Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America
Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America
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DOI：
10.1002/2017gl075922
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发表时间：
2018-01
影响因子：
5.2
通讯作者：
W. Smith;J. Biederman;R. Scott;David J. P. Moore;M. He;J. Kimball;Dong Yan;A. Hudson;M. Barnes;N. MacBean;A. Fox;M. Litvak
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文献类型：
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作者：
W. Smith;J. Biederman;R. Scott;David J. P. Moore;M. He;J. Kimball;Dong Yan;A. Hudson;M. Barnes;N. MacBean;A. Fox;M. Litvak
卫星遥感提供了无与伦比的关于植被总初级生产力的时空信息。然而，对全球初级生产力与遥感观测之间的关系及其如何随尺度、生物物理约束和植被类型等因素而变化的理解仍然有限。这一知识差距在旱地生态系统中尤为明显，因为旱地生态系统具有高度时空变异性的特点，而且长期实地测量结果对旱地生态系统的反映不足。在这里，我们利用北美西南部的涡度协方差（EC）数据合成，评估卫星衍生的植被代理如何准确地捕获跨旱地梯度的季节到年际GPP动态。我们评估了增强植被指数，太阳诱导荧光（SIF）和光化学反射率指数。我们发现的证据表明，SIF是更准确地捕捉季节性GPP动态，特别是万年青为主的EC网站和更准确地估计所有旱地EC网站的年际GPP动态的全部幅度。这些结果表明，纳入SIF可以显着改善基于卫星的GPP估计。
Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under‐represented by long‐term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite‐derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar‐induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen‐dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. These results suggest that incorporation of SIF could significantly improve satellite‐based GPP estimates.