Show simple item record

dc.contributor.authorDe Cáceres, Miquel
dc.contributor.authorMartín Alcón, Santiago
dc.contributor.authorGonzález-Olabarria, José Ramón
dc.contributor.authorColl Mir, Lluís
dc.date.accessioned2020-03-31T07:44:01Z
dc.date.available2020-04-12T22:11:01Z
dc.date.issued2019
dc.identifier.issn1286-4560
dc.identifier.urihttp://hdl.handle.net/10459.1/68382
dc.description.abstractKey message. We present a novel approach to define pure- and mixed-forest typologies from the comparison of pairs of forest plots in terms of species identity, diameter, and height of their trees. Context. Forest typologies are useful for many purposes, including forest mapping, assessing habitat quality, studying forest dynamics, or defining sustainable management strategies. Quantitative typologies meant for forestry applications normally focus on horizontal and vertical structure of forest plots as main classification criteria, with species composition often playing a secondary role. The selection of relevant variables is often idiosyncratic and influenced by a priori expectations of the forest types to be distinguished. Aims. We present a general framework to define forest typologies where the dissimilarity between forest stands is assessed using coefficients that integrate the information of species composition with the univariate distribution of tree diameters or heights or the bivariate distribution of tree diameters and heights. Methods. We illustrate our proposal with the classification of forest inventory plots in Catalonia (NE Spain), comparing the results obtained using the bivariate distribution of diameters and heights to those obtained using either tree heights or tree diameters only. Results. The number of subtypes obtained using the tree diameter distribution for the calculation of dissimilarity was often the same as those obtained from the tree height distribution or to those using the bivariate distribution. However, classifications obtained using the three approaches were often different in terms of forest plot membership. Conclusion. The proposed classification framework is particularly suited to define forest typologies from forest inventory data and allows taking advantage of the bivariate distribution of diameters and heights if both variables are measured. It can provide support to the development of typologies in situations where fine-scale variability of topographic, climatic, and legacy management factors leads to fine-scale variation in forest structure and composition, including uneven-aged and mixed stands.ca_ES
dc.description.sponsorshipThe study was supported by projects 979S/2013 (Autonomous Agency of National Parks, Spanish Ministry of Agriculture Food and Environment) and a Spanish “Ramon y Cajal” fellowship to M.D.C (RYC-2012-11109).ca_ES
dc.language.isoengca_ES
dc.publisherSpringer Natureca_ES
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1007/s13595-019-0824-0ca_ES
dc.relation.ispartofAnnals of Forest Science, 2019, vol. 76, núm. 40, p. 1-19ca_ES
dc.rights(c) INRA and Springer-Verlag France SAS, part of Springer Nature, 2019ca_ES
dc.subjectDissimilarity coefficientsca_ES
dc.subjectForest plotca_ES
dc.subjectForest typologyca_ES
dc.subjectMixed forestsca_ES
dc.subjectStand structureca_ES
dc.titleA general method for the classification of forest stands using species composition and vertical and horizontal structureca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.identifier.idgrec028885
dc.type.versioninfo:eu-repo/semantics/acceptedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.1007/s13595-019-0824-0


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record