Extending the use of ecological models without sacrificing details: a generic and parsimonious meta-modelling approach

Process-based models (PBMs, see table 1 for a list of abbreviations) are essential tools to assess ecosystem response to climate change, land use changes, extreme weather patterns, or other environmental disturbances. PBMs allow to deal with the high level of interactions and feedbacks which are intrinsic to ecological processes, but their complexity comes at the cost of computation time and memory. Because of that, there is a trade-off between the resolution satisfactory to describe ecological processes (e.g. organism, population, species, vegetation type …), and the computing constraints when applying PBMs at a large spatial extent and/or long time periods.

基于过程的模型（Process-based Models，PBMs，缩写列表详见表1）是评估生态系统对气候变化、土地利用变化、极端天气模式或其他环境扰动响应的核心工具。此类模型能够处理生态过程固有的高度复杂的相互作用与反馈机制，但其复杂性也以计算时长与内存占用为代价。正因如此，在能够满足生态过程描述需求的空间分辨率（例如生物体、种群、物种、植被类型……），与在大空间尺度和/或长时间跨度下运行基于过程的模型时所面临的计算约束之间，存在权衡取舍。