Predicting future ecosystems changes is necessary for better managing human resources. Such forecasting requires robust vegetation models which have been tested versus observed field data. Nowadays, it is very common that a simulation model is firstly validated using modern observed data and then tested versus palaeodata. In a sense, ecological data represent the natural laboratory for modelers. Thus, palaeo and actuo-ecological data are key points when dealing with predicting future changes. The present work represents the first step in such data-model comparison approach. Here, we use only modern plants distributions to test the robustness of our ecosystems definitions and use these definitions for testing a dynamic vegetation model. We have defined twenty-nine Bioclimatic affinity groups (BAGs) for 196 dominant plant species including trees, shrubs and herbs in China. These BAGs are characterized by the phenology and the climatic tolerances of the species they include. They are detailed enough to describe all vegetation types in China including the tropical, the subtropical, the temperate and the high altitude (Tibet Plateau) ecosystems. The climatic thresholds of these 29 BAGs were then used to test and validate a global dynamic vegetation model (CARAIB). The simulated BAGs are in good agreement with those observed in China, especially in the Tibetan Plateau and in the subtropical ecosystems. Broadly, all simulated BAGs fit quite well with the modern distribution. However, they all cover larger areas than the observed distributions, especially in the temperate region and in some areas in the northwest and the tropical zone. These discrepancies between simulated and observed distributions are related to the fact that the vegetation models simulate potential distributions. In China during recent decades natural ecosystems, mostly in the temperate zone, have been strongly altered in their species composition and geographical extent by different human activities such as the intense cultivation, deforestation, introduction of fast growing species and grazing.
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