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dc.contributor.authorMartin Queller, Emilia Maria
dc.contributor.authorTorras, O.
dc.contributor.authorSolana, J.
dc.contributor.authorAlberdi Asensi, Iciar
dc.contributor.authorSaura Martínez de Toda, Santiago
dc.date.accessioned2015-12-04T11:51:49Z
dc.date.available2015-12-04T11:51:49Z
dc.date.issued2011
dc.identifier.issn2171-5068
dc.identifier.urihttp://hdl.handle.net/10459.1/49239
dc.description.abstractAn integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and altitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general, biodiversity increased in habitats covering wider topographic ranges and comprising forest patches with more complex shapes. Patterns in other relationships varied between indicators (e.g. species richness vs. diversity), or even were opposed (trees vs. shrubs). Our study (1) allowed deepening the understanding of biodiversity patterns in a large set of Spanish forest habitats and (2) highlighted the increasing complexity of identifying common landscape conditions favouring forest biodiversity as the range of analysed biodiversity aspects is widened beyond the more commonly assessed species richness indicators.ca_ES
dc.description.sponsorshipThis work has received financial support from the Ministerio de Ciencia e Innovación (Spain) and FEDER funds through the IBEPFOR (CGL2006- 00312/BOS) project. The NFI data were supplied by the Ministerio de Medio Ambiente y Medio Rural y Marino, Spain).
dc.language.isoengca_ES
dc.publisherInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)ca_ES
dc.relationMIECI/PN2004-2007/CGL2006- 00312/BOS
dc.relation.isformatofReproducció del document publicat a http://revistas.inia.es/index.php/fs/article/view/1878ca_ES
dc.relation.ispartofForest Systems, 2011, vol. 20, núm. 1, p. 151-164ca_ES
dc.rights(c) INIA, 2011ca_ES
dc.subjectAkaike Information Criterionca_ES
dc.subjectMargalef and Shannon diversityca_ES
dc.subjectLandscape ecologyca_ES
dc.titleLarge-scale determinants of diversity across Spanish forest habitats: accounting for model uncertainty in compositional and structural indicatorsca_ES
dc.typearticleca_ES
dc.type.versionpublishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES


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