Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change
Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change
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DOI：
10.1111/j.1469-8137.2010.03350.x
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发表时间：
2010-01-01
期刊：
影响因子：
9.4
通讯作者：
Meir, Patrick
中科院分区：
文献类型：
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作者：
Galbraith, David;Levy, Peter E.;Meir, Patrick
在某些未来气候情景下，亚马逊雨林的大规模损失通常被认为是由某些大气环流模式（GCM）预测的亚马逊地区干旱增加所驱动的。然而，降雨相对于其他驱动因素的重要性从未被正式研究过。在这里，我们进行了因子模拟，以确定四个环境驱动因素的贡献（降水、温度、湿度和CO2）与亚马逊植被碳（C-veg）的模拟变化，在三个动态全球植被模型（DGVM）中，在两个DGVM中，温度升高比降水减少更重要地导致亚马逊河流域C-veg的损失（Hyland和TRIFFID），并作为重要的降水减少在第三DGVM（LPJ）。植物呼吸作用的增加、光合作用的直接下降和水汽压亏缺（VPD）的增加都有助于高温下C-veg的减少，但每个机制的贡献在不同模型中差异很大。在模型中，CO2的上升减轻了气候驱动的生物量损失，需要开展更多的工作，用高温和干旱条件下的实验数据约束模型行为。目前的模型可能对长期高温过于敏感，因为它们没有考虑生理适应。
P>The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined.Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO2) to simulated changes in Amazonian vegetation carbon (C-veg), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios.Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C-veg in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C-veg under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO2 mitigated much of the climate-driven biomass losses in the models.Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.