Handbook of field sampling for multi-taxon biodiversity studies in European forests

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 accoun...

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Autores: Burrascano, S., Trentanovi, Giovanni, Paillet, Yoan, Heilmann-Clausen, Jacob, Giordani, Paolo, Bagella, Simonetta, Bravo-Oviedo, Andrés
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/256275
Acceso en línea:http://hdl.handle.net/10261/256275
Access Level:acceso abierto
Palabra clave:Biodiversity
Field methods
Multi-taxon
Indicators
Sampling protocol
Forest stand structure
http://metadata.un.org/sdg/15
Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
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spelling Handbook of field sampling for multi-taxon biodiversity studies in European forestsBurrascano, S.Trentanovi, GiovanniPaillet, YoanHeilmann-Clausen, JacobGiordani, PaoloBagella, SimonettaBravo-Oviedo, AndrésBiodiversityField methodsMulti-taxonIndicatorsSampling protocolForest stand structurehttp://metadata.un.org/sdg/15Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity lossForests 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.This review was funded by the EU Framework Programme Horizon 2020 through the COST Association: COST Action CA18207: BOTTOMSUP- Biodiversity Of Temperate forest Taxa Orienting Management Sustainability by Unifying Perspectives.ElsevierEuropean CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2021202120212021info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/256275reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.1016/j.ecolind.2021.108266Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2562752026-05-22T06:33:51Z
dc.title.none.fl_str_mv Handbook of field sampling for multi-taxon biodiversity studies in European forests
title Handbook of field sampling for multi-taxon biodiversity studies in European forests
spellingShingle Handbook of field sampling for multi-taxon biodiversity studies in European forests
Burrascano, S.
Biodiversity
Field methods
Multi-taxon
Indicators
Sampling protocol
Forest stand structure
http://metadata.un.org/sdg/15
Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
title_short Handbook of field sampling for multi-taxon biodiversity studies in European forests
title_full Handbook of field sampling for multi-taxon biodiversity studies in European forests
title_fullStr Handbook of field sampling for multi-taxon biodiversity studies in European forests
title_full_unstemmed Handbook of field sampling for multi-taxon biodiversity studies in European forests
title_sort Handbook of field sampling for multi-taxon biodiversity studies in European forests
dc.creator.none.fl_str_mv Burrascano, S.
Trentanovi, Giovanni
Paillet, Yoan
Heilmann-Clausen, Jacob
Giordani, Paolo
Bagella, Simonetta
Bravo-Oviedo, Andrés
author Burrascano, S.
author_facet Burrascano, S.
Trentanovi, Giovanni
Paillet, Yoan
Heilmann-Clausen, Jacob
Giordani, Paolo
Bagella, Simonetta
Bravo-Oviedo, Andrés
author_role author
author2 Trentanovi, Giovanni
Paillet, Yoan
Heilmann-Clausen, Jacob
Giordani, Paolo
Bagella, Simonetta
Bravo-Oviedo, Andrés
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Biodiversity
Field methods
Multi-taxon
Indicators
Sampling protocol
Forest stand structure
http://metadata.un.org/sdg/15
Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
topic Biodiversity
Field methods
Multi-taxon
Indicators
Sampling protocol
Forest stand structure
http://metadata.un.org/sdg/15
Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/256275
url http://hdl.handle.net/10261/256275
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.1016/j.ecolind.2021.108266
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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