Characterization of a seasonally snow-covered evergreen forest ecosystem
2021
Zhang, Qingyuan
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.
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