<?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%">De Marco, Alessandra</style></author><author><style face="normal" font="default" size="100%">Proietti, Chiara</style></author><author><style face="normal" font="default" size="100%">Cionni, Irene</style></author><author><style face="normal" font="default" size="100%">Fischer, Richard</style></author><author><style face="normal" font="default" size="100%">Screpanti, Augusto</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%">Future impacts of nitrogen deposition and climate change scenarios on forest crown defoliation.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental pollution (Barking, Essex : 1987)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">climate change</style></keyword><keyword><style  face="normal" font="default" size="100%">Crown defoliation</style></keyword><keyword><style  face="normal" font="default" size="100%">General regression models</style></keyword><keyword><style  face="normal" font="default" size="100%">Nitrogen deposition</style></keyword><keyword><style  face="normal" font="default" size="100%">Random forests analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">194</style></volume><pages><style face="normal" font="default" size="100%">171-180</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Defoliation is an indicator for forest health in response to several stressors including air pollutants, and one of the most important parameters monitored in the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The study aims to estimate crown defoliation in 2030, under three climate and one nitrogen deposition scenarios, based on evaluation of the most important factors (meteorological, nitrogen deposition and chemical soil parameters) affecting defoliation of twelve European tree species. The combination of favourable climate and nitrogen fertilization in the more adaptive species induces a generalized decrease of defoliation. On the other hand, severe climate change and drought are main causes of increase in defoliation in Quercus ilex and Fagus sylvatica, especially in Mediterranean area. Our results provide information on regional distribution of future defoliation, an important knowledge for identifying policies to counteract negative impacts of climate change and air pollution.</style></abstract><accession-num><style face="normal" font="default" size="100%">25118942</style></accession-num></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%">Di Traglia, Mario</style></author><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%">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%">Is cellular automata algorithm able to predict the future dynamical shifts of tree species in Italy under climate change scenarios? A methodological approach</style></title><secondary-title><style face="normal" font="default" size="100%">Ecological Modelling</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">2-d cellular automata</style></keyword><keyword><style  face="normal" font="default" size="100%">climate change</style></keyword><keyword><style  face="normal" font="default" size="100%">Importance Value</style></keyword><keyword><style  face="normal" font="default" size="100%">Logistic analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean basin</style></keyword><keyword><style  face="normal" font="default" size="100%">Potential tree species shift</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://linkinghub.elsevier.com/retrieve/pii/S0304380010006587</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">222</style></volume><pages><style face="normal" font="default" size="100%">925 - 934</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper is presented a methodological approach which integrates statistic modelling and 2-D cellular automata (CA) in order to describe tree species shifts responding to the climate changes foreseen for Italy in the 21st century. Five Italian tree species populations of Abies alba, Pinus sylvestris, Fagus sylvatica, Acer campestris and Quercus suber and their actual potential distributions (PDs) – represented by Importance Value (IV), have been considered. Environmental and climatic relationships have been modelled through application of a new statistical methodology called extreme discretization, where the PD of a species was considered as a random ﬁeld. The IV-based PD has been spatialized through a probability function (A,S), which represented the spatio-temporal relationships between IV values and climatic (A) and geomorphological (S) variables. For each tree species = (A,S) has been estimated and inserted as rule in the 2-D cellular automata. The latter, acting by a Moore neighbouring, took in consideration also the suitability map for tree species, which has been obtained by land cover map. Two time frames (2050 and 2080) and two climatic scenarios (A2 and B1) have been considered. Results described a general reduction of the IV values and their distribution for A. alba, P. sylvestris and F. sylvatica, in both climatic scenarios, whereas an increase of IVs and distribution for Q. suber and only a slight increment of distribution for A. campestris was mainly observed under the B1 scenario, but not for the more limiting A2 scenario. Convergent results have been obtained with respect to other simulation systems concerning the shift of tree species responding to different climatic change scenarios but lacking of the description of dynamical paths. Our approach seems natural and practical to describe such phenomena. The transition rules for the CA and the parameters taken into account for the construction of the probabilistic models can be surely improved to obtain a more realistic pattern of tree species shifts. Future efforts should be made to take in account the inter-speciﬁc relationships inside the Italian forest ecosystems, in order to also consider the competiveness for resources that exert some effects on the plant distribution both in time and space.</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Elsevier B.V.</style></notes></record></records></xml>