael , Beeckman , Hans , Beierkuhnlein , Carl , Bekker , Renée M. , Belfry , Gavin , Belluau , Michaël , Beloiu Schwenke , Mirela , Benavides , Raquel , Benomar , Lahcen , Berdugo-Lattke , Mary Lee , Berenguer , Erika , Bergamin , Rodrigo Scarton , Bergmann , Joana , Carlucci , Marcos B. , Berner , Logan T. , Bernhardt-Römermann , Markus , Bigler , Christof , Bjorkman , Anne D. , Blackman , Chris J. , Blanco , Carolina Casagrande , Blonder , Benjamin Wong , Blumenthal , Dana M. , Bocanegra-González , Kelly Tatiana , Boeckx , Pascal , Bohlman , Stephanie Ann , Böhning-Gaese , Katrin , Boisvert-Marsh , Laura , Bond , William J. , Bond-Lamberty , Ben P. , Boom , Arnoud , Boonman , Coline C.F. , Bordin , Kauane Maiara , Boughton , Elizabeth H. , Boukili , Vanessa K.S. , Bowman , David M.J.S. , Bravo , Sandra Josefina , Brendel , Marco R. , Broadley , Martin R. , Brown , Kerry A. , Bruelheide , Helge , Brumnich , Federico , Bruun , Hans Henrik , Bruy , David , Buchanan , Serra Willow , Bucher , Solveig Franziska , Buchmann , Nina , Buitenwerf , Robert , Bunker , Daniel E. , Bürger , Jana
functional diversity data coverage data integration data representativeness plant traits try plant trait database
Mostra abstract
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives. © 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd
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2020
Rivista
Global Change Biology
Dettagli
Vol. 26 (1) pp. 119 - 188
DOI
Where are we now with European forest multi-taxon biodiversity and where can we head to?
Burrascano , Sabina , Chianucci , Francesco , Trentanovi , Giovanni , Kepfer-Rojas , Sebastian , Sitzia , Tommaso , Tinya , Flóra , Doerfler , Inken , Paillet , Yoan , Nagel , Thomas A. , Mitić , Božena , Morillas , Lourdes , Munzi , Silvana , Van Der Sluis , Theo , Alterio , Edoardo , Balducci , Lorenzo , de Andrade , Rafael Barreto , Bouget , Christophe , Giordani , P. , Lachat , Thibault , Matošević , Dinka , Napoleone , Francesca , Nascimbene , Juri , Paniccia , Chiara , Roth , Nicolas , Aszalós , Réka , Brazaitis , Gediminas , Cutini , Andrea , D'Andrea , Ettore , de Smedt , Pallieter , Heilmann-Clausen , Jacob , Janssen , Philippe , Kozák , Daniel , Mårell , Anders , Mikoláš , Martin , Nordén , Björn , Matula , Radim , Schall , Peter , Svoboda , Miroslav , Ujházyová , Mariana , Vandekerkhove , Kris , Wohlwend , Michael Rudolf , Xystrakis , Fotios , Aleffi , Michele , Ammer , Christian , Archaux , Frédéric , Asbeck , Thomas , N Avtzis , Dimitrios N. , Ayasse , Manfred , Bagella , Simonetta , Balestrieri , Rosario , Barbati , Anna , Basile , Marco , Bergamini , Ariel , Bertini , Giada , Biscaccianti , Alessandro Bruno , Boch , Steffen , Bölöni , János , Bombi , Pierluigi , Boscardin , Yves , Brunialti , Giorgio , Bruun , Hans Henrik , Buscot , François , Byriel , David Bille , Campagnaro , Thomas , Campanaro , Alessandro , Chauvat , Matthieu , Ciach , Michał , Čiliak , Marek , Cistrone , Luca , Pereira , Joaò Manuel Cordeiro , Daniel , Rolf , de Cinti , Bruno , de Filippo , Gabriele , Dekoninck , Wouter , Di Salvatore , Umberto , Dumas , Yann , Elek , Zoltán , Ferretti , Fabrizio , Fotakis , Dimitrios G. , Frank , Tamás , Frey , Julian , Giancola , Carmen , Gömöryová , Erika , Gosselin , Marion , Gosselin , Frédéric , Goßner , Martin M. , Götmark , Frank , Haeler , Elena , Hansen , Aslak Kappel , Hertzog , Lionel R. , Hofmeister , Jeňýk , Hošek , Jan , Johannsen , Vivian Kvist , Justensen , Mathias Just , Korboulewsky , Nathalie , Kovács , Bence , Lakatos , Ferenc , Landivar , Carlos Miguel , Lens , Luc , Lingua , Emanuele
forest biodiversity biodiversity conservation forest stand structure multi-taxon sustainable management
Mostra abstract
The European biodiversity and forest strategies rely on forest sustainable management (SFM) to conserve forest biodiversity. However, current sustainability assessments hardly account for direct biodiversity indicators. We focused on forest multi-taxon biodiversity to: i) gather and map the existing information; ii) identify knowledge and research gaps; iii) discuss its research potential. We established a research network to fit data on species, standing trees, lying deadwood and sampling unit description from 34 local datasets across 3591 sampling units. A total of 8724 species were represented, with the share of common and rare species varying across taxonomic classes: some included many species with several rare ones (e.g., Insecta); others (e.g., Bryopsida) were represented by few common species. Tree-related structural attributes were sampled in a subset of sampling units (2889; 2356; 2309 and 1388 respectively for diameter, height, deadwood and microhabitats). Overall, multi-taxon studies are biased towards mature forests and may underrepresent the species related to other developmental phases. European forest compositional categories were all represented, but beech forests were over-represented as compared to thermophilous and boreal forests. Most sampling units (94%) were referred to a habitat type of conservation concern. Existing information may support European conservation and SFM strategies in: (i) methodological harmonization and coordinated monitoring; (ii) definition and testing of SFM indicators and thresholds; (iii) data-driven assessment of the effects of environmental and management drivers on multi-taxon forest biological and functional diversity, (iv) multi-scale forest monitoring integrating in-situ and remotely sensed information. © 2023 The Authors
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2023
Rivista
Biological Conservation
Dettagli
Vol. 284
DOI
Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients
Qiu , Tong , Aravena Acuña , Marie Claire , Ascoli , Davide , Bergeron , Yves , Bogdziewicz , Michał , Boivin , Thomas , Bonal , Raúl , Caignard , Thomas , Cailleret , Maxime , Calama , Rafael A. , Calderon , Sergio Donoso , Camarero , Jesús Julio , Chang-Yang , Chia Hao , Chave , Jérôme , Chianucci , Francesco , Courbaud , Benoít , Cutini , Andrea , Das , Adrian J. , Delpierre , Nicolas , Delzon , Sylvain , Dietze , Michael C. , Dormont , Laurent , Espelta , Josep Maria , Fahey , Timothy J. , Farfan-Rios , William R. , Franklin , Jerry F. , Gehring , Catherine A. , Gilbert , Gregory S. , Gratzer , Georg , Greenberg , Cathryn H. , Guignabert , Arthur , Guo , Qinfeng , Hacket-Pain , Andrew J. , Hampe , Arndt , Han , Qingmin , Holik , Jan , Hoshizaki , K. , Ibáñez , Inés , Johnstone , Jill F. , Journé , Valentin , Kitzberger , Thomas A. , Knops , Johannes Michael Hubertus , Kunstler , Georges , Kurokawa , Hiroko , Lageard , Jonathan G.A. , LaMontagne , Jalene M. , Lefèvre , François , Leininger , Theodor D. , Limousin , Jean Marc , Lutz , James A. , Macias , Diana S. , Mårell , Anders , McIntire , Eliot J.B. , Moore , Christopher M. , Moran , Emily V. , Motta , Renzo , Myers , Jonathan A. , Nagel , Thomas A. , Naoe , Shoji , Noguchi , Mahoko , Oguro , Michio , Parmenter , Robert R. , Pearse , Ian S. , Pérez-Ramos , Ignacio M. , Piechnik , Łukasz , Podgórski , Tomasz , Poulsen , John R. , Redmond , Miranda D. , Reid , Chantal D. , Rodman , Kyle C. , Rodríguez-Sánchez , Francisco , Šamonil , Pavel , Sanguinetti , Javier D. , Scher , C. Lane , Seget , Barbara , Sharma , Shubhi , Shibata , Mitsue , Silman , Miles R. , Steele , Michael A. , Stephenson , Nathan L. , Straub , Jacob N. , Sutton , Samantha , Swenson , Jennifer J. , Swift , Margaret , Thomas , Peter A. , Uríarte , María , Vacchiano , Giorgio , Whipple , Amy Vaughn , Whitham , Thomas G. , Wion , Andreas P. , Wright , Stuart Joseph , Zhu , Kai , Zimmerman , Jess K. , Żywiec , Magdalena , Clark , James S.
plant seed seeds tree trees reproduction fertility satiety satiation
Mostra abstract
The benefits of masting (volatile, quasi-synchronous seed production at lagged intervals) include satiation of seed predators, but these benefits come with a cost to mutualist pollen and seed dispersers. If the evolution of masting represents a balance between these benefits and costs, we expect mast avoidance in species that are heavily reliant on mutualist dispersers. These effects play out in the context of variable climate and site fertility among species that vary widely in nutrient demand. Meta-analyses of published data have focused on variation at the population scale, thus omitting periodicity within trees and synchronicity between trees. From raw data on 12 million tree-years worldwide, we quantified three components of masting that have not previously been analysed together: (i) volatility, defined as the frequency-weighted year-to-year variation; (ii) periodicity, representing the lag between high-seed years; and (iii) synchronicity, indicating the tree-to-tree correlation. Results show that mast avoidance (low volatility and low synchronicity) by species dependent on mutualist dispersers explains more variation than any other effect. Nutrient-demanding species have low volatility, and species that are most common on nutrient-rich and warm/wet sites exhibit short periods. The prevalence of masting in cold/dry sites coincides with climatic conditions where dependence on vertebrate dispersers is less common than in the wet tropics. Mutualist dispersers neutralize the benefits of masting for predator satiation, further balancing the effects of climate, site fertility and nutrient demands. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.
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2023
Rivista
Nature Plants
Dettagli
Vol. 9 (7) pp. 1044 - 1056
DOI
MASTREE+: Time-series of plant reproductive effort from six continents
Hacket-Pain , Andrew J. , Foest , Jessie J. , Pearse , Ian S. , LaMontagne , Jalene M. , Koenig , Walter D. , Vacchiano , Giorgio , Bogdziewicz , Michał , Caignard , Thomas , Celebias , Paulina , van Dormolen , Joep , Fernández-Martínez , Marcos , Moris , Jose V. , Palaghianu , Ciprian , Pesendorfer , Mario B. , Satake , Akiko , Schermer , Éliane , Tanentzap , Andrew J. , Thomas , Peter A. , Vecchio , Davide , Wion , Andreas P. , Wohlgemuth , Thomas , Xue , Tingting , Abernethy , Katharine A. , Aravena Acuña , Marie Claire , Barrera , Marcelo Daniel , Barton , Jessica H. , Boutin , Stan A. , Bush , Emma R. , Donoso Calderón , Sergio R. , Carevic , Felipe S. , Castilho , Carolina V. , Manuel Cellini , Juan , Chapman , Colin A. , Chapman , H. M. , Chianucci , Francesco , Costa , Patricia Da , Croisé , Luc , Cutini , Andrea , Dantzer , Ben J. , DeRose , Robert Justin , Dikangadissi , Jean Thoussaint , Dimoto , Edmond , da Fonseca , Fernanda Lopes , Gallo , Leonardo Ariel , Gratzer , Georg , Greene , David F. , Hadad , Martín Ariel , Huertas Herrera , Alejandro , Jeffery , Kathryn J. , Johnstone , Jill F. , Kalbitzer , Urs , Kantorowicz , Władysław , Klimas , Christie Ann , Lageard , Jonathan G.A. , Lane , Jeffrey E. , Lapin , Katharina , Ledwoń , Mateusz , Leeper , Abigail C. , Lencinas , María Vanessa , Lira-Guedes , Ana Cláudia , Lordon , Michael C. , Marchelli , Paula , Marino , Shealyn , Schmidt van Marle , Harald , McAdam , Andrew G. , Momont , Ludovic R.W. , Nicolas , Manuel , de Oliveira Wadt , Lúcia Helena , Panahi , Parisa , Martínez Pastur , Guillermo J. , Patterson , Thomas W. , Luis Peri , Pablo , Piechnik , Łukasz , Pourhashemi , Mehdi , Espinoza Quezada , Claudia , Roig , Fidel Alejandro , Peña-Rojas , Karen A. , Rosas , Yamina Micaela , Schueler , Silvio , Seget , Barbara , Soler , Rosina M. , Steele , Michael A. , Toro Manríquez , Mónica Del Rosario , Tutin , Caroline E.G. , Ukizintambara , Tharcisse , White , Lee J.T. , Yadok , Biplang Godwill , Willis , John L. , Zolles , Anita , Żywiec , Magdalena , Ascoli , Davide
plant reproduction masting demography flowering general flowering recruitment regeneration
Mostra abstract
Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
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2022
Rivista
Global Change Biology
Dettagli
Vol. 28 (9) pp. 3066 - 3082
DOI
Handbook of field sampling for multi-taxon biodiversity studies in European forests
Burrascano , Sabina , Trentanovi , Giovanni , Paillet , Yoan , Heilmann-Clausen , Jacob , Giordani , P. , Bagella , Simonetta , Bravo-Oviedo , Andrés , Campagnaro , Thomas , Campanaro , Alessandro , Chianucci , Francesco , de Smedt , Pallieter , Itziar , García Mijangos , Matošević , Dinka , Sitzia , Tommaso , Aszalós , Réka , Brazaitis , Gediminas , Cutini , Andrea , D'Andrea , Ettore , Doerfler , Inken , Hofmeister , Jeňýk , Hošek , Jan , Janssen , Philippe , Kepfer-Rojas , Sebastian , Korboulewsky , Nathalie , Kozák , Daniel , Lachat , Thibault , Lõhmus , Asko , López , Rosana , Mårell , Anders , Matula , Radim , Mikoláš , Martin , Munzi , Silvana , Nordén , Björn , Pärtel , Meelis , Penner , Johannes , Runnel , Kadri , Schall , Peter , Svoboda , Miroslav , Tinya , Flóra , Ujházyová , Mariana , Vandekerkhove , Kris , Verheyen , Kris , Xystrakis , Fotios , Ódor , Péter
biodiversity forest stand structure multi-taxon field methods indicators sampling protocol
Mostra abstract
Forests host most terrestrial biodiversity and their sustainable management is crucial to halt biodiversity loss. Although scientific evidence indicates that sustainable forest management (SFM) should be assessed by monitoring multi-taxon biodiversity, most current SFM criteria and indicators account only for trees or consider indirect biodiversity proxies. Several projects performed multi-taxon sampling to investigate the effects of forest management on biodiversity, but the large variability of their sampling approaches hampers the identification of general trends, and limits broad-scale inference for designing SFM. Here we address the need of common sampling protocols for forest structure and multi-taxon biodiversity to be used at broad spatial scales. We established a network of researchers involved in 41 projects on forest multi-taxon biodiversity across 13 European countries. The network data structure comprised the assessment of at least three taxa, and the measurement of forest stand structure in the same plots or stands. We mapped the sampling approaches to multi-taxon biodiversity, standing trees and deadwood, and used this overview to provide operational answers to two simple, yet crucial, questions: what to sample? How to sample? The most commonly sampled taxonomic groups are vascular plants (83% of datasets), beetles (80%), lichens (66%), birds (66%), fungi (61%), bryophytes (49%). They cover different forest structures and habitats, with a limited focus on soil, litter and forest canopy. Notwithstanding the common goal of assessing forest management effects on biodiversity, sampling approaches differed widely within and among taxonomic groups. Differences derive from sampling units (plots size, use of stand vs. plot scale), and from the focus on different substrates or functional groups of organisms. Sampling methods for standing trees and lying deadwood were relatively homogeneous and focused on volume calculations, but with a great variability in sampling units and diameter thresholds. We developed a handbook of sampling methods (SI 3) aimed at the greatest possible comparability across taxonomic groups and studies as a basis for European-wide biodiversity monitoring programs, robust understanding of biodiversity response to forest structure and management, and the identification of direct indicators of SFM. © 2021 The Authors
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2021
Rivista
Ecological Indicators
Dettagli
Vol. 132
DOI
THz water transmittance and leaf surface area: An effective nondestructive method for determining leaf water content
Pagano , Mario , Baldacci , Lorenzo , Ottomaniello , Andrea , Dato , Giovanbattista De , Chianucci , Francesco , Masini , Luca , Carelli , Giorgio , Toncelli , Alessandra , Storchi , Paolo , Tredicucci , Alessandro , Corona , P.
drought stress leaves plants terahertz quantum cascade laser water content
Mostra abstract
Water availability is a major limiting factor in plant productivity and plays a key role in plant species distribution over a given area. New technologies, such as terahertz quantum cascade lasers (THz‐QCLs) have proven to be non‐invasive, effective, and accurate tools for measuring and monitoring leaf water content. This study explores the feasibility of using an advanced THz-QCL device for measuring the absolute leaf water content in Corylus avellana L., Laurus nobilis L., Ostrya carpinifolia Scop., Quercus ilex L., Quercus suber L., and Vitis vinifera L. (cv. Sangiovese). A recently proposed, simple spectroscopic technique was used, consisting in determining the transmission of the THz light beam through the leaf combined with a photographic measurement of the leaf area. A significant correlation was found between the product of the leaf optical depth (τ) and the leaf surface area (LA) with the leaf water mass (Mw) for all the studied species (Pearson’s r test, p ≤ 0.05). In all cases, the best fit regression line, in the graphs of τLA as a function of Mw, displayed R2 values always greater than 0.85. The method proposed can be combined with water stress indices of plants in order to gain a better understanding of the leaf water management processes or to indirectly monitor the kinetics of leaf invasion by pathogenic bacteria, possibly leading to the development of specific models to study and fight them. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
🔗 Vai alla pubblicazione
2019
Rivista
Sensors (Switzerland)
Dettagli
Vol. 19 (22)
DOI
Development of digital photographic approaches to assess leaf traits in broadleaf tree species
Chianucci , Francesco , Ferrara , Carlotta , Pollastrini , M. , Corona , P.
foliar morphology foliar physiology functional leaf traits leaf optical properties leaf reflectance
Mostra abstract
Plants display a large number of traits which are reflected in physiological and ecological functions (functional traits). Leaf traits are amongst the most important functional traits. However, a great challenge in measuring leaf traits in the field is that direct methods are limited by the cost of the instruments and the time and work required by direct measurements, which are often destructive. As an alternative, we developed and tested a non-destructive methodology to assess a suite of leaf traits using different digital photographic approaches, with the intimate aim to develop a rapid, robust and cheap protocol for leaf trait measurements in the field. The proposed digital photographic approaches were tested in broadleaved tree species Digital photography allowed to assess a morphological foliar trait (leaf area; LA) and physiological foliar traits (leaf reflectance in red (R), green (G) and blue (B) bands; leaf venation attributes). Leaf area derived from photography significantly agreed with that directly measured with a leaf area meter (LA<inf>PHOTO</inf> = 0.98 LA<inf>AREA METER</inf> + 0.84, R<sup>2</sup> = 0.99, p < 0.001); leaf reflectance in the R, G, B channels derived from photography significantly agreed with that directly measured with a field spectroradiometer (SPEC) (R<inf>PHOTO</inf> = 0.77 R<inf>SPEC</inf> + 0.05, R<sup>2</sup> = 0.61, p < 0.001; G<inf>PHOTO</inf> = 0.79 G<inf>SPEC</inf> + 0.06, R<sup>2</sup> = 0.58, p < 0.001; B<inf>PHOTO</inf> = 0.56 B<inf>SPEC</inf> + 0.00, R<sup>2</sup> = 0.51, p < 0.001). Leaf venation traits estimated from photography agreed to within ±20% measurements obtained in cleared leaves of the same species. Based on the obtained results, we demonstrated that digital photography can be an effective tool to obtain a fast, cheap, reliable and non-destructive assessment of morphological and physiological leaf traits in broadleaf tree species, being highly suitable for use in long-term research and monitoring programs. © 2019 Elsevier Ltd
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2019
Rivista
Ecological Indicators
Dettagli
Vol. 106
DOI
Multi-temporal dataset of stand and canopy structural data in temperate and Mediterranean coppice forests
Chianucci , Francesco , Ferrara , Carlotta , Bertini , Giada , Fabbio , Gianfranco , Tattoni , Clara , Rocchini , Duccio , Corona , P. , Cutini , Andrea
leaf area index canopy gap fraction coppice management conversion litterfall
Mostra abstract
Key message: We provided long-term stand and canopy structural data from permanent monitoring plots representative of some most diffuse temperate and Mediterranean forests, under different coppice management regimes. Periodic inventories were performed in the surveyed plots since the 1970s. Annual litterfall production and its partitioning (leaf, woody, reproductive parts) and optical canopy measurements using the LAI-2000 Plant Canopy Analyzer were performed every year in fully equipped plots since the 1990s. These data can be used for evaluating the influence of coppice management in the stand and canopy structure, the parametrization of radiative transfer models that require accurate ground truth data, and the calibration of high to medium resolution remotely sensed data. Dataset access is at https://doi.org/10.17632/z8zm3ytkcx.2. Associated metadata is available at https://agroenvgeo.data.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/2bd2d77f-3cf8-43da-b1b5-9f8196dc017f . © 2019, INRA and Springer-Verlag France SAS, part of Springer Nature.
🔗 Vai alla pubblicazione
2019
Rivista
Annals of Forest Science
Dettagli
Vol. 76 (3)
DOI
Generalized biomass equations for Stone pine (Pinus pinea L.) across the Mediterranean basin
Correia , A. C. , Faias , Sónia Pacheco , Ruiz-Peinado , Ricardo , Chianucci , Francesco , Cutini , Andrea , Fontes , Luís , Manetti , Maria Chiara , Montero , Gregorio , Soares , P. , Tomé , Margarida
aboveground biomass allometry carbon estimation mixed models residual analysis root biomass simultaneous fitting
Mostra abstract
Accurate estimates of tree biomass are strongly required for forest carbon budget estimates and to understand ecosystem dynamics for a sustainable management. Existing biomass equations for Mediterranean species are scarce, stand- and site-specific and therefore are not suitable for large scale application. In this study, biomass allometric equations were developed for stone pine (Pinus pinea L.), a Mediterranean tree species with relevant ecologic and economic interest. A dataset of 283 harvested trees was compiled with above- and belowground biomass from 16 sites in three countries (Italy, Spain, Portugal) representative of the species’ geographical Mediterranean distribution. A preliminary approach comparing the ordinary least squares method and the mixed model approach was performed in order to evaluate the most appropriate method for nested data in the absence of calibration data. To quantify the sources of error associated with applying biomass equations beyond the geographical range of the data used to develop them, a residual analysis was conducted. The allometric analysis showed low intra-specific variability in aboveground biomass relationships, which was relatively insensitive to the stand and site conditions. Significant differences were found for the crown components (needles and branches), which may be attributed to local geographical adaptation, site conditions and stand management. The root biomass was highly correlated with diameter at breast height irrespective of the geographical origin. Biased estimates were found when using site-specific equations outside the geographical range from where they were developed. The new biomass equations improved the accuracy of biomass estimates, particularly for the aboveground components of higher dimension trees and for the root component, being highly suitable for use in regional and national biomass forest calculations. It is, up to the present, the most complete database of harvested stone pine trees worldwide. © 2018
🔗 Vai alla pubblicazione
2018
Rivista
Forest Ecology and Management
Dettagli
Vol. 429 pp. 425 - 436
DOI
Relationships between overstory and understory structure and diversity in semi-natural mixed floodplain forests at Bosco Fontana (Italy)
Chianucci , Francesco , Minari , Emma , Fardusi , Most Jannatul , Merlini , Paolo , Cutini , Andrea , Corona , P. , Mason , Franco
functional diversity leaf area index hemispherical photography deciduous forests diversity measure
Mostra abstract
The "Bosco Fontana" natural reserve includes the last remaining mixed floodplain forest in northern Italy and one of the most endangered ecosystems in Europe. Its effective management is hindered by the complexity of interactions of mixed-tree species and the influence of environmental factors on understory plant diversity. In this study we analyzed the patterns of natural evolution in semi-natural floodplain forest stands at Bosco Fontana with the aim of better understanding its current natural processes and dynamics. Stand structure, taxonomic and functional diversity, species composition, and leaf area index (LAI) of overstory and understory layers were surveyed in permanent plots over two inventory years (1995, 2005). The influence of environmental factors on understory plant diversity was assessed using Ellenberg’s indices for light, soil moisture, soil nutrient and soil reaction. Results indicated that overstory species composition varies according to the soil moisture, with hornbeam prevailing in xeric sites and deciduous oak species in mesic sites. Xeric sites showed high functional dispersion in both drought and shade tolerant traits, while it was significantly lower in both overstory and understory in the moist site. Functional dispersion of drought tolerance in the overstory and understory layers was positively correlated, while species richness was negatively correlated between the two layers. Diversity in the understory was mainly correlated with soil conditions. Understory LAI was positively correlated with overstory LAI in xeric and mesic plots, while no correlations were found in the moist plot. Overall, our results suggest that site conditions (soil conditions and water availability) are the major drivers of understory and overstory dynamics in the study forest. Hence, local site conditions and the understory should be carefully considered in the management of mixed floodplain forests. © SISEF.
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2016
Rivista
IForest
Dettagli
Vol. 9 (6) pp. 919 - 926
DOI
Tree-oriented silviculture for valuable timber production in mixed Turkey oak (Quercus cerris L.) coppices in Italy
Giuliarelli , Diego , Mingarelli , Elena , Corona , P. , Pelleri , F. , Alivernini , Alessandro , Chianucci , Francesco
localized thinning mixed forests single-tree selection sporadic tree species valuable tree
Mostra abstract
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.
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2016
Rivista
Annals of Silvicultural Research
Dettagli
Vol. 40 (2) pp. 148 - 154
DOI
Estimation of canopy attributes in beech forests using true colour digital images from a small fixed-wing UAV
Chianucci , Francesco , Disperati , L. , Guzzi , Donatella , Bianchini , Daniele , Nardino , Vanni , Lastri , Cinzia , Rindinella , Andrea , Corona , P.
fagus sylvatica leaf area index drone hemispherical photography cover photography sensefly ebee
Mostra abstract
Accurate estimates of forest canopy are essential for the characterization of forest ecosystems. Remotely-sensed techniques provide a unique way to obtain estimates over spatially extensive areas, but their application is limited by the spectral and temporal resolution available from these systems, which is often not suited to meet regional or local objectives. The use of unmanned aerial vehicles (UAV) as remote sensing platforms has recently gained increasing attention, but their applications in forestry are still at an experimental stage. In this study we described a methodology to obtain rapid and reliable estimates of forest canopy from a small UAV equipped with a commercial RGB camera. The red, green and blue digital numbers were converted to the green leaf algorithm (GLA) and to the CIE L<sup>*</sup>a<sup>*</sup>b<sup>*</sup> colour space to obtain estimates of canopy cover, foliage clumping and leaf area index (L) from aerial images. Canopy attributes were compared with in situ estimates obtained from two digital canopy photographic techniques (cover and fisheye photography). The method was tested in beech forests. UAV images accurately quantified canopy cover even in very dense stand conditions, despite a tendency to not detecting small within-crown gaps in aerial images, leading to a measurement of a quantity much closer to crown cover estimated from in situ cover photography. Estimates of L from UAV images significantly agreed with that obtained from fisheye images, but the accuracy of UAV estimates is influenced by the appropriate assumption of leaf angle distribution. We concluded that true colour UAV images can be effectively used to obtain rapid, cheap and meaningful estimates of forest canopy attributes at medium-large scales. UAV can combine the advantage of high resolution imagery with quick turnaround series, being therefore suitable for routine forest stand monitoring and real-time applications. © 2015 Elsevier B.V.
🔗 Vai alla pubblicazione
2016
Rivista
International Journal of Applied Earth Observation and Geoinformation
Dettagli
Vol. 47 pp. 60 - 68
DOI
Long-term response to thinning in a beech (Fagussylvatica L.) coppice stand under conversion to high forest in central Italy
Chianucci , Francesco , Salvati , Luca , Giannini , Tessa , Chiavetta , U. , Corona , P. , Cutini , Andrea
leaf area index thinning canopy analyzer continuous cover forestry coppice management plant
Mostra abstract
European beech (Fagus sylvatica L.) forests have a long history of coppicing, but the majority of formerly managed coppices are currently under conversion to high forest. The long time required to achieve conversion requires a long-term perspective to fully understand the implication of the applied conversion practices. In this study, we showed results from a long-term (1992–2014) casestudy comparing two management options (natural evolution and periodic thinning) in a beech coppice in conversion to high forest. Leaf area index, litter production, radiation transmittance and growth efficiency taken as relevant stand descriptors, were estimated using both direct and indirect optical methods. Overall, results indicated that beech coppice showed positive and prompt responses to active conversion practices based on periodic medium-heavy thinning. A growth efficiency index showed that tree growth increased as the cutting intensity increased. Results from the case study supported the effectiveness of active conversion management from an economic (timber harvesting) and ecological (higher growth efficiency) point of view. © 2016, Finnish Society of Forest Science. All rights reserved.
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2016
Rivista
Silva Fennica
Dettagli
Vol. 50 (3)
DOI
A Multidimensional Statistical Framework to Explore Seasonal Profile, Severity and Land-Use Preferences of Wildfires in a Mediterranean Country
Salvati , Luca , Ferrara , Agostino Maria Silvio , Mancino , Giuseppe , Kelly , Claire L. , Chianucci , Francesco , Corona , P.
fire frequency fire severity fire-smart management greece land-use types
Mostra abstract
This study analyses spatio-temporal patterns of wildfires in Greece using a multidimensional statistical framework based on non-parametric correlations, principal component analysis, clustering and stepwise discriminant analysis. Specifically, we assess the frequency, seasonal profile, severity and land-use type of 135 178 wildfires which occurred between 2000-2012 in Greece, one of the countries most affected by fire in Europe. Our results show that both the number of fires and the average size of the area covered by fire show a specific seasonal pattern with a marked increase during the dry season. Principal component analysis identifies three dimensions linked with the main type of land-use affected by the fires: (i) medium and large fires primarily affected landscapes composed of forests, mixed woodlands/shrublands and croplands; (ii) small fires mainly affected fragmented landscapes, i.e. those with mosaics of different crops, market gardens and non-vegetated, abandoned or marginal areas; (iii) fires affecting wetlands and pastures occurred particularly in late summer and showing medium-low severity. Hierarchical clustering highlights similarities in spatio-temporal patterns between fire indicators (ignition date, burnt land cover classes, fire size, fire density). K-means clustering allows us to distinguish between low-severity fires occurring in the wet season from intense and frequent fires occurring in the dry season but with distinct land-use selectivity. The research reported here contributes insight into the complexity of wild fires in the Mediterranean region and supports the design of more effective fire prevention measures including sustainable forest management practices and careful regional planning to minimise risk factors.
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2015
Rivista
International Forestry Review
Dettagli
Vol. 17 (4) pp. 485 - 497
DOI
A simple multivariate analysis to assess diversity in a complex long-term managed forest area in central Italy
Chiavetta , U. , Lasserre , Bruno , Di Martino , P. , Marchetti , Marco
forest biodiversity forest ecosystems sustainable forest management correlation principal components analysis
Mostra abstract
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.
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2015
Rivista
Plant Biosystems
Dettagli
Vol. 149 (6) pp. 1015 - 1024
DOI
Structural attributes of stand overstory and light under the canopy
Angelini , Alice , Corona , P. , Chianucci , Francesco , Portoghesi , Luigi
forest management overstory stand structural attributes understory light
Mostra abstract
This paper reviews the literature relating to the relationship between light availability in the understory and the main qualitative and quantitative attributes of stand overstory usually considered in forest management and planning (species composition, density, tree sizes, etc.) as well as their changes as consequences of harvesting. The paper is divided in two sections: the first one reviews studies which investigated the influence of species composition on understory light conditions; the second part examines research on the relationships among stand parameters determined from mensurational field data and the radiation on understory layer. The objective was to highlight which are the most significant stand traits and management features to build more practical models for predicting light regimes in any forest stand and, in more general terms, to support forest managers in planning and designing silvicultural treatments that retain structure in different way in order to meet different objectives.
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2015
Rivista
Annals of Silvicultural Research
Dettagli
Vol. 39 (1) pp. 23 - 31
DOI
Assessment of potential bioenergy from coppice forests trough the integration of remote sensing and field surveys
Lasserre , Bruno , Chirici , Gherardo , Chiavetta , U. , Garfì , Vittorio , Tognetti , Roberto , Drigo , Rudi , Di Martino , P. , Marchetti , Marco
remote sensing forest inventory sustainable forest management coppice firewood biomass k-nearest neighbours
Mostra abstract
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.
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2011
Rivista
Biomass and Bioenergy
Dettagli
Vol. 35 (1) pp. 716 - 724
DOI
Multi-taxon and forest structure sampling for identification of indicators and monitoring of old-growth forest
Blasi , Carlo , Marchetti , Marco , Chiavetta , U. , Aleffi , Michele , Audisio , P. Aldo , Azzella , Mattia Martin , Brunialti , Giorgio , Capotorti , Giulia , Del Vico , Eva , Lattanzi , Edda , Persiani , Anna Maria , Ravera , Sonia , Tilia , Agnese , Burrascano , Sabina
structural attributes multi-taxon species lists species co-occurrence structure-based indicators taxon-based indicators
Mostra abstract
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.
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2010
Rivista
Plant Biosystems
Dettagli
Vol. 144 (1) pp. 160 - 170
DOI
Linking taxonomical and functional biodiversity of saproxylic fungi and beetles in broad-leaved forests in southern Italy with varying management histories
Persiani , Anna Maria , Audisio , P. Aldo , Lunghini , Dario , Maggi , Oriana , Granito , Vito Mario , Biscaccianti , Alessandro Bruno , Chiavetta , U. , Marchetti , Marco
beetles coarse woody debris fungi old-growth forest saproxylic communities taxonomical and functional biodiversity trophic guilds
Mostra abstract
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.
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2010
Rivista
Plant Biosystems
Dettagli
Vol. 144 (1) pp. 250 - 261
DOI
Post fire natural regeneration monitoring with the integrated use of high resolution remotely sensed images: The case study of the Pineta di Castel Fusano; Monitoraggio della rinnovazione naturale post incendio tramite l'uso integrato di immagini telerilevate ad alta risoluzione: Il caso della pineta di Castel Fusano
Chirici , Gherardo , Balsi , Marco , Bertini , Roberta , Bonora , Nico , Chiavetta , U. , Ottaviano , Marco , Corona , P. , Lamonaca , Andrea , Giuliarelli , Diego , Mastronardi , Alessandro , Nardinocchi , Giovanni , Sambucini , Valter , Tonti , Daniela , Marchetti , Marco
remote sensing forest wildfires k-nearest neighbors natural re generation neural networks spatialisation
Mostra abstract
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.
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2008
Rivista
Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento
Dettagli
Vol. 40 (1) pp. 107 - 122
DOI