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Parameter uncertainties in the modelling of vegetation dynamics - Effects on tree community structure and ecosystem functioning in European forest biomes

机译:植被动力学建模中的参数不确定性-对欧洲森林生物群落中树木群落结构和生态系统功能的影响

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Dynamic vegetation models are useful tools for analysing terrestrial ecosystem processes and their interactions with climate through variations in carbon and water exchange. Long-term changes in structure and composition (vegetation dynamics) caused by altered competitive strength between plant functional types (PFTs) are attracting increasing attention as controls on ecosystem functioning and potential feedbacks to climate. Imperfect process knowledge and limited observational data restrict the possibility to parameterise these processes adequately and potentially contribute to uncertainty in model results. This study addresses uncertainty among parameters scaling vegetation dynamic processes in a process-based ecosystem model, LPJ-GUESS, designed for regional-scale studies, with the objective to assess the extent to which this uncertainty propagates to additional uncertainty in the tree community structure (in terms of the tree functional types present and their relative abundance) and thus to ecosystem functioning (carbon storage and fluxes). The results clearly indicate that the uncertainties in parameterisation can lead to a shift in competitive balance, most strikingly among deciduous tree PFTs, with dominance of either shade-tolerant or shade-intolerant PFTs being possible, depending on the choice of plausible parameter values. Despite this uncertainty, our results indicate that the resulting effect on ecosystem functioning is low. Since the vegetation dynamics in LPJ-GUESS are representative for the more complex Earth system models now being applied within ecosystem and climate research, we assume that our findings will be of general relevance. We suggest that, in terms of carbon storage and fluxes, the heavier parameterisation requirement of the processes involved does not widen the overall uncertainty in model predictions.
机译:动态植被模型是用于分析陆地生态系统过程及其通过碳和水交换变化而与气候的相互作用的有用工具。由于对生态系统功能的控制和对气候的潜在反馈,植物功能类型(PFT)之间竞争强度的改变引起的结构和组成的长期变化(植被动态)正引起越来越多的关注。不完善的过程知识和有限的观测数据限制了对这些过程进行充分参数化的可能性,并可能导致模型结果的不确定性。这项研究解决了基于过程的生态系统模型LPJ-GUESS中参数缩放植被动态过程的不确定性,该模型旨在进行区域规模的研究,目的是评估这种不确定性在多大程度上传播到树木群落结构中的其他不确定性(就目前存在的树木功能类型及其相对丰度而言),进而对生态系统功能(碳储存和通量)而言。结果清楚地表明,参数设置中的不确定性可能导致竞争平衡发生变化,尤其是在落叶乔木PFT之间,根据可行的参数值的选择,耐荫性或耐荫性PFT可能占主导地位。尽管存在这种不确定性,我们的结果表明,对生态系统功能的最终影响很小。由于LPJ-GUESS中的植被动力学代表了目前正在生态系统和气候研究中应用的更复杂的地球系统模型,因此我们认为我们的发现将具有普遍意义。我们建议,就碳储存和通量而言,所涉及过程的较重参数化要求不会扩大模型预测中的总体不确定性。

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