<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Catry, Filipe X.</style></author><author><style face="normal" font="default" size="100%">Moreira, Francisco</style></author><author><style face="normal" font="default" size="100%">Cardillo, Enrique</style></author><author><style face="normal" font="default" size="100%">Pausas, Juli G.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Moreira, Francisco</style></author><author><style face="normal" font="default" size="100%">Arianoutsou, Margarita</style></author><author><style face="normal" font="default" size="100%">Corona, Piermaria</style></author><author><style face="normal" font="default" size="100%">De las Heras, Jorge</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Post-Fire Management of Cork Oak Forests</style></title><secondary-title><style face="normal" font="default" size="100%">Post-Fire Management and Restoration of Southern European Forests</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cork harvesting</style></keyword><keyword><style  face="normal" font="default" size="100%">Cork oak forests</style></keyword><keyword><style  face="normal" font="default" size="100%">crown regeneration</style></keyword><keyword><style  face="normal" font="default" size="100%">management</style></keyword><keyword><style  face="normal" font="default" size="100%">natural regeneration</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://link.springer.com/book/10.1007/978-94-007-2208-8/page/1http://www.springerlink.com/index/T14G11G6K89M6643.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Netherlands</style></publisher><isbn><style face="normal" font="default" size="100%">978-94-007-2207-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter concerns the ecology and post-fire management of cork oak forests. It starts with a short overview of ecological and socio-economic context, continuing with an introduction on the cork oak post-fire regeneration strategies and the main factors affecting tree responses. Several post-fire management issues and alternatives, such as tree logging, assisting natural regeneration, reforestation, cork harvesting and pruning, or protecting against herbivory, are also 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: Post-Fire Management and Restoration of Southern European Forests&lt;br/&gt;electronic-resource-num: 10.1007/978-94-007-2208-8</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%">Corona, Piermaria</style></author><author><style face="normal" font="default" size="100%">Dettori, Sandro</style></author><author><style face="normal" font="default" size="100%">Filigheddu, Maria Rosaria</style></author><author><style face="normal" font="default" size="100%">Maetzke, Federico</style></author><author><style face="normal" font="default" size="100%">Scotti, Roberto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Site quality evaluation by classification tree: an application to cork quality in Sardinia</style></title><secondary-title><style face="normal" font="default" size="100%">European Journal of Forest Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classiﬁcation tree</style></keyword><keyword><style  face="normal" font="default" size="100%">Cork quality</style></keyword><keyword><style  face="normal" font="default" size="100%">Logistic regression</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus suber</style></keyword><keyword><style  face="normal" font="default" size="100%">Site classiﬁcation and evaluation</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><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/index/10.1007/s10342-004-0047-1</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">124</style></volume><pages><style face="normal" font="default" size="100%">37 - 46</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cork harvesting and stopper production represent a major forest industry in Sardinia (Italy). The target of the present investigation was to evaluate the ‘‘classiﬁcation tree’’ as a tool to discover possible relationships between microsite characteristics and cork quality. Seven main cork oak (Quercus suber) producing areas have been identiﬁed in Sardinia, for a total of more than 122,000 ha. Sixty-three sample trees, distributed among diﬀerent geographical locations and microsite conditions, were selected. A soil proﬁle near each sample tree was described, soil samples were collected and analysed. After debarking, cork quality of each sample tree was graded by an independent panel of experts. Microsites where trees had more than 50% of the extracted cork graded in the best quality class, according to the oﬃcial quality standard in Italy, were labelled as prime microsites, the others as nonprime microsites. Relationships between a binary dummy variable (0 for nonprime microsites, 1 for prime microsites) and site factors were investigated using classiﬁcation tree analysis to select the relevant variables and to deﬁne the classiﬁcation scheme. Prime quality microsites for cork production proved to be characterised by elevation, soil phosphorus content and sandiness. Results have been compared with those of the more conventional parametric approach by logistic regression. The work demonstrates the advantages of the classiﬁcation tree method. The model may be appropriate for classiﬁcations at landscape and stand mapping levels, where it is possible to sample a number of microsites and to evaluate distributional characteristics of model output, while its precision is only indicative when estimating the prime quality of single microsites.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></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%">Corona, Piermaria</style></author><author><style face="normal" font="default" size="100%">Dettori, Sandro</style></author><author><style face="normal" font="default" size="100%">Filigheddu, Maria Rosaria</style></author><author><style face="normal" font="default" size="100%">Maetzke, Federico</style></author><author><style face="normal" font="default" size="100%">Scotti, Roberto</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Site quality evaluation by classification tree: an application to cork quality in Sardinia</style></title><secondary-title><style face="normal" font="default" size="100%">European Journal of Forest Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classiﬁcation tree</style></keyword><keyword><style  face="normal" font="default" size="100%">Cork quality</style></keyword><keyword><style  face="normal" font="default" size="100%">Logistic regression</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus suber</style></keyword><keyword><style  face="normal" font="default" size="100%">Site classiﬁcation and evaluation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">124</style></volume><pages><style face="normal" font="default" size="100%">37-46</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Cork harvesting and stopper production represent a major forest industry in Sardinia (Italy). The target of the present investigation was to evaluate the ‘‘classiﬁcation tree’’ as a tool to discover possible relationships between microsite characteristics and cork quality. Seven main cork oak (Quercus suber) producing areas have been identiﬁed in Sardinia, for a total of more than 122,000 ha. Sixty-three sample trees, distributed among diﬀerent geographical locations and microsite conditions, were selected. A soil proﬁle near each sample tree was described, soil samples were collected and analysed. After debarking, cork quality of each sample tree was graded by an independent panel of experts. Microsites where trees had more than 50% of the extracted cork graded in the best quality class, according to the oﬃcial quality standard in Italy, were labelled as prime microsites, the others as nonprime microsites. Relationships between a binary dummy variable (0 for nonprime microsites, 1 for prime microsites) and site factors were investigated using classiﬁcation tree analysis to select the relevant variables and to deﬁne the classiﬁcation scheme. Prime quality microsites for cork production proved to be characterised by elevation, soil phosphorus content and sandiness. Results have been compared with those of the more conventional parametric approach by logistic regression. The work demonstrates the advantages of the classiﬁcation tree method. The model may be appropriate for classiﬁcations at landscape and stand mapping levels, where it is possible to sample a number of microsites and to evaluate distributional characteristics of model output, while its precision is only indicative when estimating the prime quality of single microsites.</style></abstract></record></records></xml>