文章基本信息

标题：Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
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作者：K Sakaguchi ; X Zeng ; LR Leung 等
期刊名称：Environmental Research Letters
印刷版ISSN：1748-9326
电子版ISSN：1748-9326
出版年度：2016
卷号：11
期号：12
页码：124029
DOI：10.1088/1748-9326/aa51d9
语种：English
出版社：IOP Publishing Ltd
摘要：Land carbon sensitivity to atmospheric CO₂ concentration (β_L) and climate warming (γ_L) is a crucial part of carbon-climate feedbacks that affect the magnitude of future warming. Although these sensitivities can be estimated by earth system models, their dependence on model representation of land carbon dynamics and the inherent model assumptions has rarely been investigated. Using the widely used Community Land Model version 4 as an example, we examine how β_L and γ_L vary with prescribed versus dynamic vegetation covers. Both sensitivities are found to be larger with dynamic compared to prescribed vegetation on decadal timescale in the late twentieth century, with a more robust difference in γ_L. The latter is a result of dynamic vegetation model deficiencies in representing the competitions between deciduous versus evergreen trees and tree versus grass over the tropics and subtropics. The biased vegetation cover changes the regional characteristics of carbon-nitrogen cycles such that plant productivity responds less strongly to the enhancement of nitrogen mineralization with warming, so more carbon is lost to the atmosphere with rising temperature. The result calls for systematic evaluations of land carbon sensitivities with varying assumptions for land cover representations to help prioritize development effort and constrain uncertainties in carbon-climate feedbacks.