Mostrar el registro sencillo

dc.contributor.authorSerge, M. A.
dc.contributor.authorMazier, F.
dc.contributor.authorFyfe, R.
dc.contributor.authorGaillard, M.-J.
dc.contributor.authorKlein, Antonio
dc.contributor.authorLagnoux, A.
dc.contributor.authorGalop, D.
dc.contributor.authorGithumbi, E.
dc.contributor.authorMindrescu, M.
dc.contributor.authorNielsen, A. B.
dc.contributor.authorTrondman, A.-K.
dc.contributor.authorPoska, A.
dc.contributor.authorSugita, S.
dc.contributor.authorWoodbridge, J.
dc.contributor.authorAbel-Schaad, Daniel
dc.contributor.authorÅkesson, C.
dc.contributor.authorAlenius, T.
dc.contributor.authorAmmann, B.
dc.contributor.authorPérez Díaz, Sebastián 
dc.contributor.authorPérez Obiol, Ramón
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-10-06T12:52:36Z
dc.date.available2023-10-06T12:52:36Z
dc.date.issued2023
dc.identifier.issn2073-445X
dc.identifier.urihttps://hdl.handle.net/10902/30163
dc.description.abstractReliable quantitative vegetation reconstructions for Europe during the Holocene are crucial to improving our understanding of landscape dynamics, making it possible to assess the past effects of environmental variables and land-use change on ecosystems and biodiversity, and mitigating their effects in the future. We present here the most spatially extensive and temporally continuous pollen-based reconstructions of plant cover in Europe (at a spatial resolution of 1º × 1º) over the Holocene (last 11.7 ka BP) using the "Regional Estimates of VEgetation Abundance from Large Sites" (REVEALS) model. This study has three main aims. First, to present the most accurate and reliable generation of REVEALS reconstructions across Europe so far. This has been achieved by including a larger number of pollen records compared to former analyses, in particular from the Mediterranean area. Second, to discuss methodological issues in the quantification of past land cover by using alternative datasets of relative pollen productivities (RPPs), one of the key input parameters of REVEALS, to test model sensitivity. Finally, to validate our reconstructions with the global forest change dataset. The results suggest that the RPPs.st1 (31 taxa) dataset is best suited to producing regional vegetation cover estimates for Europe. These reconstructions offer a long-term perspective providing unique possibilities to explore spatial-temporal changes in past land cover and biodiversity.es_ES
dc.description.sponsorshipThis research was funded by the TERRANOVA Project, H2020 Marie Sklodowska-Curie grant agreement no. 813904es_ES
dc.format.extent32 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceLand, 2023, 12, 986es_ES
dc.subject.otherEuropees_ES
dc.subject.otherQuantitative past land coveres_ES
dc.subject.otherHolocenees_ES
dc.subject.otherPollen dataes_ES
dc.subject.otherREVEALS modeles_ES
dc.subject.otherRelative pollen productivityes_ES
dc.subject.otherValidationes_ES
dc.titleTesting the Effect of Relative Pollen Productivity on the REVEALS Model: A Validated Reconstruction of Europe-Wide Holocene Vegetationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.3390/land12050986
dc.type.versionpublishedVersiones_ES


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Excepto si se señala otra cosa, la licencia del ítem se describe como © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.