<?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%">Correia, a C. C.</style></author><author><style face="normal" font="default" size="100%">Minunno, F.</style></author><author><style face="normal" font="default" size="100%">Caldeira, M. C. C.</style></author><author><style face="normal" font="default" size="100%">Banza, J.</style></author><author><style face="normal" font="default" size="100%">Mateus, J.</style></author><author><style face="normal" font="default" size="100%">Carneiro, M.</style></author><author><style face="normal" font="default" size="100%">Wingate, L.</style></author><author><style face="normal" font="default" size="100%">Shvaleva, a</style></author><author><style face="normal" font="default" size="100%">Ramos, a</style></author><author><style face="normal" font="default" size="100%">Jongen, M.</style></author><author><style face="normal" font="default" size="100%">Bugalho, M. N. N.</style></author><author><style face="normal" font="default" size="100%">Nogueira, C.</style></author><author><style face="normal" font="default" size="100%">Lecomte, X.</style></author><author><style face="normal" font="default" size="100%">Pereira, J. S. S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Soil water availability strongly modulates soil CO2 efflux in different Mediterranean ecosystems: Model calibration using the Bayesian approach</style></title><secondary-title><style face="normal" font="default" size="100%">Agriculture, Ecosystems &amp; Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bayesian calibration</style></keyword><keyword><style  face="normal" font="default" size="100%">Empirical model</style></keyword><keyword><style  face="normal" font="default" size="100%">Mediterranean</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil CO2 efﬂux</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil moisture</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil respiration</style></keyword><keyword><style  face="normal" font="default" size="100%">Soil temperature</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://linkinghub.elsevier.com/retrieve/pii/S016788091200285X</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">161</style></volume><pages><style face="normal" font="default" size="100%">88 - 100</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Soil respiration in drought prone regions is highly dependent on the precipitation regime and soil moisture conditions, which are expected to change in a global warming context. In the present study we used an extensive collection of ﬁeld chamber measurements of soil respiration (Rs ) from forest and grassland sites of centre and south of Portugal distributed over a 10 year period. This data were summarized and analysed with the objective to describe seasonal variability of Rs as affected by soil moisture (Hs ) and soil temperature (Ts ). A Bayesian framework was used to test the effectiveness of soil bioclimatic models in estimating Rs on a daily and monthly time step. Rs seasonality was similar between sites, reaching a maximum in spring and autumn and a minimum in the dry season (July–September). No differences were observed for Rs between sites with different standing biomass or soil carbon stocks either on an annual or seasonal timescale. Hs , and not Ts , was the driving factor of Rs during most of the year. Ts drove Rs response only above certain Hs limits: 10% for forest sites and 15% for grassland sites leading to a Q10 of 2.01, 1.61 and 1.31 for closed forests, open forests and grasslands, respectively. The Bayesian analysis showed that models using Hs as an independent variable performed better than models driven by Ts alone. Monthly estimates of Rs in grasslands can be predicted by simple climatic models based on Hs but none of them was suitable for forest ecosystems, stressing the need for a process-based approach. This study adds to the evidence that Hs controls Rs ﬂuxes for Mediterranean ecosystems and should always be taken into account for extrapolation purposes.</style></abstract><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><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment and up-scaling of CO2 exchange by patches of the herbaceous vegetation mosaic in a Portuguese cork oak woodland</style></title><secondary-title><style face="normal" font="default" size="100%">Agricultural and Forest Meteorology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://linkinghub.elsevier.com/retrieve/pii/S0168192308000981</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">148</style></volume><pages><style face="normal" font="default" size="100%">1318 - 1331</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Long-term eddy covariance measurements over a montado oak woodland in southern Portugal have documented a vulnerability to predicted decreases in springtime rainfall, since water availability during spring limits annual CO2 gain, the growth of fodder for animals, and the production of cork by Quercus suber. The current study examined CO2 exchange of three different herbaceous vegetation components distributed over montado landscapes and within the footprint of long-term landscape eddy covariance monitoring studies. Simultaneous measurements with eddy covariance at two sites and with manually operated chambers at multiple locations revealed that slow drainage of shallow basins, the onset of drying at higher sites and a high release of CO2 below tree canopies signiﬁcantly inﬂuenced the overall course of montado ecosystem gas exchange during the spring. Hyperbolic light response models were employed to up-scale and compare herbaceous gas exchange with landscape net ecosystem CO2 ﬂux. The up-scaling demonstrates the importance of the herbaceous understory in determining annual carbon balance of the montado and suggests a relatively small additional CO2 uptake by the tree canopies and boles, i.e., by the aboveground tree compartment, during springtime. Annual ﬂux totals obtained during the extremely dry year 2005 and a normal precipitation year 2006 for the oak woodland and a nearby grassland were essentially the same, indicating that both ecosystems similarly exploit available resources. Based on comparisons with additional temperate grasslands, we can visualize the montado herbaceous cover as a typical European grassland canopy, but where temperature ﬂuctuations in winter control uptake, and where total production depends on springtime rainfall as it controls phenological events and eventually dieback of the vegetation. On the other hand, tree canopies remain active longer during late spring and early summer, modifying the montado response from that of grassland. Uncertainties in ﬂux estimates via both chamber and eddy covariance methodologies currently prevent a full understanding of vegetation/atmosphere coupling, of the recycling of CO2 between the understory communities and trees, and of relationships between exchange rates of individual components of the vegetation mosaic and overall carbon and water balances in montado landscapes.</style></abstract><issue><style face="normal" font="default" size="100%">8-9</style></issue></record></records></xml>