Assessing consistency of spring phenology of snow-covered forests as estimated by vegetation indices, gross primary production, and solar-induced chlorophyll fluorescence

Abstract

Accurate phenology characterization is of great importance for measuring ecosystem dynamics, especially for carbon and water exchange between land and the atmosphere. Vegetation indices (VIs), calculated from land surface reflectance, are widely used to estimate phenology from the leaf and canopy structure perspective. Gross Primary Production (GPP) and solar-induced chlorophyll fluorescence (SIF) are used to estimate phenology from the canopy functional (physiological) perspective. To what degree are the spring phenology estimated from these different perspectives consistent with each other? In this study, we evaluated the consistency of the start of the growing season (SOS) in spring for snow-covered evergreen needleleaf forests (ENF) and deciduous broadleaf forests (DBF) using three vegetation indices, in-situ GPP data from the eddy covariance flux towers (GPPEC), GPP data from the Vegetation Photosynthesis Model (GPPVPM), and SIF data from the GOME-2. Results showed that SOSNDVI dates were much earlier than SOS dates from EVI (SOSEVI), land surface water index (LSWI) (SOSLSWI), GPP (SOSGPP; SOSGPP-EC, SOSGPP_VPM) and SIF (SOSSIF) for both snow-covered evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF). SOSLSWI dates were more linearly correlated with SOSGPP and SOSSIF than SOS dates from NDVI and EVI. At ENF sites, SOSLSWI dates were 17 (± 27) days later and SOSEVI were 25 (± 34) days later than SOSGPP_EC dates. At DBF sites, SOSLSWI and SOSEVI dates were 1-week (± 13 days) later than SOSGPP_EC dates. In the snow-covered regions at mid- to high-latitude in the Northern Hemisphere, SOSLSWI dates were 2˜3 weeks (± 5 days) later than those of SOSGPP_VPM and SOSSIF for both ENF and DBF. Our results clearly highlight the need for further investigation of NDVI-based SOS dates, which were likely affected by snowmelt in snow-covered forests, and the potential of LSWI for tracking the effects of snow on SOS dates. Estimations of SOS dates in snow-covered forests should consider the effects of both snow cover and temperature on leaf emergence (green-up) and gross primary production.