<?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 Andrés, Juan Manuel</style></author><author><style face="normal" font="default" size="100%">Borge, Rafael</style></author><author><style face="normal" font="default" size="100%">de la Paz, David</style></author><author><style face="normal" font="default" size="100%">Lumbreras, Julio</style></author><author><style face="normal" font="default" size="100%">Rodríguez, Encarnación</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementation of a module for risk of ozone impacts assessment to vegetation in the Integrated Assessment Modelling system for the Iberian Peninsula. Evaluation for wheat and Holm oak.</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%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: toxicity</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">CMAQ WRF</style></keyword><keyword><style  face="normal" font="default" size="100%">Critical level</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">iberian peninsula</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone risk assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: toxicity</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: drug effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: growth &amp; development</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Stomatal conductance</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum: drug effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Triticum: growth &amp; development</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.ncbi.nlm.nih.gov/pubmed/22398018</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">165</style></volume><pages><style face="normal" font="default" size="100%">25 - 37</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A module to estimate risks of ozone damage to vegetation has been implemented in the Integrated Assessment Modelling system for the Iberian Peninsula. It was applied to compute three different indexes for wheat and Holm oak; daylight AOT40 (cumulative ozone concentration over 40 ppb), cumulative ozone exposure index according to the Directive 2008/50/EC (AOT40-D) and POD(Y) (Phytotoxic Ozone Dose over a given threshold of Y nmol m(-2) s(-1)). The use of these indexes led to remarkable differences in spatial patterns of relative ozone risks on vegetation. Ozone critical levels were exceeded in most of the modelling domain and soil moisture content was found to have a significant impact on the results. According to the outputs of the model, daylight AOT40 constitutes a more conservative index than the AOT40-D. Additionally, flux-based estimations indicate high risk areas in Portugal for both wheat and Holm oak that are not identified by AOT-based methods.</style></abstract><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Elsevier Ltd&lt;br/&gt;accession-num: 22398018</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%">Gómez-Aparicio, LORENA</style></author><author><style face="normal" font="default" size="100%">Ibáñez, Beatriz</style></author><author><style face="normal" font="default" size="100%">Serrano, María S.</style></author><author><style face="normal" font="default" size="100%">De Vita, Paolo</style></author><author><style face="normal" font="default" size="100%">Avila, José M.</style></author><author><style face="normal" font="default" size="100%">Pérez-Ramos, Ignacio M.</style></author><author><style face="normal" font="default" size="100%">García, Luis V.</style></author><author><style face="normal" font="default" size="100%">Esperanza Sánchez, M.</style></author><author><style face="normal" font="default" size="100%">Marañón, Teodoro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial patterns of soil pathogens in declining Mediterranean forests: implications for tree species regeneration.</style></title><secondary-title><style face="normal" font="default" size="100%">The New phytologist</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Forest decline</style></keyword><keyword><style  face="normal" font="default" size="100%">Host-Pathogen Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean Region</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">neighborhood models</style></keyword><keyword><style  face="normal" font="default" size="100%">Phytophthora</style></keyword><keyword><style  face="normal" font="default" size="100%">Phytophthora: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Pythium</style></keyword><keyword><style  face="normal" font="default" size="100%">Pythium: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus suber</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">regeneration dynamics</style></keyword><keyword><style  face="normal" font="default" size="100%">Seedling</style></keyword><keyword><style  face="normal" font="default" size="100%">Seedling: microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil Microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">soil texture</style></keyword><keyword><style  face="normal" font="default" size="100%">soil-borne pathogens</style></keyword><keyword><style  face="normal" font="default" size="100%">species coexistence</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.ncbi.nlm.nih.gov/pubmed/22428751</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">194</style></volume><pages><style face="normal" font="default" size="100%">1014 - 1024</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Soil-borne pathogens are a key component of the belowground community because of the significance of their ecological and socio-economic impacts. However, very little is known about the complexity of their distribution patterns in natural systems. Here, we explored the patterns, causes and ecological consequences of spatial variability in pathogen abundance in Mediterranean forests affected by oak decline. We used spatially explicit neighborhood models to predict the abundance of soil-borne pathogen species (Phytophthora cinnamomi, Pythium spiculum and Pythium spp.) as a function of local abiotic conditions (soil texture) and the characteristics of the tree and shrub neighborhoods (species composition, size and health status). The implications of pathogen abundance for tree seedling performance were explored by conducting a sowing experiment in the same locations in which pathogen abundance was quantified. Pathogen abundance in the forest soil was not randomly distributed, but exhibited spatially predictable patterns influenced by both abiotic and, particularly, biotic factors (tree and shrub species). Pathogen abundance reduced seedling emergence and survival, but not in all sites or tree species. Our findings suggest that heterogeneous spatial patterns of pathogen abundance at fine spatial scale can be important for the dynamics and restoration of declining Mediterranean forests.</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;accession-num: 22428751</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%">Simonson, William D</style></author><author><style face="normal" font="default" size="100%">Allen, Harriet D</style></author><author><style face="normal" font="default" size="100%">Coomes, David A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of an airborne lidar system to model plant species composition and diversity of Mediterranean oak forests.</style></title><secondary-title><style face="normal" font="default" size="100%">Conservation biology : the journal of the Society for Conservation Biology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">cluster analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Conservation of Natural Resources</style></keyword><keyword><style  face="normal" font="default" size="100%">Conservation of Natural Resources: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">mediterranean oak forest</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">predictive modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote Sensing Technology</style></keyword><keyword><style  face="normal" font="default" size="100%">Remote Sensing Technology: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">vascular plants</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">840-850</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Airborne lidar is a remote-sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three-dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape-level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first-and-last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar- and field-measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar-measured vegetation height (R(2) = 0.50, p &lt; 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground-truthing and its timing relative to acquisition of lidar data.</style></abstract><accession-num><style face="normal" font="default" size="100%">22731687</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%">Alonso, Rocío</style></author><author><style face="normal" font="default" size="100%">Vivanco, Marta G</style></author><author><style face="normal" font="default" size="100%">González-Fernández, Ignacio</style></author><author><style face="normal" font="default" size="100%">Bermejo, Victoria</style></author><author><style face="normal" font="default" size="100%">Palomino, Inmaculada</style></author><author><style face="normal" font="default" size="100%">Garrido, Juan Luis</style></author><author><style face="normal" font="default" size="100%">Elvira, Susana</style></author><author><style face="normal" font="default" size="100%">Salvador, Pedro</style></author><author><style face="normal" font="default" size="100%">Artíñano, Begoña</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling the influence of peri-urban trees in the air quality of Madrid region (Spain).</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%">Air Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">air pollution</style></keyword><keyword><style  face="normal" font="default" size="100%">Air pollution removal</style></keyword><keyword><style  face="normal" font="default" size="100%">Air Pollution: statistics &amp; numerical data</style></keyword><keyword><style  face="normal" font="default" size="100%">Air quality models</style></keyword><keyword><style  face="normal" font="default" size="100%">Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">Cities</style></keyword><keyword><style  face="normal" font="default" size="100%">Dry deposition</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Spain</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Urban forest</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier Ltd</style></publisher><volume><style face="normal" font="default" size="100%">159</style></volume><pages><style face="normal" font="default" size="100%">2138-2147</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Tropospheric ozone (O(3)) is considered one of the most important air pollutants affecting human health. The role of peri-urban vegetation in modifying O(3) concentrations has been analyzed in the Madrid region (Spain) using the V200603par-rc1 version of the CHIMERE air quality model. The 3.7 version of the MM5 meteorological model was used to provide meteorological input data to the CHIMERE. The emissions were derived from the EMEP database for 2003. Land use data and the stomatal conductance model included in CHIMERE were modified according to the latest information available for the study area. Two cases were considered for the period April-September 2003: (1) actual land use and (2) a fictitious scenario where El Pardo peri-urban forest was converted to bare-soil. The results show that El Pardo forest constitutes a sink of O(3) since removing this green area increased O(3) levels over the modified area and over down-wind surrounding areas.</style></abstract><accession-num><style face="normal" font="default" size="100%">21269745</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%">Romeralo, María</style></author><author><style face="normal" font="default" size="100%">Moya-Laraño, Jordi</style></author><author><style face="normal" font="default" size="100%">Lado, Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Social amoebae: environmental factors influencing their distribution and diversity across south-western Europe.</style></title><secondary-title><style face="normal" font="default" size="100%">Microbial ecology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictyosteliida</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictyosteliida: classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictyosteliida: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictyosteliida: isolation &amp; purification</style></keyword><keyword><style  face="normal" font="default" size="100%">Dictyosteliida: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil: parasitology</style></keyword><keyword><style  face="normal" font="default" size="100%">SPAIN (citation)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">154-165</style></pages><isbn><style face="normal" font="default" size="100%">0024801097</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The social amoebae (dictyostelids) are the only truly multicellular lineage within the superkingdom Amoebozoa, the sister group to Ophistokonts (Metazoa+Fungi). Despite the exceptional phylogenetic and evolutionary value of this taxon, the environmental factors that determine their distribution and diversity are largely unknown. We have applied statistical modeling to a set of data obtained from an extensive and detailed survey in the south-western of Europe (The Iberian Peninsula including Spain and Portugal) in order to estimate some of the main environmental factors influencing the distribution and diversity of dictyostelid in temperate climates. It is the first time that this methodology is applied to the study of this unique group of soil microorganisms. Our results show that a combination of climatic (temperature, water availability), physical (pH) and vegetation (species richness) factors favor dictyostelid species richness. In the Iberian Peninsula, dictyostelid diversity is highest in colder and wet environments, indicating that this group has likely diversified in relatively cold places with high levels of water availability.</style></abstract><accession-num><style face="normal" font="default" size="100%">20614116</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%">Figueira, Rui</style></author><author><style face="normal" font="default" size="100%">Tavares, Paula C</style></author><author><style face="normal" font="default" size="100%">Palma, Luís</style></author><author><style face="normal" font="default" size="100%">Beja, Pedro</style></author><author><style face="normal" font="default" size="100%">Sérgio, Cecília</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of indicator kriging to the complementary use of bioindicators at three trophic levels.</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%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Bioindicators</style></keyword><keyword><style  face="normal" font="default" size="100%">birds</style></keyword><keyword><style  face="normal" font="default" size="100%">Birds: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: instrumentation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: statistics &amp; numerical d</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicator kriging</style></keyword><keyword><style  face="normal" font="default" size="100%">Indices</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Mosses</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">157</style></volume><pages><style face="normal" font="default" size="100%">2689-2696</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The use of biological indicators is widespread in environmental monitoring, although it has long been recognised that each bioindicator is generally associated with a range of potential limitations and shortcomings. To circumvent this problem, this study adopted the complementary use of bioindicators representing different trophic levels and providing different type of information, in an innovative approach to integrate knowledge and to estimate the overall health state of ecosystems. The approach is illustrated using mercury contamination in primary producers (mosses), primary consumers (domestic pigeons and red-legged partridges) and top predators (Bonelli's eagles) in southern Portugal. Indicator kriging geostatistics was used to identify the areas where mercury concentration was higher than the median for each species, and to produce an index that combines mercury contamination across trophic levels. Spatial patterns of mercury contamination were consistent across species. The combined index provided a new level of information useful in incorporating measures of overall environmental contamination into pollution studies.</style></abstract><accession-num><style face="normal" font="default" size="100%">19477568</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%">Figueira, Rui</style></author><author><style face="normal" font="default" size="100%">Tavares, Paula C.</style></author><author><style face="normal" font="default" size="100%">Palma, Luís</style></author><author><style face="normal" font="default" size="100%">Beja, Pedro</style></author><author><style face="normal" font="default" size="100%">Sérgio, Cecília</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of indicator kriging to the complementary use of bioindicators at three trophic levels.</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%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Bioindicators</style></keyword><keyword><style  face="normal" font="default" size="100%">birds</style></keyword><keyword><style  face="normal" font="default" size="100%">Birds: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Bryophyta: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecosystem</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: instrumentation</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring: statistics &amp; numerical d</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Pollutants: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Feathers: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicator kriging</style></keyword><keyword><style  face="normal" font="default" size="100%">Indices</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Mercury: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Mosses</style></keyword><keyword><style  face="normal" font="default" size="100%">Portugal</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19477568</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">157</style></volume><pages><style face="normal" font="default" size="100%">2689 - 2696</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The use of biological indicators is widespread in environmental monitoring, although it has long been recognised that each bioindicator is generally associated with a range of potential limitations and shortcomings. To circumvent this problem, this study adopted the complementary use of bioindicators representing different trophic levels and providing different type of information, in an innovative approach to integrate knowledge and to estimate the overall health state of ecosystems. The approach is illustrated using mercury contamination in primary producers (mosses), primary consumers (domestic pigeons and red-legged partridges) and top predators (Bonelli's eagles) in southern Portugal. Indicator kriging geostatistics was used to identify the areas where mercury concentration was higher than the median for each species, and to produce an index that combines mercury contamination across trophic levels. Spatial patterns of mercury contamination were consistent across species. The combined index provided a new level of information useful in incorporating measures of overall environmental contamination into pollution studies.</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;accession-num: 19477568</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%">Grote, Rüdiger</style></author><author><style face="normal" font="default" size="100%">LAVOIR, ANNE-VIOLETTE</style></author><author><style face="normal" font="default" size="100%">Rambal, Serge</style></author><author><style face="normal" font="default" size="100%">Staudt, Michael</style></author><author><style face="normal" font="default" size="100%">Zimmer, Ina</style></author><author><style face="normal" font="default" size="100%">Schnitzler, Jörg-Peter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling the drought impact on monoterpene fluxes from an evergreen Mediterranean forest canopy.</style></title><secondary-title><style face="normal" font="default" size="100%">Oecologia</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Carbon dioxide</style></keyword><keyword><style  face="normal" font="default" size="100%">Carbon Dioxide: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Computer Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Drought impact</style></keyword><keyword><style  face="normal" font="default" size="100%">Droughts</style></keyword><keyword><style  face="normal" font="default" size="100%">France</style></keyword><keyword><style  face="normal" font="default" size="100%">Model coupling</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">monoterpene emission</style></keyword><keyword><style  face="normal" font="default" size="100%">Monoterpenes</style></keyword><keyword><style  face="normal" font="default" size="100%">Monoterpenes: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">photosynthesis</style></keyword><keyword><style  face="normal" font="default" size="100%">Photosynthesis: physiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex (holm oak)</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Scaling</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">water</style></keyword><keyword><style  face="normal" font="default" size="100%">Water: metabolism</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">160</style></volume><pages><style face="normal" font="default" size="100%">213-223</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In many ecosystems drought cycles are common during the growing season but their impact on volatile monoterpene emissions is unclear. Therefore, we aimed to develop and evaluate a process-based modelling approach to explore the explanatory power of likely mechanisms. The biochemically based isoprene and monoterpene emission model SIM-BIM2 has been modified and linked to a canopy model and a soil water balance model. Simulations are carried out for Quercus ilex forest sites and results are compared to measured soil water, photosynthesis, terpene-synthase activity, and monoterpene emission rates. Finally, the coupled model system is used to estimate the annual drought impact on photosynthesis and emission. The combined and adjusted vegetation model was able to simulate photosynthesis and monoterpene emission under dry and irrigated conditions with an R(2) of 0.74 and 0.52, respectively. We estimated an annual reduction of monoterpene emission of 67% for the extended and severe drought period in 2006 in the investigated Mediterranean ecosystem. It is concluded that process-based ecosystem models can provide a useful tool to investigate the involved mechanisms and to quantify the importance of specific environmental constraints.</style></abstract><accession-num><style face="normal" font="default" size="100%">19219456</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%">KEENAN, Trevor</style></author><author><style face="normal" font="default" size="100%">Niinemets, Ülo</style></author><author><style face="normal" font="default" size="100%">Sabaté, Santi</style></author><author><style face="normal" font="default" size="100%">Gracia, Carlos</style></author><author><style face="normal" font="default" size="100%">Penuelas, Josep</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Seasonality of monoterpene emission potentials in Quercus ilex and Pinus pinea: Implications for regional VOC emissions modeling</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Geophysical Research: Atmospheres</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Holm oak</style></keyword><keyword><style  face="normal" font="default" size="100%">Italian stone pine</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">regional inventory</style></keyword><keyword><style  face="normal" font="default" size="100%">Seasonality</style></keyword><keyword><style  face="normal" font="default" size="100%">VOC emissions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">114</style></volume><pages><style face="normal" font="default" size="100%">n/a--n/a</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">VOC emissions from terrestrial ecosystems provide one of the principal controls over oxidative photochemistry in the lower atmosphere and the resulting air pollution. Such atmospheric processes have strong seasonal cycles. Although similar seasonal cycles in VOC emissions from terrestrial ecosystems have been reported, regional emissions inventories generally omit the effect of seasonality on emissions. We compiled measurement data on seasonal variations in monoterpene emissions potentials for two evergreen species (Quercus ilex and Pinus pinea) and used these data to construct two contrasting seasonal response functions for the inclusion in monoterpene emission models. We included these responses in the Niinemets et al. model and compared simulation results to those of the MEGAN model, both with and without its predicted seasonality. The effect of seasonality on regional monoterpene emissions inventories for European Mediterranean forests dominated by these species was tested for both models, using the GOTILWA+ biosphere model platform. The consideration of seasonality in the Niinemets et al. model reduced total estimated annual monoterpene emissions by up to 65% in some regions, with largest reductions at lower latitudes. The MEGAN model demonstrated a much weaker seasonal response than that in the Niinemets et al. model, and did not capture the between species seasonality differences found in this study. Results suggest that previous regional model inventories based on one fixed emission factor likely overestimate regional emissions, and species-specific expressions of seasonality may be necessary. The consideration of seasonality both largely reduces monoterpene emissions estimates, and changes their expected seasonal distribution.</style></abstract></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%">Espín, Juan Carlos</style></author><author><style face="normal" font="default" size="100%">González-Barrio, Rocío</style></author><author><style face="normal" font="default" size="100%">Cerdá, Begoña</style></author><author><style face="normal" font="default" size="100%">López-Bote, Clemente</style></author><author><style face="normal" font="default" size="100%">Rey, Ana I</style></author><author><style face="normal" font="default" size="100%">Tomás-Barberán, Francisco a</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Agricultural and Food Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animal</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">bile</style></keyword><keyword><style  face="normal" font="default" size="100%">bioavailability</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Availability</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Fluids</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Fluids: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Cereals</style></keyword><keyword><style  face="normal" font="default" size="100%">Cereals: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">colon</style></keyword><keyword><style  face="normal" font="default" size="100%">diet</style></keyword><keyword><style  face="normal" font="default" size="100%">ellagic acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Ellagitannin</style></keyword><keyword><style  face="normal" font="default" size="100%">gall bladder</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins: pharmacokinetics</style></keyword><keyword><style  face="normal" font="default" size="100%">intestine</style></keyword><keyword><style  face="normal" font="default" size="100%">metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Seeds</style></keyword><keyword><style  face="normal" font="default" size="100%">Seeds: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Swine</style></keyword><keyword><style  face="normal" font="default" size="100%">Swine: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Tissue Distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">urolithin</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><publisher><style face="normal" font="default" size="100%">American Chemical Society</style></publisher><volume><style face="normal" font="default" size="100%">55</style></volume><pages><style face="normal" font="default" size="100%">10476-10485</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Ellagitannin-containing foods (strawberries, walnuts, pomegranate, raspberries, oak-aged wine, etc.) have attracted attention due to their cancer chemopreventive, cardioprotective, and antioxidant effects. Ellagitannins (ETs) are not absorbed as such but are metabolized by the intestinal flora to yield urolithins (hydroxydibenzopyran-6-one derivatives). In this study, Iberian pig is used as a model to clarify human ET metabolism. Pigs were fed either cereal fodder or acorns, a rich source of ETs. Plasma, urine, bile, lumen and intestinal tissues (jejunum and colon), feces, liver, kidney, heart, brain, lung, muscle, and subcutaneous fat tissue were analyzed. The results demonstrate that acorn ETs release ellagic acid (EA) in the jejunum, then the intestinal flora metabolizes EA sequentially to yield tetrahydroxy- (urolithin D), trihydroxy- (urolithin C), dihydroxy- (urolithin A), and monohydroxy- (urolithin B) dibenzopyran-6-one metabolites, which were absorbed preferentially when their lipophilicity increased. Thirty-one ET-derived metabolites were detected, including 25 urolithin and 6 EA derivatives. Twenty-six extensively conjugated metabolites were detected in bile, glucuronides and methyl glucuronides of EA and particularly urolithin A, C, and D derivatives, confirming a very active enterohepatic circulation. Urolithins A and B as well as dimethyl-EA-glucuronide were detected in peripheral plasma. The presence of EA metabolites in bile and in urine and its absence in intestinal tissues suggested its absorption in the stomach. Urolithin A was the only metabolite detected in feces and together with its glucuronide was the most abundant metabolite in urine. No metabolites accumulated in any organ analyzed. The whole metabolism of ETs is shown for the first time, confirming previous studies in humans and explaining the long persistency of urolithin metabolites in the body mediated by an active enterohepatic circulation.</style></abstract><accession-num><style face="normal" font="default" size="100%">17990850</style></accession-num><notes><style face="normal" font="default" size="100%">From Duplicate 2 (Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans - Espín, Juan Carlos; González-Barrio, Rocío; Cerdá, Begoña; López-Bote, Clemente; Rey, Ana I; Tomás-Barberán, Francisco A)</style></notes><research-notes><style face="normal" font="default" size="100%">From Duplicate 2 (Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans - Espín, Juan Carlos; González-Barrio, Rocío; Cerdá, Begoña; López-Bote, Clemente; Rey, Ana I; Tomás-Barberán, Francisco A)</style></research-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%">Espín, Juan Carlos</style></author><author><style face="normal" font="default" size="100%">González-Barrio, Rocío</style></author><author><style face="normal" font="default" size="100%">Cerdá, Begoña</style></author><author><style face="normal" font="default" size="100%">López-Bote, Clemente</style></author><author><style face="normal" font="default" size="100%">Rey, Ana I.</style></author><author><style face="normal" font="default" size="100%">Tomás-Barberán, Francisco a</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Agricultural and Food Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animal</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">bile</style></keyword><keyword><style  face="normal" font="default" size="100%">bioavailability</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Availability</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Fluids</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Fluids: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Cereals</style></keyword><keyword><style  face="normal" font="default" size="100%">Cereals: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">colon</style></keyword><keyword><style  face="normal" font="default" size="100%">diet</style></keyword><keyword><style  face="normal" font="default" size="100%">ellagic acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Ellagitannin</style></keyword><keyword><style  face="normal" font="default" size="100%">gall bladder</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrolyzable Tannins: pharmacokinetics</style></keyword><keyword><style  face="normal" font="default" size="100%">intestine</style></keyword><keyword><style  face="normal" font="default" size="100%">metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Seeds</style></keyword><keyword><style  face="normal" font="default" size="100%">Seeds: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Swine</style></keyword><keyword><style  face="normal" font="default" size="100%">Swine: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Tissue Distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">urolithin</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17990850http://dx.doi.org/10.1021/jf0723864</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">55</style></volume><pages><style face="normal" font="default" size="100%">10476 - 10485</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Ellagitannin-containing foods (strawberries, walnuts, pomegranate, raspberries, oak-aged wine, etc.) have attracted attention due to their cancer chemopreventive, cardioprotective, and antioxidant effects. Ellagitannins (ETs) are not absorbed as such but are metabolized by the intestinal flora to yield urolithins (hydroxydibenzopyran-6-one derivatives). In this study, Iberian pig is used as a model to clarify human ET metabolism. Pigs were fed either cereal fodder or acorns, a rich source of ETs. Plasma, urine, bile, lumen and intestinal tissues (jejunum and colon), feces, liver, kidney, heart, brain, lung, muscle, and subcutaneous fat tissue were analyzed. The results demonstrate that acorn ETs release ellagic acid (EA) in the jejunum, then the intestinal flora metabolizes EA sequentially to yield tetrahydroxy- (urolithin D), trihydroxy- (urolithin C), dihydroxy- (urolithin A), and monohydroxy- (urolithin B) dibenzopyran-6-one metabolites, which were absorbed preferentially when their lipophilicity increased. Thirty-one ET-derived metabolites were detected, including 25 urolithin and 6 EA derivatives. Twenty-six extensively conjugated metabolites were detected in bile, glucuronides and methyl glucuronides of EA and particularly urolithin A, C, and D derivatives, confirming a very active enterohepatic circulation. Urolithins A and B as well as dimethyl-EA-glucuronide were detected in peripheral plasma. The presence of EA metabolites in bile and in urine and its absence in intestinal tissues suggested its absorption in the stomach. Urolithin A was the only metabolite detected in feces and together with its glucuronide was the most abundant metabolite in urine. No metabolites accumulated in any organ analyzed. The whole metabolism of ETs is shown for the first time, confirming previous studies in humans and explaining the long persistency of urolithin metabolites in the body mediated by an active enterohepatic circulation.</style></abstract><issue><style face="normal" font="default" size="100%">25</style></issue><notes><style face="normal" font="default" size="100%">From Duplicate 2 (Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans - Espín, Juan Carlos; González-Barrio, Rocío; Cerdá, Begoña; López-Bote, Clemente; Rey, Ana I; Tomás-Barberán, Francisco A)From Duplicate 2 (Iberian Pig as a Model To Clarify Obscure Points in the Bioavailability and Metabolism of Ellagitannins in Humans - Espín, Juan Carlos; González-Barrio, Rocío; Cerdá, Begoña; López-Bote, Clemente; Rey, Ana I; Tomás-Barberán, Francisco A)The following values have no corresponding Zotero field:&lt;br/&gt;publisher: American Chemical Society&lt;br/&gt;accession-num: 17990850</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%">Grote, Rüdiger</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sensitivity of volatile monoterpene emission to changes in canopy structure: a model-based exercise with a process-based emission model</style></title><secondary-title><style face="normal" font="default" size="100%">New Phytologist</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">biomass</style></keyword><keyword><style  face="normal" font="default" size="100%">foliage distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">leaf area index</style></keyword><keyword><style  face="normal" font="default" size="100%">light</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">monoterpene emission</style></keyword><keyword><style  face="normal" font="default" size="100%">Monoterpenes</style></keyword><keyword><style  face="normal" font="default" size="100%">Monoterpenes: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">photosynthesis</style></keyword><keyword><style  face="normal" font="default" size="100%">Photosynthesis: radiation effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Leaves: radiation effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus ilex</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: radiation effects</style></keyword><keyword><style  face="normal" font="default" size="100%">Scaling</style></keyword><keyword><style  face="normal" font="default" size="100%">stand density</style></keyword><keyword><style  face="normal" font="default" size="100%">Temperature</style></keyword><keyword><style  face="normal" font="default" size="100%">Time Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Volatilization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><publisher><style face="normal" font="default" size="100%">Blackwell Publishing Ltd</style></publisher><volume><style face="normal" font="default" size="100%">173</style></volume><pages><style face="normal" font="default" size="100%">550-561</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">* • This paper investigates the dependence of monoterpene emissions at the canopy scale on total leaf area and leaf distribution. Simulations were carried out for a range of hypothetical but realistic forest canopies of the evergreen Quercus ilex (holm oak). * • Two emission models were applied that either did (SIM-BIM2) or did not (G93) account for cumulative responses to temperature and light. Both were embedded into a canopy model that considered spatial and temporal variations of foliage properties. This canopy model was coupled to a canopy climate model (CANOAK) to determine the micrometeorological conditions at the leaf scale. * • Structural properties considerably impacted monoterpene emission. The sensitivities to changes in total leaf area and to leaf area distribution were found to be of similar magnitude. The two different models performed similarly on a whole-year basis but showed clear differences during certain episodes. * • The analysis showed that structural indices have to be carefully evaluated for proper scaling of emission from leaves to canopy. Further research is encouraged on seasonal dynamics of emission potentials.</style></abstract><accession-num><style face="normal" font="default" size="100%">17244049</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%">Lavado Contador, J F</style></author><author><style face="normal" font="default" size="100%">Maneta, M</style></author><author><style face="normal" font="default" size="100%">Schnabel, S</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of near-surface soil moisture at large scale by digital terrain modeling and neural networks.</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental monitoring and assessment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Dehesa</style></keyword><keyword><style  face="normal" font="default" size="100%">forecasting soil moisture</style></keyword><keyword><style  face="normal" font="default" size="100%">humidity</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks (Computer)</style></keyword><keyword><style  face="normal" font="default" size="100%">sampling</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil</style></keyword><keyword><style  face="normal" font="default" size="100%">topographic variables</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">121</style></volume><pages><style face="normal" font="default" size="100%">213-232</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.</style></abstract><accession-num><style face="normal" font="default" size="100%">16752041</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%">Giorgio, Egidio</style></author><author><style face="normal" font="default" size="100%">Maddau, Lucia</style></author><author><style face="normal" font="default" size="100%">Spanu, Emanuela</style></author><author><style face="normal" font="default" size="100%">Evidente, Antonio</style></author><author><style face="normal" font="default" size="100%">Rosini, Carlo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assignment of the Absolute Configuration of (+)-Diplopyrone, the Main Phytotoxin Produced by Diplodia mutila, the Pathogen of the Cork Oak Decline, by a Nonempirical Analysis of Its Chiroptical Properties†</style></title><secondary-title><style face="normal" font="default" size="100%">The Journal of Organic Chemistry</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">absolute configuration</style></keyword><keyword><style  face="normal" font="default" size="100%">Circular dichroism</style></keyword><keyword><style  face="normal" font="default" size="100%">DeVoe method</style></keyword><keyword><style  face="normal" font="default" size="100%">diplopyrone (voyant)</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitosporic Fungi</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitosporic Fungi: pathogenicity</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Structure</style></keyword><keyword><style  face="normal" font="default" size="100%">mycotoxins</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycotoxins: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Optical rotation</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Diseases: microbiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrones</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyrones: chemistry</style></keyword><keyword><style  face="normal" font="default" size="100%">Stereoisomerism</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">American Chemical Society</style></publisher><volume><style face="normal" font="default" size="100%">70</style></volume><pages><style face="normal" font="default" size="100%">7-13</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The nonempirical assignment of the absolute configuration of (+)-diplopyrone, the main phytotoxin of Diplodia mutila, i.e., an endophytic fungus, widespread in Sardinian oak forests, and considered one of the main causes of cork oak decline, has been approached by two different methods:? (a) the exciton analysis of the circular dichroism (CD) spectrum and (b) the ab initio calculation of the optical rotatory power. Both methods indicate that (+)-diplopyrone is 6-[(1S)-1-hydroxyethyl]-2,4a(S),6(R),8a(S)-tetrahydropyrano[3,2-b]pyran-2-one, so the stereostructure of this important biomolecule is safely determined for the first time. A comparison of advantages and limitations of the two methods of analysis is also presented.</style></abstract><accession-num><style face="normal" font="default" size="100%">15624901</style></accession-num><notes><style face="normal" font="default" size="100%">From Duplicate 2 (Assignment of the Absolute Configuration of (+)-Diplopyrone, the Main Phytotoxin Produced by Diplodia mutila, the Pathogen of the Cork Oak Decline, by a Nonempirical Analysis of Its Chiroptical Properties† - Giorgio, Egidio; Maddau, Lucia; Spanu, Emanuela; Evidente, Antonio; Rosini, Carlo)</style></notes><research-notes><style face="normal" font="default" size="100%">From Duplicate 2 (Assignment of the Absolute Configuration of (+)-Diplopyrone, the Main Phytotoxin Produced by Diplodia mutila, the Pathogen of the Cork Oak Decline, by a Nonempirical Analysis of Its Chiroptical Properties† - Giorgio, Egidio; Maddau, Lucia; Spanu, Emanuela; Evidente, Antonio; Rosini, Carlo)</style></research-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%">Belahbib, N</style></author><author><style face="normal" font="default" size="100%">Pemonge, M.-H. H</style></author><author><style face="normal" font="default" size="100%">Ouassou, A</style></author><author><style face="normal" font="default" size="100%">Sbay, H</style></author><author><style face="normal" font="default" size="100%">Kremer, A</style></author><author><style face="normal" font="default" size="100%">Petit, R J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Frequent cytoplasmic exchanges between oak species that are not closely related: Quercus suber and Q. ilex in Morocco</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Ecology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chloroplast</style></keyword><keyword><style  face="normal" font="default" size="100%">Chloroplast: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">cpDNA</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">geographical structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">introgression</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Morocco</style></keyword><keyword><style  face="normal" font="default" size="100%">mtDNA</style></keyword><keyword><style  face="normal" font="default" size="100%">PCR–RFLP</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><publisher><style face="normal" font="default" size="100%">Blackwell Science Ltd</style></publisher><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">2003-2012</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Chloroplast (cp) and mitochondrial (mt) DNA variation were studied in 97 populations of cork oak (Quercus suber) in Morocco; in 31 of these populations, holm oak (Quercus ilex), a clearly distinct species, also occurred and was compared with Q. suber. Three cpDNA and one mtDNA primer pairs were used in the survey, each in combination with one restriction enzyme. Six haplotypes belonging to two very divergent lineages were detected; one lineage predominates in each species, and is probably ancestral, as inferred from comparisons with other oak species. In the mixed-species populations, cytoplasmic genomes were frequently shared across species, as indicated by an introgression ratio of 0.63. This index is a new measure of the propensity of species to share locally genetic markers, varying from zero (complete differentiation) to one (no differentiation). By contrast, more closely related deciduous oak species (Q. robur, Q. petraea and Q. pubescens) have introgression ratios varying from 0.82 to 0.97. The introgression events appear to have been more frequent in the direction Q. ilex (female) × Q. suber (male), a finding which seems attributable to the flowering phenology of these two species. This asymmetry may have favoured immigration of Q. suber beyond its main range, in regions already colonized by Q. ilex. There, rare hybridization and further introgression through long distance pollen flow have established populations that are morphologically indistinguishable from Q. suber but that have cytoplasmic genomes originating from the local Q. ilex populations.</style></abstract><accession-num><style face="normal" font="default" size="100%">11555243</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%">Belahbib, N.</style></author><author><style face="normal" font="default" size="100%">Pemonge, M.-H. H.</style></author><author><style face="normal" font="default" size="100%">Ouassou, A.</style></author><author><style face="normal" font="default" size="100%">Sbay, H.</style></author><author><style face="normal" font="default" size="100%">Kremer, A.</style></author><author><style face="normal" font="default" size="100%">Petit, R. J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Frequent cytoplasmic exchanges between oak species that are not closely related: Quercus suber and Q. ilex in Morocco</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Ecology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chloroplast</style></keyword><keyword><style  face="normal" font="default" size="100%">Chloroplast: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">cpDNA</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">geographical structure</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">introgression</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Morocco</style></keyword><keyword><style  face="normal" font="default" size="100%">mtDNA</style></keyword><keyword><style  face="normal" font="default" size="100%">PCR–RFLP</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus</style></keyword><keyword><style  face="normal" font="default" size="100%">Quercus: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees</style></keyword><keyword><style  face="normal" font="default" size="100%">Trees: genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2001///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/11555243http://dx.doi.org/10.1046/j.0962-1083.2001.01330.x</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">2003 - 2012</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Chloroplast (cp) and mitochondrial (mt) DNA variation were studied in 97 populations of cork oak (Quercus suber) in Morocco; in 31 of these populations, holm oak (Quercus ilex), a clearly distinct species, also occurred and was compared with Q. suber. Three cpDNA and one mtDNA primer pairs were used in the survey, each in combination with one restriction enzyme. Six haplotypes belonging to two very divergent lineages were detected; one lineage predominates in each species, and is probably ancestral, as inferred from comparisons with other oak species. In the mixed-species populations, cytoplasmic genomes were frequently shared across species, as indicated by an introgression ratio of 0.63. This index is a new measure of the propensity of species to share locally genetic markers, varying from zero (complete differentiation) to one (no differentiation). By contrast, more closely related deciduous oak species (Q. robur, Q. petraea and Q. pubescens) have introgression ratios varying from 0.82 to 0.97. The introgression events appear to have been more frequent in the direction Q. ilex (female) × Q. suber (male), a finding which seems attributable to the flowering phenology of these two species. This asymmetry may have favoured immigration of Q. suber beyond its main range, in regions already colonized by Q. ilex. There, rare hybridization and further introgression through long distance pollen flow have established populations that are morphologically indistinguishable from Q. suber but that have cytoplasmic genomes originating from the local Q. ilex populations.</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;publisher: Blackwell Science Ltd&lt;br/&gt;accession-num: 11555243</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%">Peco, B</style></author><author><style face="normal" font="default" size="100%">Espigares, T</style></author><author><style face="normal" font="default" size="100%">Levassor, C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Trends and fluctuations in species abundance and richness in Mediterranean annual pastures</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Vegetation Science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autumn rainfall distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">Generalized Linear</style></keyword><keyword><style  face="normal" font="default" size="100%">Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Post-ploughing succession</style></keyword><keyword><style  face="normal" font="default" size="100%">Topography</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">21-28</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Floristic data collected from permanent plots during 14 consecutive years are used to model the frequency of the 62 most abundant species in relation to post-ploughing succession, topography and rainfall in annual Mediterranean grasslands located in a Quercus rotundifolia dehesa. The interannual dynamics of species richness are also analysed. From 1980 to 1993, presence/absence data of grassland species were noted in five 20 cm × 20 cm permanent quadrats placed at random in 1980 in 14 permanent plots on a southfacing slope along the topographic gradient. Weekly autumn rainfall data over the 14 years were analysed using a profile attributes index and Hybrid Multidimensional Scaling to arrange the years according to their autumn rainfall pattern. Generalized Linear Models were used to fit the species richness and species frequency according to topographic position, age since the last ploughing episode, total rainfall in the growing season and autumn rainfall pattern using a forward stepwise procedure. The richness model includes all of these variables, and reveals a relatively high goodness-of-fit (71%). The fact that the meteorological factors play a key role in modelling richness forces us to include them if we wish to use richness as an indicator of the degree of disturbance in these highly fluctuating annual pastures. Models of species dynamics show that although roughly 33% of the species have a successional behaviour, the majority are more dependent on temporal heterogeneity associated with rainfall or spatial heterogeneity linked to the topographic gradient.</style></abstract></record></records></xml>