Largely underestimated carbon emission from land use and land cover change in the conterminous United States
Largely underestimated carbon emission from land use and land cover change in the conterminous United States
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DOI：
10.1111/gcb.14768
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发表时间：
2019-08
影响因子：
11.6
通讯作者：
Zhen Yu;Chaoqun Lu;H. Tian;J. Canadell
中科院分区：
文献类型：
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作者：
Zhen Yu;Chaoqun Lu;H. Tian;J. Canadell
由于土地利用和土地覆盖变化（LULCC）引起的碳(C)排放和吸收是全球碳预算中最不确定的术语，这主要是由于LULCC数据有限和模型能力不足（例如，农业管理代表性不足）。我们采用常用的基于FAOSTAT的全球土地利用协调数据（LUH2）和一个新的高分辨率多源协调国家土地利用协调数据库（YLmap）来驱动美国邻近地区的土地生态系统模型（DLEM）。我们发现，来自国家统计数据的LUH2数据可能高估了近期的耕地撂荒和森林恢复，导致之前报告的土地利用碳排放被低估，原因是耕地的定义和汇总的LULCC信号都是粗分辨率的。这种高估导致1980-2016年期间LUH2在美国驱动的模式模拟中有很强的碳汇（30.3±2.5 Tg C/年），而我们在使用YLmap时发现了中等的碳源（13.6±3.5 Tg C/年）。这一差异意味着，以往基于全球LUH2数据集的碳预算分析低估了美国的碳排放，这是因为YLmap克服了在粗分辨率下圈定合适的农田和汇总的土地转换信号。因此，为了更准确地量化LULCC引起的碳排放并更好地服务于全球碳预算核算，迫切需要开发精细尺度的国家特定LULCC数据来表征土地利用的细节。
Carbon (C) emission and uptake due to land use and land cover change (LULCC) are the most uncertain term in the global carbon budget primarily due to limited LULCC data and inadequate model capability (e.g., underrepresented agricultural managements). We take the commonly used FAOSTAT‐based global Land Use Harmonization data (LUH2) and a new high‐resolution multisource harmonized national LULCC database (YLmap) to drive a land ecosystem model (DLEM) in the conterminous United States. We found that recent cropland abandonment and forest recovery may have been overestimated in the LUH2 data derived from national statistics, causing previously reported C emissions from land use have been underestimated due to the definition of cropland and aggregated LULCC signals at coarse resolution. This overestimation leads to a strong C sink (30.3 ± 2.5 Tg C/year) in model simulations driven by LUH2 in the United States during the 1980–2016 period, while we find a moderate C source (13.6 ± 3.5 Tg C/year) when using YLmap. This divergence implies that previous C budget analyses based on the global LUH2 dataset have underestimated C emission in the United States owing to the delineation of suitable cropland and aggregated land conversion signals at coarse resolution which YLmap overcomes. Thus, to obtain more accurate quantification of LULCC‐induced C emission and better serve global C budget accounting, it is urgently needed to develop fine‐scale country‐specific LULCC data to characterize the details of land conversion.