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dc.contributor.authorGhadban, Siba
dc.contributor.authorAméztegui González, Aitor
dc.contributor.authorRodrigues Mimbrero, Marcos
dc.contributor.authorChocarro, Cristina
dc.contributor.authorAlcasena Urdíroz, Fermín J.
dc.contributor.authorVega García, Cristina
dc.date.accessioned2022-02-18T11:49:34Z
dc.date.available2022-02-18T11:49:34Z
dc.date.issued2021
dc.identifier.issn2071-1050
dc.identifier.urihttp://hdl.handle.net/10459.1/73035
dc.description.abstractPlant diversity is a core value of forests and is rapidly becoming a primary management goal under the threat of global environmental changes. Changing conditions, including forestry interventions, or lack of them, may endanger its preservation. Abandonment of management in forests previously subjected to a multipurpose silviculture and secondary succession is hypothesized to have altered the biodiverse Mediterranean forests in recent years and affected plant diversity. We used data in national forest inventory plots and local landscape ecology metrics from forest cartography, combined with artificial neural networks, to predict richness and Shannon diversity indices for the tree and shrub layers of several Mediterranean forest types. We found that richness and diversity depend on forest structure and on local landscape patterns, and also, though to a lesser degree, on site conditions (mainly soil pH), but not on forest intervention. In order to benefit plant diversity in the forest landscapes analyzed, forest management practices need to promote diameter variety, the presence of large trees, tree cover, variation in the height of trees and shrubs, and a heterogeneous local landscape at the stand level. Aleppo pine forests and Scots pine forests showed more consistent results in their models than cork oak and black pine forests, both of which require further research.ca_ES
dc.description.sponsorshipFinancial support was provided as a scholarship to Siba Ghadban by the Erasmus Mundus Programme MEDfOR funded by the European Commission (https://www.medfor.eu/, accessed on 18 October 2021). This work was conducted under the project CLIMARK (LIFE16 CCM/ES/000065)-Forest management promotion for climate change mitigation through the design of a local market of climatic credits, funded by the European Commission.ca_ES
dc.language.isoengca_ES
dc.publisherMDPIca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.3390/su132111658ca_ES
dc.relation.ispartofSustainability, 2021, vol. 13, núm. 21, p. 1-19ca_ES
dc.rightscc-by (c) Ghadban et al., 2021ca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectLandscape metricsca_ES
dc.subjectForest managementca_ES
dc.subjectArtificial neural networksca_ES
dc.subjectRichnessca_ES
dc.subjectShannon diversity indexca_ES
dc.subject.otherPaisatgeca_ES
dc.subject.otherBoscos--Gestióca_ES
dc.subject.otherBoscos i silviculturaca_ES
dc.titleStand structure and local landscape variables are the dominant factors explaining shrub and tree diversity in Mediterranean forestsca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.identifier.idgrec031724
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.3390/su132111658


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cc-by (c) Ghadban et al., 2021
Except where otherwise noted, this item's license is described as cc-by (c) Ghadban et al., 2021