TY - JOUR
T1 - Handbook of field sampling for multi-taxon biodiversity studies in European forests
AU - Burrascano, Sabina
AU - Trentanovi, Giovanni
AU - Paillet, Yoan
AU - Heilmann-Clausen, Jacob
AU - Giordani, Paolo
AU - Bagella, Simonetta
AU - Bravo-Oviedo, Andrés
AU - Campagnaro, Thomas
AU - Campanaro, Alessandro
AU - Francesco, Chianucci
AU - Smedt, Pallieter De
AU - Itziar, García-Mijangos
AU - Matošević, Dinka
AU - Sitzia, Tommaso
AU - Aszalós, Réka
AU - Brazaitis, Gediminas
AU - Andrea, Cutini
AU - Ettore, D'Andrea
AU - Doerfler, Inken
AU - Hofmeister, Jeňýk
AU - Hošek, Jan
AU - Janssen, Philippe
AU - Rojas, Sebastian Kepfer
AU - Korboulewsky, Nathalie
AU - Kozák, Daniel
AU - Lachat, Thibault
AU - Lõhmus, Asko
AU - Lopez, Rosana
AU - Mårell, Anders
AU - Matula, Radim
AU - Mikoláš, Martin
AU - Munzi, Silvana
AU - Nordén, Björn
AU - Pärtel, Meelis
AU - Penner, Johannes
AU - Runnel, Kadri
AU - Schall, Peter
AU - Svoboda, Miroslav
AU - Tinya, Flóra
AU - Ujházyová, Mariana
AU - Vandekerkhove, Kris
AU - Verheyen, Kris
AU - Xystrakis, Fotios
AU - Ódor, Péter
PY - 2021/12/1
Y1 - 2021/12/1
N2 - 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.
AB - 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.
U2 - 10.1016/j.ecolind.2021.108266
DO - 10.1016/j.ecolind.2021.108266
M3 - A1: Web of Science-article
SN - 1470-160X
VL - 132
JO - Ecological Indicators
JF - Ecological Indicators
M1 - 108266
ER -