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态响应和反馈是一项挑战，需要开发模型和数据集。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型（GCM）的输出，逆模拟古植被数据，传递函数和模拟方法将被用来生成独立的套古气候重建。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。四个DVM的性能将在反向和正常模式下进行比较。这种并行使用的方法，数据和模型将允许评估的鲁棒性的古气候和古植被重建，并帮助确定在哪里需要进一步的模型开发。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发挥欧洲古植被数据集在古气候研究中的价值。利用DVM探索过去的情景将有助于模型的发展，并使它们成为更有效的工具，用于预测未来的生态系统响应植被多样性，气候变化的迁移反应，碳循环和水文的变化。

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.