<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Attorre, Fabio</style></author><author><style face="normal" font="default" size="100%">Francesconi, Fabio</style></author><author><style face="normal" font="default" size="100%">Sanctis, Michele</style></author><author><style face="normal" font="default" size="100%">Alfò, Marco</style></author><author><style face="normal" font="default" size="100%">Martella, Francesca</style></author><author><style face="normal" font="default" size="100%">Valenti, Roberto</style></author><author><style face="normal" font="default" size="100%">Vitale, Marcello</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Classifying and Mapping Potential Distribution of Forest Types Using a Finite Mixture Model</style></title><secondary-title><style face="normal" font="default" size="100%">Folia Geobotanica</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Finite Mixture Model</style></keyword><keyword><style  face="normal" font="default" size="100%">forest types</style></keyword><keyword><style  face="normal" font="default" size="100%">Italy</style></keyword><keyword><style  face="normal" font="default" size="100%">Potential distribution</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/index/10.1007/s12224-012-9139-8</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The present paper presents the application of a finite mixture model (FMM) to analyze spatially explicit data on forest composition and environmental variables to produce a high-resolution map of their current potential distribution. FMM provides a convenient yet formal setting for model-based clustering. Within this framework, forest data are assumed to come from an underlying FMM, where each mixture component corresponds to a cluster and each cluster is characterized by a different composition of tree species. An important extension of this model is based on including a set of covariates to predict class membership. These covariates can be climatic and topographical parameters as well as geographical coordinates and the class membership of neighbouring plots. FMM was applied to a national forest inventory of Italy consisting of 6,714 plots with a measure of abundance for 27 tree species. In this way, a map of potential forest types was produced. The limitations and usefulness of the proposed modelling approach were analyzed and discussed, comparing the results with an independently derived expert map</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>3</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rego, F</style></author><author><style face="normal" font="default" size="100%">Godinho-Ferreira, P</style></author><author><style face="normal" font="default" size="100%">Uva, J S</style></author><author><style face="normal" font="default" size="100%">Cunha, J</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Marchetti, M</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Combination of structural and compositional factors for describing forest types using national forest inventory data</style></title><secondary-title><style face="normal" font="default" size="100%">Monitoring and Indicators of Forest Biodiversity in Europe - From Ideas to Operationality</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">composition</style></keyword><keyword><style  face="normal" font="default" size="100%">forest types</style></keyword><keyword><style  face="normal" font="default" size="100%">national forest inventory</style></keyword><keyword><style  face="normal" font="default" size="100%">vertical structure</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">EUROPEAN FOREST INSTITUTE</style></publisher><pub-location><style face="normal" font="default" size="100%">TORIKATU 34, FIN-80100 JOENSUU, FINLAND</style></pub-location><pages><style face="normal" font="default" size="100%">153-162</style></pages><isbn><style face="normal" font="default" size="100%">952-5453-04-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For the first time in Portugal, simple variables describing the vertical structure and the composition of forests on the Portuguese mainland were included in the 2258 sample plots of the National Forest Inventory (DGF 2001). The vertical forest structure was assessed by percentage cover of seven height. classes and the composition of the different layers was described using plant species, or groups of plant species, easily identifiable in the field. Cluster analysis, in particular K-means statistics, was performed using combinations of vertical structure and compositional data, resulting in ten main natural groups or forest types: 1) Quercus pyrenaica forests; 2) Other deciduous oak forests; 3) Arbutus unedo forests; 4) Cistus shrubs; 5) Cytisus shrubs; 6) Acacia forests; 7) Quercus suber forests; 8) Pinus pinaster forests; 9) Eucalyptus forests; and 10) Other forests. The last four groups were further subdivided according to the vertical structure resulting in twenty final forest types. The geographical distribution of these forests types and the implications for biodiversity and other forest issues are presented and discussed.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rego, F.</style></author><author><style face="normal" font="default" size="100%">Godinho-Ferreira, P.</style></author><author><style face="normal" font="default" size="100%">Uva, J. S.</style></author><author><style face="normal" font="default" size="100%">Cunha, J.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Marchetti, M.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Combination of structural and compositional factors for describing forest types using national forest inventory data</style></title><secondary-title><style face="normal" font="default" size="100%">Monitoring and Indicators of Forest Biodiversity in Europe - From Ideas to Operationality</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">composition</style></keyword><keyword><style  face="normal" font="default" size="100%">forest types</style></keyword><keyword><style  face="normal" font="default" size="100%">national forest inventory</style></keyword><keyword><style  face="normal" font="default" size="100%">vertical structure</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005///</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">EUROPEAN FOREST INSTITUTE</style></publisher><pages><style face="normal" font="default" size="100%">153 - 162</style></pages><isbn><style face="normal" font="default" size="100%">952-5453-04-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For the first time in Portugal, simple variables describing the vertical structure and the composition of forests on the Portuguese mainland were included in the 2258 sample plots of the National Forest Inventory (DGF 2001). The vertical forest structure was assessed by percentage cover of seven height. classes and the composition of the different layers was described using plant species, or groups of plant species, easily identifiable in the field. Cluster analysis, in particular K-means statistics, was performed using combinations of vertical structure and compositional data, resulting in ten main natural groups or forest types: 1) Quercus pyrenaica forests; 2) Other deciduous oak forests; 3) Arbutus unedo forests; 4) Cistus shrubs; 5) Cytisus shrubs; 6) Acacia forests; 7) Quercus suber forests; 8) Pinus pinaster forests; 9) Eucalyptus forests; and 10) Other forests. The last four groups were further subdivided according to the vertical structure resulting in twenty final forest types. The geographical distribution of these forests types and the implications for biodiversity and other forest issues are presented and discussed.</style></abstract><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;periodical: Monitoring and Indicators of Forest Biodiversity in Europe - From Ideas to Operationality&lt;br/&gt;issue: 51&lt;br/&gt;pub-location: TORIKATU 34, FIN-80100 JOENSUU, FINLAND</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">van Wesemael, Bas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Litter decomposition and nutrient distribution in humus profiles in some mediterranean forests in southern Tuscany</style></title><secondary-title><style face="normal" font="default" size="100%">Forest Ecology and Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">forest types</style></keyword><keyword><style  face="normal" font="default" size="100%">litter decomposition</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean forest (voyant)</style></keyword><keyword><style  face="normal" font="default" size="100%">mineralization</style></keyword><keyword><style  face="normal" font="default" size="100%">nutrient concentration</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1993</style></year></dates><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">99-114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Decomposition of leaf litter and the distribution of elements in the humus layer were studied in mediterranean deciduous, sclerophyllous and coniferous forests on acid rocks. The results indicate a clear difference in relative decomposition rate between pine needles (Pinus pinaster: 0.12 year−1) and leaves of deciduous and sclerophyllous species (Quercus cerris, Quercus suber and Arbutus unedo: 0.30 year−1). The concentrations of N, P, S and Ca increase upon decomposition, whereas that of K decreases by initial leaching, and those of Mg, Mn (Fe, Al) remain unchanged except for an increase resulting from mineral contamination. In deciduous and sclerophyllous litter, absolute amounts of N, P, S and Ca increase until a critical concentration level is reached, after which net mineralization occurs. For pine needles net mineralization was not observed within 915 days. In analogy with the situation during the litter bag experiments, elemental concentrations are highest in the lower more decomposed part of the humus profiles. In deciduous and sclerophyllous forests net mineralization of N, P, S and Ca starts in the lower part of the fermentation layer. In the coniferous forest elemental concentrations are much lower and no indications of N, P, S and Ca mineralization were found in the ectorganic horizons.</style></abstract></record></records></xml>