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Pubblicazioni Scientifiche

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Pubblicazioni per anno
Multiple drivers of functional diversity in temperate forest understories: Climate, soil, and forest structure effects
Mostra abstract
In macroecology, shifting from coarse- to local-scale explanatory factors is crucial for understanding how global change impacts functional diversity (FD). Plants possess diverse traits allowing them to differentially respond across a spectrum of environmental conditions. We aim to assess how macro- to microclimate, stand-scale measured soil properties, forest structure, and management type, influence forest understorey FD at the macroecological scale. Our study covers Italian forests, using thirteen predictors categorized into climate, soil, forest structure, and management. We analyzed five traits (i.e., specific leaf area, plant size, seed mass, belowground bud bank size, and clonal lateral spread) capturing independent functional dimensions to calculate the standardized effect size of functional diversity (SES-FD) for all traits (multi-trait) and for single traits. Multiple regression models were applied to assess the effect of predictors on SES-FD. We revealed that climate, soil, and forest structure significantly drive SES-FD of specific leaf area, plant size, seed mass, and bud bank. Forest management had a limited effect. However, differences emerged between herbaceous and woody growth forms of the understorey layer, with herbaceous species mainly responding to climate and soil features, while woody species were mainly affected by forest structure. Future warmer and more seasonal climate could reduce the diversity of resource economics, plant size, and persistence strategies of the forest understorey. Soil eutrophication and acidification may impact the diversity of regeneration strategies; canopy closure affects the diversity of above- and belowground traits, with a larger effect on woody species. Multifunctional approaches are vital to disentangle the effect of global changes on functional diversity since independent functional specialization axes are modulated by different drivers. © 2024 The Authors
Plant functional traits are correlated with species persistence in the herb layer of old-growth beech forests
Mostra abstract
This paper explores which traits are correlated with fine-scale (0.25 m<sup>2</sup>) species persistence patterns in the herb layer of old-growth forests. Four old-growth beech forests representing different climatic contexts (presence or absence of summer drought period) were selected along a north–south gradient in Italy. Eight surveys were conducted in each of the sites during the period spanning 1999–2011. We found that fine-scale species persistence was correlated with different sets of plant functional traits, depending on local ecological context. Seed mass was found to be as important for the fine-scale species persistence in the northern sites, while clonal and bud-bank traits were markedly correlated with the southern sites characterised by summer drought. Leaf traits appeared to correlate with species persistence in the drier and wetter sites. However, we found that different attributes, i.e. helomorphic vs scleromorphic leaves, were correlated to species persistence in the northernmost and southernmost sites, respectively. These differences appear to be dependent on local trait adaptation rather than plant phylogenetic history. Our findings suggest that the persistent species in the old-growth forests might adopt an acquisitive resource-use strategy (i.e. helomorphic leaves with high SLA) with higher seed mass in sites without summer drought, while under water-stressed conditions persistent species have a conservative resource-use strategy (i.e. scleromorphic leaves with low SLA) with an increased importance of clonal and resprouting ability. © 2020, The Author(s).
Effects of climate, soil, forest structure and land use on the functional composition of the understorey in Italian forests
Mostra abstract
Question: In functional biogeography studies, generalizable patterns in the relationship between plant traits and the environment have yet to emerge. Local drivers (i.e., soil, land use, vegetation structure) can increase our understanding of the trait–environment relationship. What is the role of climate and local drivers in shaping abundance-weighted trait patterns of forest understories at biogeographic scales?. Location: Italian forests. Methods: We selected 201 sites that are statistically representative for the heterogeneity of Italian forests across three biogeographic regions (alpine, continental, and mediterranean). Understorey vegetation was recorded for each site on an area of 400 m<sup>2</sup>, together with 25 environmental variables related to climate, soil, land use and forest structure. Specific leaf area (SLA), plant height (H) and seed mass (SM) were obtained from databases. Community-weighted mean (CWM) values were calculated. Variance partitioning was used to identify the relative role of groups of environmental variables on the CWM of traits. Generalized Additive Models were used to assess the relationship between traits and single variables. Results: Climate alone and climate–soil interactions explained the largest proportion of the variation of all the traits (13.7% to 22.8%). Temperature-related factors as well as soil N and P availability were the climatic and edaphic explanatory variables most correlated to trait variation. Forest structure and land use accounted for a smaller percentage of the variation in traits. Land-use factors alone were important in explaining only SLA variation. Conclusions: While climate plays a major role in trait–environment relationships in forest understories, our results highlighted the need to integrate at least soil properties as local drivers of trait variation in broad scale functional biogeography studies of these systems. © 2019 International Association for Vegetation Science
Climate is the main driver of clonal and bud bank traits in Italian forest understories
Mostra abstract
The study of plant trait-environment links is rarely focused on traits that inform on space occupancy and resprouting (both affecting plant persistence), especially in forest understories. Traits that can effectively capture such key functions are associated with clonality and bud banks. We hypothesized that: 1) climate is the main driver of clonal and bud bank traits, 2) traits related to space occupancy (e.g., greater lateral spread) are more important in more mesic, richer soils forests, and 3) traits related to resprouting ability (e.g., larger bud bank) are more important in more intensively and recently managed forests. We addressed these hypotheses by analysing a unique dataset that is statistically representative of Italian forests heterogeneity and includes three biogeographic regions (Alpine, Continental, Mediterranean). We recorded data for sixteen climatic, soil and management variables. We calculated community weighted mean (CWM) values of seven clonal and bud bank traits for the forest understory vegetation. We used i) redundancy analysis to assess trait-environment relations, and ii) variance partitioning analyses to identifying the relative role of different groups of abiotic variables on CWM variation of all traits combined together, as well as clonal and bud bank traits taken separately. Climate alone had a pervasive effect in determining patterns of clonal and bud bank traits in Italian forest understories, mainly related to the effects of temperature extremes and seasonality. Unexpectedly, soil and management factors alone showed marginal effects on clonal and bud bank traits. However, soil features influenced trait patterns when joined with climate. Our results confirmed that, at the biogeographic scale, climate played a lion-share role in determining persistence-related traits of forest-floor plants. At the local-scale, other interplaying factors (e.g., management, soil variables) may come into play in shaping patterns of the studied plant traits. This study stressed the importance of examining functional trait patterns along complex environmental gradients. © 2019 Elsevier GmbH
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
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
Tree-oriented silviculture for valuable timber production in mixed Turkey oak (Quercus cerris L.) coppices in Italy
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.
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
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.