<?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></contributors><titles><title><style face="normal" font="default" size="100%">A method for climate and vegetation reconstruction through the inversion of a dynamic vegetation model</style></title><secondary-title><style face="normal" font="default" size="100%">Climate Dynamics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">371-389</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Climate reconstructions from data sensitive to past climates provide estimates of what these climates were like. Comparing these reconstructions with simulations from climate models allows to validate the models used for future climate prediction. It has been shown that for fossil pollen data, gaining estimates by inverting a vegetation model allows inclusion of past changes in carbon dioxide values. As a new generation of dynamic vegetation model is available we have developed an inversion method for one model, LPJ-GUESS. When this novel method is used with high-resolution sediment it allows us to bypass the classic assumptions of (1) climate and pollen independence between samples and (2) equilibrium between the vegetation, represented as pollen, and climate. Our dynamic inversion method is based on a statistical model to describe the links among climate, simulated vegetation and pollen samples. The inversion is realised thanks to a particle ﬁlter algorithm. We perform a validation on 30 modern European sites and then apply the method to the sediment core of Meerfelder Maar (Germany), which covers the Holocene at a temporal resolution of approximately one sample per 30 years. We demonstrate that reconstructed temperatures are constrained. The reconstructed precipitation is less well constrained, due to the dimension considered (one precipitation by season), and the low sensitivity of LPJ-GUESS to precipitation changes.</style></abstract></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%">Quantifying components of risk for European woody species under climate change</style></title><secondary-title><style face="normal" font="default" size="100%">Global Change Biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><publisher><style face="normal" font="default" size="100%">Blackwell Publishing Ltd</style></publisher><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">1788-1799</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Estimates of species extinction risk under climate change are generally based on differences in present and future climatically suitable areas. However, the locations of potentially suitable future environments (affecting establishment success), and the degree of climatic suitability in already occupied and new locations (affecting population viability) may be equally important determinants of risk. A species considered to be at low risk because its future distribution is predicted to be large, may actually be at high risk if these areas are out of reach, given the species' dispersal and migration rates or if all future suitable locations are only marginally suitable and the species is unlikely to build viable populations in competition with other species. Using bioclimatic models of 17 representative European woody species, we expand on current ways of risk assessment and suggest additional measures based on (a) the distance between presently occupied areas and areas predicted to be climatically suitable in the future and (b) the degree of change in climatic suitability in presently occupied and unoccupied locations. Species of boreal and temperate deciduous forests are predicted to face higher risk from loss of climatically suitable area than species from warmer and drier parts of Europe by 2095 using both the moderate B1 and the severe A1FI emission scenario. However, the average distance from currently occupied locations to areas predicted suitable in the future is generally shorter for boreal species than for southern species. Areas currently occupied will become more suitable for boreal and temperate species than for Mediterranean species whereas new suitable areas outside a species' current range are expected to show greater increases in suitability for Mediterranean species than for boreal and temperate species. Such additional risk measures can be easily derived and should give a more comprehensive picture of the risk species are likely to face under climate change.</style></abstract></record></records></xml>