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Pubblicazioni Scientifiche
Filtri di ricerca 19 risultati
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Estimated biomass loss caused by the vaia windthrow in northern italy: Evaluation of active and passive remote sensing options
Vaglio Laurin
,
Gaia
,
Puletti
,
Nicola
,
Tattoni
,
Clara
,
Ferrara
,
Carlotta
,
Pirotti
,
Francesco
Mostra abstract
Windstorms are a major disturbance factor for European forests. The 2018 Vaia storm, felled large volumes of timber in Italy causing serious ecological and financial losses. Remote sensing is fundamental for primary assessment of damages and post‐emergency phase. An explicit estimation of the timber loss caused by Vaia using satellite remote sensing was not yet undertaken. In this investigation, three different estimates of timber loss were compared in two study sites in the Alpine area: pre‐existing local growing stock volume maps based on lidar data, a recent national‐level forest volume map, and an novel estimation of AGB values based on active and passive remote sensing. The compared datasets resemble the type of information that a forest manager might potentially find or produce. The results show a significant disagreement in the different biomass estimates, related to the methods used to produce them, the study areas characteristics, and the size of the damaged areas. These sources of uncertainty highlight the difficulty of estimating timber loss, unless a unified national or regional European strategy to improve preparedness to forest hazards is defined. Considering the frequent impacts on forest resources that occurred in the last years in the European Union, remote sensing‐based surveys targeting forests is urgent, particularly for the many European countries that still lack reliable forest stocks data. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Characterizing subcanopy structure of Mediterranean forests by terrestrial laser scanning data
forest biodiversity
lidar
terrestrial laser scanner
forest structure
spatial prediction
voxelization
Mostra abstract
Vegetation structure is one of the key factors in forest ecosystems. Especially understory structure has major implications for wildlife habitat selection, reproduction, and survival. Structural indices traditionally used to characterize understory vegetation are based on field vegetation surveys describing general features such as leaf area index (LAI), canopy cover or vegetation height, hiding much of the three-dimensional vegetation structure complexity. The application of terrestrial laser scanning (TLS) in forest ecological and management applications is becoming more effective. In this study, we use TLS data to quantify spatial attributes of forest subcanopy in four different forest strata ranging from 0.5 m to 10 m from the ground. We collected data in 12 plots of mature European beech (Fagus sylvatica L.) forests and 12 plots of mature black pine (Pinus nigra subsp. laricio Maire) forests, located in the Sila National Park, Italy. We propose a TLS-based approach to estimate a fine-scale vegetation density using the Plant Density Index (PDI) and to test the PDI at different height classes. We found a significant relationship between the PDI and the number of trees belonging to the dominant layer, using the Spearman correlation coefficient (r = 0.83, p<inf>val</inf> = 0.001). Basing on PDI values, a cluster analysis of the four subcanopy strata was carried out for deriving clusters of structurally homogeneous forest plots. Results identified three clusters in terms of the vegetation features in the horizontal height classes: the first cluster primarily includes Beech forests characterized by plots with the highest tree densities; the second one includes both Beech and Pine forests characterized by dense ground vegetation and shrubs and an intermediate tree density; the third group is represented by Pine forests with massive presence of vegetation lower strata and moderate tree density. Then, PCA allowed identifying the relationship between the considered subcanopy layers and forest plots. © 2021 Elsevier B.V.
Traditional and TLS-based forest inventories of beech and pine forests located in Sila National Park: A dataset
Mostra abstract
Vegetation structure is a key determinant of species distribution and diversity. Compared to traditional methods, the use of Terrestrial Laser Scanning (TLS) has allowed massive amounts of point cloud data collected for quantifying three-dimensional habitat properties at increasing spatial and temporal scales. We used TLS to characterize the forest plots across a broad range of forest structural diversity, located in the Sila National Park, South Italy. The dataset reports data collected in 24 15-m-radius circular plots, 12 of which were dominated by beech (Fagus sylvatica L.) and 12, by black pine (Pinus nigra subsp. laricio). In detail, this work provides dataset of i) plot-level attributes calculated from raw data, such as the number of trees, ii) tree-level data, comprising a total of 1709 trees, with information related to field-based forest inventory such as the diameter at breast height (DBH), and iii) plot-level information related to the time for conducting both traditional field- and TLS-based forest inventories. Compared to traditional methods, the use of TLS allows a very high-resolution quantification of the 3D forest structural properties, also reducing the time for conducting forest inventories. © 2020
Influence of voxel size and point cloud density on crown cover estimation in poplar plantations using terrestrial laser scanning
Mostra abstract
Accurate estimates of crown cover (CC) are central for a wide range of forestry studies. As direct measurements do not exist to retrieve this variable in the field, CC is conventionally determined from optical measurements as the complement of gap fraction close to the zenith. As an alternative to passive optical measurements, active sensors like terrestrial Light Detection And Ranging (LiDAR) allows for characterizing the 3D canopy structure with unprecedented detail. We evaluated the reliability of terrestrial LiDAR (TLS) to estimate CC using a voxel-based approach. Specifically, we tested how different voxel sizes (ranging from 5-20 cm) and voxel densities (1-9 points/dm<sup>3</sup>) influenced the retrieval of CC. Results were compared against benchmark values obtained from digital cover photography (DCP). The trial was performed in hybrid poplar plantations in Northern Italy. Results indicate that TLS can be used for obtaining accurate estimates of CC, but the choice of voxel size and point density is critical for achieving such accuracy. In hybrid poplars, the best performance was obtained using voxel size of 10 cm and point density of 8 points/dm<sup>3</sup>. The combined ability of measuring and mapping CC also holds great potential to use TLS for calibrating and upscaling results using coarser-scale remotely sensed products. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.
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.
Estimation of forest leaf area index using satellite multispectral and synthetic aperture radar data in Iran
Vafaei
,
Sasan
,
Fathizadeh
,
Omid
,
Puletti
,
Nicola
,
Fadaei
,
Hadi
,
Rasooli
,
Sabri Baqer
,
Vaglio Laurin
,
Gaia
Mostra abstract
Different satellite datasets, including multispectral Sentinel 2 and synthetic aperture radar Sentinel 1 and ALOS2, were tested to estimate the Leaf Area Index (LAI) in the Zagros forests, Ilam province, in Iran. Field data were collected in 61 sample plots by hemispherical photographs, to train and validate the LAI estimation models. Different satellite data combinations were used as input in regression models built with the following algorithms: Multiple Linear Regression, Random Forests, and Partial Least Square Regression. The results indicate that Leaf Area Index can be best estimated using integrated ALOS2 and Sentinel 2 data; these inputs generated the model with higher accuracy (R<sup>2</sup> = 0.84). The combination of a single band and a vegetation index from Sentinel 2 also led to successful results (R<sup>2</sup> = 0.81). Lower accuracy was obtained when using only ALOS 2 (R<sup>2</sup> = 0.72), but this dataset is helpful where cloud coverage affects optical data. Sentinel 1 data was not useful for LAI predic-tion. The optimal model was based on the traditional Multiple Linear Regression algorithm, using a preliminary input selection step to exclude multi-collinearity effects. To avoid this step, the use of Partial Least Square Regression may be an alternative, as this algorithm was able to produce estimates similar to those obtained with the best model. © SISEF.
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
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.
What Is Known About the Management of European Beech Forests Facing Climate Change? A Review
Antonucci
,
Serena
,
Santopuoli
,
Giovanni
,
Marchetti
,
Marco
,
Tognetti
,
Roberto
,
Chiavetta
,
U.
,
Garfì
,
Vittorio
Mostra abstract
Purpose of Review: This paper aims to retrace the most significant management strategies adopted across European beech forests over the last 25 years, highlighting those that are most efficient and promising. We investigate five main topics including forest management, forest models, species mixture, genetic, and regeneration. Recent Findings: European beech is one of the most widespread and important tree species for the European forest sector. In the light of the ongoing climate crisis, understanding the growth dynamics and the response of beech forests to climate change is crucial to identify advantageous management strategies. Ecology, growth, management, distribution, interaction with other species, genetic, and regeneration aspects of European beech were investigated in different geographical areas of Europe. Despite recent researches focusing on climate change issues, how adaptation and mitigation measures can be integrated into silvicultural guidelines to improve the resilience of European beech forests remains unclear. Summary: To answer this question, we collected and reviewed articles about the management of European beech facing climate change, which were published in peer-reviewed journals over the last 25 years. Articles were grouped into five geographic European areas, according to the classification used by the State of Europe’s forests. Obtained articles were further clustered into five main topics: management, mixed forest, modelling, genetic, and regeneration. The review highlighted the importance of using long-term monitoring plots to understand the effect of climate change on the stability of European beech forests, suggesting climate-smart measures that would help these forests adapt to climate change. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
foreMast: an R package for predicting beech (Fagus sylvatica L.) masting events in European countries
forest management
climatic cues
fagus sylvatica l. (european beech)
mast event
r package
seed production
Mostra abstract
Key message: Forecasting annual seed production will improve the management of forests across Europe. The foreMast R package we developed predicts current year masting probability in beech (Fagus sylvatica L.) using climate data easily accessible by any stakeholder. Context: Modelling and predicting forest masting is one of the most challenging tasks in forest management, as it is a strategy shared by several species, very important for tree dispersion and forest regeneration, mainly related to climate and ecological processes. Aims: As many studies focus on European beech (Fagus sylvatica L.) masting without simple practical implementations, we developed a tool capable of predicting beech masting years. Methods: The tool is an R package (foreMast) made by three functions, which relies mainly on climate data. The algorithm performance is compared with the records of the MASTREE database, which gather several beech seed production series for various sites across European countries. Results: Overall, the results show a tight correlation with the compared sites (ρ = 0.50 to 0.61, p-value < 0.0001, respectively), especially when temperatures weigh three times more than precipitation. Nevertheless, in some sites, seed production seems to be more related to precipitation dynamics than to temperatures. Conclusion: foreMast can be used both for studying changes in mast events in relation to climate changes and in operative forest management and planning. It is flexible and thus amenable to future implementation of additional predicting variables or target species. © 2021, INRAE and Springer-Verlag France SAS, part of Springer Nature.
A multi-criteria analysis of forest restoration strategies to improve the ecosystem services supply: an application in Central Italy
Paletto
,
Alessandro
,
Pieratti
,
Elisa
,
De Meo
,
Isabella
,
Agnelli
,
Alessandro Elio
,
Cantiani
,
Paolo
,
Chiavetta
,
U.
,
Mazza
,
Gianluigi
,
Lagomarsino
,
Alessandra
carbon sequestration
carbon stock
biophysical assessment
economic evaluation
multiple-criteria decision analysis (mcda)
recreational activities
Mostra abstract
• Key message: A multi-criteria analysis can be an interesting tool to assess the effects of silvicultural treatments on ecosystem services supply. In the degraded forests, thinning has a positive effect on the provision of ecosystem services such as timber and bioenergy production, climate change mitigation, and recreational attractiveness. • Context: The Millennium Ecosystem Assessment highlights the importance of the ecosystem services for human well-being and for maintaining conditions for life on Earth. Silvicultural treatments can improve the provision of ecosystem services to increase local communities’ well-being. • Aims: The aim of this study is to understand the effects of two-forest restoration practices (selective thinning and thinning from below) on three ecosystem services (wood production, climate change mitigation, and recreational opportunities) in an Italian case study. • Methods: A multi-criteria decision analysis (MCDA) was performed to compare the effects of three forest restoration scenarios (baseline, selective thinning, thinning from below) on ecosystem services. Wood production was estimated considering the local market prices and the wood volumes harvested, while climate change mitigation was quantified through the C-stock and C-sequestration changes in carbon pools due to the silvicultural treatments. The recreational activities were assessed through a questionnaire survey. A sample of 200 visitors was interviewed face-to-face to estimate the impact of thinning on recreational activities. • Results: The results of the MCDA show that the selective thinning scenario is the optimal forest restoration practice to increase the recreational attractiveness and the wood production in the study area. • Conclusion: The results concerning the effects of the silvicultural treatments on ecosystem services supply are an important tool to support decision makers. © 2021, INRAE and Springer-Verlag France SAS, part of Springer Nature.
Comparison of TLS against traditional surveying method for stem taper modelling. A case study in European beech (Fagus sylvatica L.) forests of mount Amiata
Torresan
,
C.
,
Pelleri
,
F.
,
Manetti
,
Maria Chiara
,
Becagli
,
Claudia
,
Castaldi
,
Cristiano
,
Notarangelo
,
Monica
,
Chiavetta
,
U.
Mostra abstract
Traditionally, taper equations are developed from measurements collected through a destructive sampling of trees. Terrestrial laser scanning (TLS) enables high levels of accuracy of individual tree parameters measurement avoiding tree felling. With this study, we wanted to assess the performance of two approaches to calibrate a taper function: using stem diameters extracted from TLS point clouds and measured at different tree heights with the traditional and usual forest instruments. We compared the performance of four taper equations built with data collected by TLS and traditional survey in a European beech (Fagus sylvatica L.) forests of mount Amiata (Tuscany Region, Italy). We computed the volume of stem sections 1.00 m long by integrating the most performing TLS-based taper equation and by the Huber, Smalian and cone formulas applied on the diameter and height values measured with the traditional field surveys. We conducted the analysis of error distribution in volume estimates computed integrating the most performing TLS-based taper function along the stem. We tested if the differences in the volume estimate of the two methods were significant. Schumacher and Hall (1933) equation was the most performing taper function both in case of using TLS and traditional surveyed data, being the TLS-based function more performant (rRMSE = 6.90% vs 9.17%). Its performance did not increase when diameter values were extracted from TLS point clouds with a higher frequency (i.e. 25.0 cm vs 1.00 m). By integrating the TLS-based Schumacher and Hall (1933) function, the sections with the highest error resulted from 5.00 to 7.00 m of stem height (i.e. RMSE from 14.72 to 19.14 dm<sup>3</sup> and rRMSE from 13.00 to 17.76%). This study case represents the first attempts to develop a taper equation for European beech of mount Amiata using values of stem diameter and height extracted from the TLS point cloud. The results demonstrated that TLS produces the same stem volume estimates as traditional method avoiding falling trees. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.
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
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
Testing an expanded set of sustainable forest management indicators in Mediterranean coppice area
Cutini
,
Andrea
,
Ferretti
,
Marco
,
Bertini
,
Giada
,
Brunialti
,
Giorgio
,
Bagella
,
Simonetta
,
Chianucci
,
Francesco
,
Fabbio
,
Gianfranco
,
Fratini
,
Roberto
,
Riccioli
,
Francesco
,
Caddeo
,
C.
,
Calderisi
,
Marco
,
Ciucchi
,
B.
,
Corradini
,
Stefano
,
Cristofolini
,
Fabiana
,
Cristofori
,
Antonella
,
Di Salvatore
,
Umberto
,
Ferrara
,
Carlotta
,
Frati
,
Luisa
,
Landi
,
Sara
,
Marchino
,
Luca
,
Patteri
,
Giacomo
,
Piovosi
,
Maurizio
,
Roggero
,
Pier Paolo
,
Seddaiu
,
Giovanna
,
Gottardini
,
Elena
silviculture
coppice conversion
coppice natural evolution
coppice system
environmental monitoring
sfm criteria
Mostra abstract
Although coppice forests represent a significant part of the European forest area, especially across southern Countries, they received little attention within the Sustainable Forest Management (SFM) processes and scenarios, whose guidelines have been mainly designed to high forests and national scale. In order to obtain “tailored” information on the degree of sustainability of coppices on the scale of the stand, we evaluated (i) whether the main coppice management options result in different responses of the SFM indicators, and (ii) the degree to which the considered SFM indicators were appropriate in their application at stand level. The study considered three different management options (Traditional Coppice TC, coppice under Natural Evolution NE, and coppice under Conversion to high forest by means of periodical thinning CO). In each of the 43 plots considered in the study, which covered three different European Forest Types, we applied a set of eighteen “consolidated” SFM indicators, covering all the six SFM Criteria (FOREST EUROPE, 2020) and, additionally, tested other sixteen novel indicators shaped for agamic forests and/or applicable at stand level. Results confirmed that several consolidated indicators related to resources status (Growing stock and Carbon stock), health (Defoliation and Forest damage), and socio-economic functions (Net revenue, Energy and Accessibility) were highly appropriate for evaluating the sustainability of coppice at stand level. In addition, some novel indicators related to resources status (Total above ground tree biomass), health (Stand growth) and protective functions (Overstorey cover and Understorey cover) proved to be highly appropriate and able to support the information obtained by the consolidated ones. As a consequence, a subset of consolidated SFM indicators, complemented with the most appropriate novel ones, may represent a valid option to support the evaluation of coppice sustainability at stand level. An integrated analysis of the SFM indicators showed that NE and CO display significant higher environmental performances as compared with TC. In addition, CO has positive effects also on socio-economic issues, while TC -which is an important cultural heritage and a silvicultural option that may help to keep local communities engaged in forestry – combines high wood harvesting rates with dense understory cover. Overall, each of the three management options showed specific sustainability values; as a consequence, their coexistence at a local scale and in accordance with the specific environmental conditions and the social-economic context, is greatly recommended since it may fulfill a wider array of sustainability issues. © 2021
Continuous observations of forest canopy structure using low-cost digital camera traps
Mostra abstract
Assessing forest canopy dynamics is crucial for understanding the response of vegetation to environmental variability and change. While digital repeat photography is gaining increased attention for obtaining field phenology observations, colour indices derived from this method are often affected by leaf colour and actual canopy structure, complicating the physical interpretation of results. In addition, repeated photography requires power, storage capacity and remote data transfer, which are often limited in forest conditions. As an alternative, we tested a simple, cheap and fast solution to derive daily canopy structure observation from digital camera traps (CTs). Formerly deployed for wildlife monitoring, CTs are low-cost digital cameras designed for outdoor conditions and have low battery consumption, enable repeat acquisition, and often feature remote data transfer protocols. The trial was performed in a deciduous oak stand, where continuous images were acquired over a 1-year period using the time-lapse feature of the CT. Daily time series of canopy structure attributes were derived from the collected images using simple and automated procedures. Results were validated against reference manual cover photography measurements. The daily time series of foliage cover and leaf area index were then used to derive phenological transition dates, which were compared against phenological observations obtained from satellite Sentinel-2 data. Results indicated that field and satellite data provided comparable accuracy in determining the start of season (SOS). Larger discrepancies were found in determining the end of season (EOS), which can be attributed to the low number of good quality autumn images available from the satellite data. We concluded that CT is a robust method, which is ideally suited for routine, continuous field monitoring of canopy attributes and phenology. While this method can be used for evaluating remote sensing observations, the combination of CTs with satellite data holds great potential for greater spatiotemporal coverage, from field to landscape scales. © 2021
Evaluating sampling schemes for quantifying seed production in beech (Fagus sylvatica) forests using ground quadrats
Chianucci
,
Francesco
,
Tattoni
,
Clara
,
Ferrara
,
Carlotta
,
Ciolli
,
Marco
,
Brogi
,
Rudy
,
Zanni
,
Michele
,
Apollonio
,
Marco
,
Cutini
,
Andrea
Mostra abstract
Accurate estimates of seed production are central for understanding mast seeding mechanisms at tree and forest scales, and for designing sustainable management strategies. As trees are long-lived organisms, a long-term perspective is required to understand how reproduction acts during the life cycle of a tree. However, long-term series of seed production are challenging to obtain, as the available seed count procedures strictly rely on field methods, which are cost- and time-consuming, inherently limiting their widespread use at extensive spatial and temporal scales. In this study, we proposed a simple, rapid and flexible field method based on counting the seed in mobile ground quadrats (GQ), which was tested in beech forests. Quadrat measurements were first validated against reference measurements obtained from litter traps (LT) in three permanent plots. Results indicated that GQ provides robust and reliable estimates of seeds, which are not affected by seed predation occurring at the forest floor. Additional quadrat measurements were performed to evaluate the influence of sampling schemes (random, regular, systematic) on the estimation of mean seed production at the plot scale. One hundred quadrats were collected in 0.25 ha beech plots and considered as a reference for evaluating the different sampling schemes and sampling sizes. Measurements were performed in October (three plots), which represented the peak of seed fall, and November (two plots). Results indicate that about 25 randomly located measurements allowed to characterize plot-level mean seed production with an acceptable error below 20%, regardless of the different mean seed production observed between the studied plots and the sampling periods. If the 25 sampling points are arranged in a grid, the obtained mean estimates are within the confidence interval of the reference plot-level values. © 2021 Elsevier B.V.
A comparison of ground-based count methods for quantifying seed production in temperate broadleaved tree species
Tattoni
,
Clara
,
Chianucci
,
Francesco
,
Ciolli
,
Marco
,
Ferrara
,
Carlotta
,
Marchino
,
Luca
,
Zanni
,
Michele
,
Zatelli
,
Paolo
,
Cutini
,
Andrea
Mostra abstract
• Key message: Litter trap is considered the most effective method to quantify seed production, but it is expensive and time-consuming. Counting fallen seeds using a quadrat placed on the ground yields comparable estimates to the litter traps. Ground quadrat estimates derived from either visual counting in the field or image counting from quadrat photographs are comparable, with the latter being also robust in terms of user sensitivity. • Context: Accurate estimates of forest seed production are central for a wide range of ecological studies. As reference methods such as litter traps (LT) are cost- and time-consuming, there is a need of fast, reliable, and low-cost tools to quantify this variable in the field. • Aims: To test two indirect methods, which consist of counting the seeds fallen in quadrats. • Methods: The trial was performed in three broadleaved (beech, chestnut, and Turkey oak) tree species. Seeds are either manually counted in quadrats placed at the ground (GQ) or from images acquired in the same quadrats (IQ) and then compared against LT measurements. • Results: GQ and IQ provide fast and reliable estimates of seeds in both oak and chestnut. In particular, IQ is robust in terms of user sensitivity and potentially enables automation in the process of seed monitoring. A null-mast year in beech hindered validation of quadrats in beech. • Conclusion: Quadrat counting is a powerful tool to estimate forest seed production. We recommend using quadrats and LT to cross-calibrate the two methods in case of estimating seed biomass. Quadrats could then be used more routinely on account of their faster and simpler procedure to obtain measurements at more spatially extensive scales. © 2021, The Author(s).
Characterizing the climatic niche of mast seeding in beech: Evidences of trade-offs between vegetation growth and seed production
Bajocco
,
Sofia
,
Ferrara
,
Carlotta
,
Bascietto
,
Marco
,
Alivernini
,
Alessandro
,
Chirichella
,
Roberta
,
Cutini
,
Andrea
,
Chianucci
,
Francesco
Mostra abstract
Masting is a complex mechanism which is mainly driven by a combination of internal plant resources and climatic conditions. While the driving role of climate in masting is being intensively studied, the interplay among climate, seed production, vegetation growth and phenology still needs further investigation. The objectives of this study were to identify the climatic determinants of different levels of seed production and of NDVI-based vegetation growth and phenology in European beech, and to evaluate if exists a trade-off between these two plant processes. To answer these questions, we used a 25-year-long dataset of beech seed production. We exploited the concept of ecological niche assuming that a mast year can be modeled like a species with variable preferences for different resources, which are the underlying annual climatic conditions; we performed an Ecological Niche Factor Analysis (ENFA), a presence-only modeling tool conventionally used in zoology and botany, and used seasonal (spring, summer, autumn) Standardized Precipitation-Evaporation Index (SPEI) observations, considering the current year (y−0), and up to one (y−1) and two (y−2) years before the masting event. For analyzing the role of vegetation growth and phenology, we used seasonal Normalized Difference Vegetation Index (NDVI) values and associated NDVI-based phenological metrics derived from Landsat imagery. Results indicated the driving role of climate for masting, especially in VHSP years. A moist summer and dry spring at y−2 and a dry summer at y−1 represented the main driving climatic conditions for masting; while a moist spring during the observation year represented the key condition for triggering higher intensities of seed production. Summer NDVI at y−0 and y−1 represented the variables discriminating best between masting and non-masting years and resulted as driven by opposite summer climatic conditions than seed production, thus indicating a trade-off between seed production and vegetation phenology. We concluded that reproduction and vegetation growth act as two different climate-dependent plant responses in beech, in a way that certain conditions through the years promote mast seeding and the opposite conditions favor vegetation growth. The understanding of climate-growth-masting relationships represents indispensable knowledge for providing a holistic view of masting mechanisms and developing adaptive forest management strategies in this species. © 2020
IN SITU (TREE TALKER) AND REMOTELY-SENSED MULTISPECTRAL IMAGERY (SENTINEL-2) INTEGRATION FOR CONTINUOUS FOREST MONITORING: THE FIRST STEP TOWARD WALL-TO-WALL MAPPING OF TREE FUNCTIONAL TRAITS
Francini
,
Saverio
,
Zorzi
,
Ilaria
,
Giannetti
,
Francesca
,
Chianucci
,
Francesco
,
Travaglini
,
Davide
,
Chirici
,
Gherardo
,
Cocozza
,
C.
Mostra abstract
Monitoring tree functional traits is essential for understanding forest ecosystems' capability to respond to climate change. Advancements in continuous proximal sensors and IoT technologies hold great potential for monitoring forest and tree ecosystem processes at the finest spatial and temporal scale. An example is the TreeTalker (TT) technology, which features sensors for measurements of the radial growth, sap flow, multispectral light transmission, air temperature, and humidity at tree level with an hourly frequency rate. Such information can be linked with remote sensing data acquired by the Sentinel-2 (S2) mission, allowing for scaling results over more spatially extensive areas. Firstly, we compared six TT with four S2 spectral bands with similar wavelengths. No correlation was found for blue, green and red channels (R<sup>2</sup> ranged between 0.04 and 0.09) while higher values were found for the near-infrared channel (R<sup>2</sup> = 0.9). To obtain an accurate prediction of TTs bands, also for those TTs bands which wavelengths are not similar to that of S2 bands, we implemented a Sentinel-2 to TreeTalker model (S2TT) by using an 8-layers fully connected deep neural network. The model was tested by using 23 Sentinel-2 imagery and data acquired by 40 TreeTalkers located in two different sites in Tuscany (a beech and a silver fir forest stand) in the period between 2020-07-15 and 2020-11-15. The R<sup>2</sup> ranged between 0.61 (B7, blue) and 0.96 (B6, near-infrared band). The S2TT model represents the first link between remote sensing and TreeTalkers, which might allow predicting tree functional traits using Sentinel-2 imagery. © 2021, Italian Society of Remote Sensing. All rights reserved.
Dataset of tree inventory and canopy structure in poplar plantations in Northern Italy
Chianucci
,
Francesco
,
Marchino
,
Luca
,
Bidini
,
Claudio
,
Giorcelli
,
Achille
,
Coaloa
,
Domenico
,
Chiarabaglio
,
Pier Mario
,
Giannetti
,
Francesca
,
Chirici
,
Gherardo
,
Tattoni
,
Clara
Mostra abstract
The dataset reports data collected in 38 square (50 x 50m) 0.25 ha plots representative of poplar plantations in Lombardy Region (Northern Italy), which were used to calibrate optical information derived from unmanned aerial vehicle (UAV) and satellite (Sentinel-2) sensors. In each plot, the diameter at breast height was measured using a caliper; height, stem and crown volume of each tree were then derived from diameter using allometric equations developed in an independent study. Additional canopy attributes (foliage and crown cover, crown porosity, leaf area index) were derived in each plot from 12-20 optical images collected using digital cover photography (DCP). The collected data allows characterizing the assessment of structure of these plantations, along with their variation over the rotation time. Canopy and crown data also enable the evaluation of optimal rotation and tree spacing, as well as the relationship between stand and canopy structure. The raw datasets consist of 2,591 records (trees) associated with inventory measurements and 616 records (images) associated with optical canopy measurements. An R code was also provided to calculate plot-level attributes from raw data. Dataset and associated metadata are freely available at http://dx.doi.org/10.17632/ycr7w5pvkt.1. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.