Photosynthesis by terrestrial plants represents the majority of CO₂ uptake on Earth, yet it is difficult to measure directly from space. Estimation of gross primary production (GPP) from remote sensing indices represents a primary source of uncertainty, in particular for observing seasonal variations in evergreen forests. Recent vegetation remote sensing techniques have highlighted spectral regions sensitive to dynamic changes in leaf/needle carotenoid composition, showing promise for tracking seasonal changes in photosynthesis of evergreen forests. However, these have mostly been investigated with intermittent field campaigns or with narrow-band spectrometers in these ecosystems. To investigate this potential, we continuously measured vegetation reflectance (400–900 nm) using a canopy spectrometer system, PhotoSpec, mounted on top of an eddy-covariance flux tower in a subalpine evergreen forest at Niwot Ridge, Colorado, USA. We analyzed driving spectral components in the measured canopy reflectance using both statistical and process-based approaches. The decomposed spectral components co-varied with carotenoid content and GPP, supporting the interpretation of the photochemical reflectance index (PRI) and the chlorophyll/carotenoid index (CCI). Although the entire 400–900 nm range showed additional spectral changes near the red edge, it did not provide significant improvements in GPP predictions. We found little seasonal variation in both normalized difference vegetation index (NDVI) and the near-infrared vegetation index (NIRv) in this ecosystem. In addition, we quantitatively determined needle-scale chlorophyll-to-carotenoid ratios as well as anthocyanin contents using full-spectrum inversions, both of which were tightly correlated with seasonal GPP changes. Reconstructing GPP from vegetation reflectance using partial least-squares regression (PLSR) explained approximately 87 % of the variability in observed GPP. Our results linked the seasonal variation in reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests.

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分解反射光谱以跟踪亚高山常绿森林的总初级生产力

陆地植物的光合作用占CO ₂的大部分对地球的吸收，但是很难直接从太空进行测量。根据遥感指数估算的初级总产值（GPP）是不确定性的主要来源，尤其是对于观察常绿森林的季节变化而言。最近的植被遥感技术已经强调了对叶/针类胡萝卜素成分的动态变化敏感的光谱区域，这显示了跟踪常绿森林光合作用的季节性变化的希望。但是，在这些生态系统中，大多数是通过间歇性野外运动或使用窄带光谱仪进行调查的。为了研究这种潜力，我们使用冠层光谱仪系统PhotoSpec连续测量了植被反射率（400-900 nm），该系统安装在Niwot Ridge亚高山常绿森林的涡度-协方差通量塔顶部，美国科罗拉多州。我们使用统计方法和基于过程的方法分析了测得的树冠反射率中的驱动光谱成分。分解后的光谱成分与类胡萝卜素含量和GPP共变，支持对光化学反射指数（PRI）和叶绿素/类胡萝卜素指数（CCI）的解释。尽管整个400-900 nm范围在红边附近都显示了其他光谱变化，但它并未在GPP预测中提供显着改善。我们发现该生态系统中的归一化植被指数（NDVI）和近红外植被指数（NIRv）几乎没有季节性变化。此外，我们使用全光谱反演来定量测定针状叶绿素与类胡萝卜素的比例以及花青素含量，两者均与季节性GPP变化紧密相关。使用偏最小二乘回归（PLSR）从植被反射率重建GPP可以解释观察到的GPP中大约87％的可变性。我们的结果将反射率的季节性变化与光防护性颜料池的大小相关联， 强调常绿森林中与GPP季节性相关的400-900 nm范围内的所有光谱位置。