Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests
Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests
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OCO-2 观测到的叶绿素荧光与温带森林通量塔估计的总初级生产力密切相关
DOI：
10.1016/j.rse.2017.09.034
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发表时间：
2018
影响因子：
13.5
通讯作者：
He Binbin
中科院分区：
文献类型：
--
作者：
Li Xing;Xiao Jingfeng;He Binbin
太阳诱导叶绿素荧光为从空间监测植被光合作用开辟了一个新的视角，最近已被用于估算总初级生产力。然而，以前的研究主要是基于温室气体观测卫星（GOSAT）和全球臭氧监测实验-2（GOME-2）的卫星观测，这些粗分辨率的SIF测量使用GPP来自涡度协方差（EC）通量塔的评估一直受到卫星和塔足迹之间的尺度不匹配。我们使用来自轨道碳观测站-2（OCO-2）的新的远红SIF观测结果，具有更精细的空间分辨率和2014年至2016年EC通量塔的GPP数据，以研究温带森林GPP和SIF之间的关系。OCO-2 SIF跟踪塔GPP良好，并在两个检索波段（757 nm和771 nm）和瞬时（中午）和每日的时间尺度与塔GPP有很强的相关性，与757 nm波段（SIF 757）在每日的时间尺度最强的关系。与基于Terra或Aqua卫星上的中分辨率成像光谱仪（MODIS）获得的地表反射率产品的增强植被指数（EVI）和归一化差异植被指数（NDVI）相比，每日SIF 757与塔GPP表现出更强的相关性，并且与基于双向反射分布函数（BRDF）校正的反射率产品的EVI具有类似的强关系（MCD 43 A4）基于Terra和Aqua的数据。SIF 757的光合有效辐射（APAR）解释了85%的方差，而APAR与两个环境标量fTmin和fVPD（代表最低温度胁迫和水分胁迫）的乘积解释了更高的方差（92%）。这表明，SIF主要取决于APAR，也受到环境胁迫的影响，决定光合光利用效率。BRDF校正的EVI也比SIF具有优势，因为EVI具有空间和时间连续的覆盖范围，并且具有更长的记录（2000年至今）。OCO-2 SIF 757对GPP的估计效果很好（R2= 0.81，p < 0.0001; RMSE = 1.11 gC m− 2d− 1），其性能与基于光利用效率逻辑的GPP模型MODIS GPP算法相当或略好。通过在Park福尔斯（OCO-2的校准/验证站点）周围的Target模式下采集的密集OCO-2观测数据，我们还生成了网格化的SIF，然后在景观尺度上以每个像素为基础估计GPP。我们的研究结果表明OCO-2观测到的叶绿素荧光在估计温带森林GPP方面的强大能力，并揭示了其在未来生态系统功能和碳循环研究中的潜力和局限性。
Solar-induced chlorophyll fluorescence (SIF) opens a new perspective on the monitoring of vegetation photosynthesis from space, and has been recently used to estimate gross primary productivity (GPP). However, previous studies on SIF were mainly based on satellite observations from the Greenhouse Gases Observing Satellite (GOSAT) and Global Ozone Monitoring Experiment-2 (GOME-2), and the evaluation of these coarse-resolution SIF measurements using GPP derived from eddy covariance (EC) flux towers has been hindered by the scale mismatch between satellite and tower footprints. We use new far-red SIF observations from the Orbiting Carbon Observatory-2 (OCO-2) with much finer spatial resolution and GPP data from EC flux towers from 2014 to 2016 to examine the relationship between GPP and SIF for temperate forests. The OCO-2 SIF tracked tower GPP well, and had strong correlation with tower GPP at both retrieval bands (757 nm and 771 nm) and both instantaneous (mid-day) and daily timescales, with the strongest relationship for the 757 nm band (SIF757) at the daily timescale. Daily SIF757exhibited much stronger correlation with tower GPP compared to the enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) based on the surface reflectance product derived from the moderate resolution imaging spectroradiometer (MODIS) onboard either Terra or Aqua satellite and had a similarly strong relationship as EVI based on the bidirectional reflectance distribution function (BRDF) corrected reflectance product (MCD43A4) based on data from both Terra and Aqua. Absorbed photosynthetically active radiation (APAR) explained 85% of the variance in SIF757, while the product of APAR and two environmental scalars -fTminandfVPD (representing minimum temperature stress and water stress) explained higher variance (92%) in SIF757. This suggests that SIF mainly depends on APAR and is also affected by environmental stresses that determine photosynthetic light use efficiency. The BRDF-corrected EVI also has advantages over SIF in that EVI has spatially and temporally continuous coverage and has a much longer record (2000-present). The OCO-2 SIF757estimated GPP well (R2= 0.81,p< 0.0001; RMSE = 1.11 gC m− 2d− 1), and its performance was comparable to or slightly better than that of the MODIS GPP algorithm, a GPP model based on the light use efficiency logic. With intensive OCO-2 observations acquired in theTargetmode around Park Falls, a calibration/validation site for OCO-2, we also generated gridded SIF and then estimated GPP on a per-pixel basis at the landscape scale. Our findings demonstrate the strong ability of chlorophyll fluorescence observed by OCO-2 in estimating GPP for temperate forests and reveal its potential and limitations in future ecosystem functioning and carbon cycling studies.