日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_(GPP))为第63天,生长季结束时间(EOS_(GPP))为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_(GPP)31天,植被指数EOS滞后EOS_(GPP)10—17天。虽然基于3种遥感指数估算的春季和秋季物候都滞后于通量GPP的物候期,但是卫星SIF的物候信息能够更好地捕捉常绿针叶林的生长阶段。同时,春季温度是影响森林生长季开始时间的最重要因素;秋季水分和辐射是影响生长季结束时间的关键因素。由此可见,SIF估算的亚热带常绿针叶林的春季和秋季物候的滞后时间要短于传统植被指数,能更好地追踪常绿林光合作用的季节性,为深入研究陆地生态系统碳循环及其对气候变化的响应提供重要的基础。

Land surface phenology tracked by remotely sensed sun-induced chlorophyll fluorescence in subtropical evergreen coniferous forests

Vegetation phenology, the timing and the length of growing season, is sensitive indicator in response of terrestrial carbon, energy and water cycles to climate change. Understanding the changes of vegetation phenology as well as its response to climate change is of significance for predicting climate changes and global carbon cycle. Vegetation phenology are estimated mainly based on reflectance-calculated vegetation indexes (VIs), such as normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). However, large uncertainty exists in performance of VIs in land surface phenology due to small changes in seasonal variations of evergreen confers. The methodology of SIF to estimate land surface phenology has frequently been applied in deciduous forest. However, monitoring the phenology using SIF has not been sufficiently investigated in evergreen coniferous forest. In this study, we assessed the ability of reflectance-based vegetation indices (NDVI, EVI) and SIF datasets in monitoring the gross primary production (GPP)-based phenology in a subtropical evergreen coniferous forest. The vegetation indices were obtained from MODerate-resolution Imaging Spectroradiometer (MODIS) products and the SIF is retrieved from Global Ozone Monitoring Experiment-2 (GOME-2) from 2007 to 2011. Our results indicated that the GPP-based phenology, such as the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (LOS) of subtropical evergreen conifers were day of year (DOY) 63, DOY 324 and DOY 272. The phenological metrics derived from the SIF were later than those derived from eddy covariance GPP, and the time-lag SOS_SIF and EOS_SIF were 19 days and 2 days, respectively. The time-lag SOS from NDVI and EVI was about 31 days related to SOS_GPP; meanwhile the time-lag EOS from NDVI and EVI was 10-17 days. The LOS derived from remotely sensed indexes were all shorter than the LOS_GPP, and GOME-2 SIF behaved better in capturing the growing stage of evergreen conifers in subtropical region of China. Spring temperature had the highest correlation with SOS, while water condition and solar radiation were determinants of the EOS at Qianyanzhou station. These results suggest that SIF, containing information of light-use efficiency, can accurately monitor the phenology of evergreen conifers and has important implications for biosphere models.