Characterization of a seasonally snow-covered evergreen forest ecosystem

It remains challenging to interpret seasonal profile of vegetation dynamics from empirical indices NDVI and EVI for boreal forests due to confounding impacts of snow, soil and snowmelt in winter and spring. This work aims to characterize the seasonally snow-covered Howland boreal forest ecosystem in Maine, USA with the Moderate Resolution Imaging Spectrometer (MODIS) images. Vegetation cover fraction (VGCF), fractional absorption of photosynthetically active radiation (fAPAR) by all canopy components (fAPARcanopy), fAPAR by canopy chlorophyll (fAPARchl) and fAPAR by canopy non-chlorophyll components (fAPARnon-chl) were extracted from MODIS images in multiple years (2001 - 2014). Snow exposed during December to April. Top of canopy viewable snow cover fraction in April of multiple years varied between 0.02 and 0.16 (0.06 +/- 0.04). Seasonal VGCF and fAPARcanopy showed a summer plateau (VGCF: 0.97 +/- 0.01; fAPARcanopy: 0.90 +/- 0.01). Both seasonal fAPARchl and fAPARnon-chl changed with time, and seasonal fAPARnon-chl had a bimodal shape. Spring VGCF varied between 0.54 and 0.69 (0.61 +/- 0.04). Spring fAPARchl and fAPARnon-chl were 0.22 +/- 0.03 and 0.21 +/- 0.02, respectively. Peak summer fAPARchl was 0.58 +/- 0.02. The lowest summer fAPARnon-chl was 0.32 +/- 0.02. Replacing fAPARcanopy with fAPARchl to simulate boreal forest ecosystem gross primary production (GPP) could reduce uncertainties in GPP simulations.

Automated summary

This study investigated the seasonal snow cover of the Howland boreal forest ecosystem in Maine, USA using MODIS images, which revealed the variations in vegetation cover fraction, absorption of photosynthetically active radiation, and related parameters throughout different seasons.