College of Life and Environmental Sciences, University of Exeter, Exeter, UK
College of Life and Environmental Sciences, University of Exeter, Exeter, UK.
Philos Trans R Soc Lond B Biol Sci. 2018 Oct 8;373(1760):20170315. doi: 10.1098/rstb.2017.0315.
The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration () observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.
当前一代动态全球植被模型 (DGVM) 缺乏对植被对土壤干旱响应的机制表示，从而削弱了它们准确预测地球系统对未来气候情景和气候异常（如厄尔尼诺事件）的响应能力。我们提出了一种简单的数值方法来模拟植物对干旱的响应，该方法结合了气孔最优化理论和植物水力学，可以用于动态全球植被模型 (DGVM)。该模型通过长期土壤干旱实验中的林分尺度森林蒸腾观测进行了验证，并用于预测三个亚马逊森林站点对 20 世纪气候异常的响应。我们表明，我们的气孔最优化模型对环境条件产生了现实的气孔响应，并可以准确模拟热带森林如何对季节性甚至长期土壤干旱做出响应。我们的模型预测，在厄尔尼诺年份土壤干旱暴露的亚马逊森林站点中，气候异常的累积效应比替代经验性干旱表示方案更加强烈。我们的模型与经验性干旱因素之间的对比响应突出了基于水力的气孔最优化模型在 DGVM 中代表植被对干旱和气候异常的响应的实用性。本文是“2015/2016 年厄尔尼诺对热带陆地碳循环的影响：模式、机制和意义”讨论会议的一部分。
