FP 04: Dynamic European Climate-Vegetation Impact and Interactions (DECVEG)

理解和预测陆地植被对气候变化的瞬时反应和反馈是需要开发模型和数据集的挑战。八个研究小组将使用和改进动态植被模型(DVM)和古植被数据，以研究欧洲的气候-植被相互作用。现有的和新的大气环流模式(GCM)输出、古植被数据的逆模拟、传递函数和类比方法将被用来产生独立的古气候重建集。DVM将由GCM古气候数据驱动，并将其输出与古生态数据集进行比较。我们将比较四个DVM在反向模式和正常模式下的性能。这种方法、数据和模型的并行使用将有助于评估古气候和古植被重建的稳健性，并有助于确定需要进一步开发模型的地方。将进行一系列新的GCM-DVM耦合模拟。一个中心目标是最大限度地提高欧洲古植被数据集在古气候研究中的价值。使用DVM探索过去的情景将有助于模型的开发，并使其成为预测未来生态系统对植被多样性、对气候变化的迁徙反应、碳循环和水文学变化的反应的更有效工具。

Understanding and predicting transient terrestrial vegetation responses and feedbacks to climate change are challenges that require development of both models and datasets. Eight research groups will use and improve both dynamic vegetation models (DVMs) and paleovegetation data in order to study climate-vegetation interactions in Europe. Existing and new general circulation model (GCM) output, inverse modelling of paleovegetation data, transfer functions and the analogue approach will be used to generate independent sets of paleoclimatic reconstructions. DVMs will be driven by GCM palaeoclimatic data, and their output compared with palaeoecological datasets. Performance of four DVMs will be compared in both inverse and normal mode. This parallel use of methods, data and models will permit assessment of the robustness of the palaeoclimate and palaeovegetation reconstructions and help identify where further model development is needed. A new series of coupled GCM-DVM simulations will be made. A central aim is to maximise the value of European palaeovegetation datasets in palaeoclimate research. Using DVMs to explore past scenarios will contribute to model development and make them into more effective tools for predicting future ecosystem responses with regard to vegetation diversity, migrational response to climate change, alterations in carbon cycle and hydrology.