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Can decision rules simulate carbon allocation for years with contrasting and extreme weather conditions? A case study for three temperate beech forests

机译:决策规则可以模拟多年来在极端气候条件下的碳分配吗?以三个温带山毛榉森林为例

摘要

The allocation of carbohydrates to different tree processes and organs is crucial to understand the overall carbon (C) cycling rate in forest ecosystems. Decision rules (DR) (e.g. functional balances and source-sink relationships) are widely used to model C allocation in forests. However, standard DR allocation schemes lack a strong environmental sensitivity and their ability to simulate the year-to-year variability and the impact of extreme events is questioned. In this study, we aimed to compare the performance of a standard DR allocation scheme to the performance of an improved DR allocation scheme taking into account drought-induced changes in allocation dynamics and acclimation of respiration. Model validation was performed against extensive datasets of C fluxes and C pools for a 9 years period (2000-2008) for the site of parameterisation (the beech forest of Hesse, France) and for two contrasting sites not used for parameterisation (the beech forest of Soro, Denmark, for 1999-2006, and Collelongo, Italy, for 2005-2006). At Hesse, 2003 was characterised by a severe and extreme drought and heat wave. The standard DR allocation scheme captured the average annual dynamics of C allocation and wood growth at beech stands with contrasting climate and standing stock. However, the allocation model required high quality GPP input and errors (even modest) in GPP resulted in large errors in the growth of the tree organs lowest in the modelled sink hierarchy (woody organs). The ability of the standard DR allocation model to simulate year-to-year variability was limited. The amended DR allocation scheme improved the annual simulations and allowed capturing the stand growth dynamics at Hesse during the extreme 2003 summer and its important lag effect on next year's wood production. Modelling of drought-induced changes in fine root dynamics and of short-term thermal acclimation of maintenance respiration should not be overlooked when simulating the C cycle of forests, particularly for sites likely to experience extreme drought and heat waves. The most relevant model bias was the inaccurate estimation of leaf biomass production (up to 15%) and a poor description of its interannual variability. Future studies should focus primarily on this limitation. (C) 2013 Elsevier B.V. All rights reserved.
机译:将碳水化合物分配给不同的树木过程和器官对于了解森林生态系统中的总体碳(C)循环速率至关重要。决策规则(DR)(例如功能平衡和源库关系)被广泛用于对森林中的C分配进行建模。但是,标准的DR分配方案缺乏强烈的环境敏感性,并且它们无法模拟逐年变化和极端事件的影响。在这项研究中,我们旨在比较标准的DR分配方案的性能与改进的DR分配方案的性能,其中考虑了干旱引起的分配动态变化和呼吸适应。针对参数化站点(法国黑森州的山毛榉森林)和两个未用于参数化的对比站点(山毛榉森林),针对9年期间(2000-2008年)的大量C通量和C池数据集进行了模型验证分别是1999-2006年的丹麦索罗市和2005-2006年的意大利科勒隆戈市)。在黑森州,2003年的特点是严重的极端干旱和热浪。标准的DR分配方案记录了山毛榉林中C分配和木材生长的年均动态,以及气候和林分存量的差异。但是,分配模型需要高质量的GPP输入,并且GPP中的错误(即使适度)也导致了在建模的接收器层次结构(木质器官)中最低的树形器官的生长出现较大的错误。标准DR分配模型模拟逐年变化的能力受到限制。修改后的DR分配方案改进了年度模拟,并允许捕获2003年夏季极端期间黑森州林分生长的动态及其对明年木材产量的重要滞后效应。在模拟森林的碳循环时,尤其是对于那些可能遭受极端干旱和热浪袭击的地点,不应忽略干旱引起的细根动态变化和维持呼吸的短期热适应模型。最相关的模型偏差是叶片生物量产量的估算不准确(高达15%),并且其年际变化的描述不充分。未来的研究应主要关注这一局限性。 (C)2013 Elsevier B.V.保留所有权利。

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