Dominant role of soil moisture in mediating carbon and water fluxes in dryland ecosystems
Dominant role of soil moisture in mediating carbon and water fluxes in dryland ecosystems
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DOI：
10.1038/s41561-023-01351-8
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发表时间：
2024-01
影响因子：
18.3
通讯作者：
S. Kannenberg;W. Anderegg;M. Barnes;M. Dannenberg;Alan K. Knapp
中科院分区：
文献类型：
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作者：
S. Kannenberg;W. Anderegg;M. Barnes;M. Dannenberg;Alan K. Knapp
由于旱地在空间和时间上的巨大异质性，旱地对全球碳和水循环的年际变化有很大影响。生态系统通量的这种可变性对理解其主要驱动因素提出了挑战。在这里，我们量化的敏感性旱地总初级生产力和蒸散量的各种水文气象驱动程序合成涡度协方差数据，遥感产品和陆地表面模型输出在美国西部。我们发现，总初级生产力和蒸散量来自涡度协方差是最敏感的土壤水分波动，蒸汽压力赤字的敏感性较低，几乎没有空气温度或光照的敏感性。我们发现，遥感数据准确地捕捉涡动协方差通量土壤水分的敏感性，但在很大程度上过度预测的敏感性，大气驱动程序。相比之下，陆面模型低估了总初级生产力土壤水分波动的敏感性约45%。在不断变化的气候中增加蒸汽压赤字的作用的辩论中，我们得出结论，土壤水分是美国旱地碳-水通量的主要驱动力。因此，必须改进土壤水分限制的模型表述，并在遥感通量产品中更现实地表述大气驱动因素如何影响旱地植被。
Drylands exert a strong influence over global interannual variability in carbon and water cycling due to their substantial heterogeneity over space and time. This variability in ecosystem fluxes presents challenges for understanding their primary drivers. Here we quantify the sensitivity of dryland gross primary productivity and evapotranspiration to various hydrometeorological drivers by synthesizing eddy covariance data, remote sensing products and land surface model output across the western United States. We find that gross primary productivity and evapotranspiration derived from eddy covariance are most sensitive to soil moisture fluctuations, with lesser sensitivity to vapour pressure deficit and little to no sensitivity to air temperature or light. We find that remote sensing data accurately capture the sensitivity of eddy covariance fluxes to soil moisture but largely over-predict sensitivity to atmospheric drivers. In contrast, land surface models underestimate sensitivity of gross primary productivity to soil moisture fluctuations by approximately 45%. Amid debates about the role of increasing vapour pressure deficit in a changing climate, we conclude that soil moisture is the primary driver of US dryland carbon–water fluxes. It is thus imperative to both improve model representation of soil water limitation and more realistically represent how atmospheric drivers affect dryland vegetation in remotely sensed flux products.