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Epiphytic lichen diversity and sustainable forest management criteria and indicators: A multivariate and modelling approach in coppice forests of Italy
Brunialti , Giorgio , Frati , Luisa , Calderisi , Marco , Giorgolo , Francesca , Bagella , Simonetta , Bertini , Giada , Chianucci , Francesco , Fratini , Roberto , Gottardini , Elena , Cutini , Andrea
biodiversity european forest types lichen diversity value (ldv) predictive models
Mostra abstract
Epiphytic lichens represent one of the most suitable indicators of forest continuity and management, especially in the context of ancient and old-growth forests. Nevertheless, they have not yet been included among Sustainable Forest Management (SFM) indicators to which Pan-European forest policy and governance refer. In addition, currently adopted SFM indicators are mainly designed for high forests rather than coppice forests, despite the fact that today this management system covers more than 10% of the total European forests. In this study we investigated these two issues by examining epiphytic lichen diversity in three coppice forest stands, located in the two Italian regions of Tuscany and Sardinia. In particular, we addressed: i) the role of lichen diversity as SFM indicator and ii) its relationship with consolidated and new SFM indicators dealing with structural, health, biodiversity, protective and socioeconomic functions. Multivariate Factor Analysis and Generalised Linear Models were adopted for data analysis. We found that lichen diversity and the frequency of single sensitive species were mainly related to the biodiversity of plants and fungi (Criterion 4), the health and vitality of the forests (Criterion 2) and their protective functions (Criterion 5). Furthermore, our results show that the lichen species highlighted by the models may represent suitable indicators in long-term studies, especially in relation to complex and interconnected aspects of sustainable forest management. Although our findings represent a first contribute to this issue, more in-depth researches will be needed to clarify further aspects of the complex interactions among SFM indicators in the context of coppice forests. © 2020 Elsevier Ltd
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2020
Rivista
Ecological Indicators
Dettagli
Vol. 115
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