Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic.
Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic.
Sci Total Environ. 2022 Jul 10;829:154681. doi: 10.1016/j.scitotenv.2022.154681. Epub 2022 Mar 18.
We used automated spectroradiometers to continuously monitor changes in the optical parameters of phenological and photosynthetic traits in beech and spruce forests. We examined seasonal variations in the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and solar-induced fluorescence in the oxygen A band (SIFA) that was estimated using a 3-FLD discrimination method from radiance data. The optical parameters tracked the activation and cessation of photosynthesis in spring and autumn. Data at photon fluxes >1200 μmol m s during extended noon hours were used to link the seasonal PRI and SIFA variations to the dynamics of photosynthesis. Seasonal PRI was significantly correlated with photosynthetic light-use efficiency (LUE) with R values of 0.66 and 0.48 for the measurements in beech and spruce forests, respectively. SIFA emissions were significantly correlated with the gross primary production (GPP) of the evergreen spruce forest (R = 0.47), but R was only 0.13 when measured in the beech forest. The correlations between the optical parameters and GPP or LUE, however, tended to be lower when using a dataset with constant NDVI. Introducing an equation combining NDVI, PRI, and the quantum yield of SIFA emission increased R for LUE estimation to 0.77 in the spruce forest and 0.63 in the beech forest. GPP was estimated from the parametric equation with improved accuracy reaching R = 0.53 and RMSE = 5.95 μmol CO m s in spruce forest and R = 0.58 and RMSE = 5.23 μmol CO m s in beech forest. Parametric equations were more efficient in estimating photosynthesis in datasets that consisted of an entire season's data. By combining NDVI, PRI and the quantum yield of SIFA, we could thus substantially improve estimations of carbon fluxes in diverse deciduous and evergreen canopies.
我们使用自动化光谱辐射计连续监测物候和光合作用特征的光学参数在山毛榉和云杉林中的变化。我们研究了归一化差异植被指数（NDVI）、光化学反射指数（PRI）和使用 3-FLD 判别方法从辐射数据估算的氧 A 带太阳诱导荧光（SIFA）的季节性变化。这些光学参数跟踪了春、秋两季光合作用的启动和停止。在长时间中午时段使用大于 1200 μmol m s 的光子通量数据将季节 PRI 和 SIFA 变化与光合作用动态联系起来。季节 PRI 与光合作用光利用效率（LUE）显著相关，山毛榉林和云杉林的 R 值分别为 0.66 和 0.48。SIFA 发射与常绿云杉林的总初级生产力（GPP）显著相关（R = 0.47），但在山毛榉林中测量时 R 仅为 0.13。然而，当使用具有恒定 NDVI 的数据集时，光学参数与 GPP 或 LUE 的相关性往往较低。引入一个结合 NDVI、PRI 和 SIFA 发射量子产率的方程，将云杉林的 LUE 估计 R 值提高到 0.77，山毛榉林的 R 值提高到 0.63。通过参数方程估算 GPP 的精度得到提高，在云杉林中 R 值为 0.53，RMSE = 5.95 μmol CO m s，在山毛榉林中 R 值为 0.58，RMSE = 5.23 μmol CO m s。参数方程在包含整个季节数据的数据集估算光合作用方面效率更高。通过结合 NDVI、PRI 和 SIFA 的量子产率，我们可以大大提高对不同落叶和常绿树冠碳通量的估算。
