Snow and vegetation seasonality influence seasonal trends of leaf nitrogen and biomass in Arctic tundra

• Main Authors: Kelsey, K. C. (Katharine C.), Pedersen, S. H. (Stine Højlund), Leffler, A. J. (A. Joshua), Sexton, J. O. (Joseph O.), Welker, J. M. (Jeffrey M.)
• Format: Article in Journal/Newspaper
• Language: English
• Published: John Wiley & Sons 2023
• Subjects: Arctic; NDVI; biomass; carbon; functional group; leaf nitrogen; nitrogen; phenology; plant functional group; snow phenology; vegetation phenology; Climate change; Tundra; Alaska
• Online Access: http://urn.fi/urn:nbn:fi-fe2023081596701

Abstract Climate change, including both increasing temperatures and changing snow regimes, is progressing rapidly in the Arctic, leading to changes in plant phenology and in the seasonal patterns of plant properties, such as tissue nitrogen (N) content and community aboveground biomass. However, significant knowledge gaps remain over how these seasonal patterns vary among Arctic plant functional groups (i.e., shrubs, grasses, and forbs) and across large geographical areas. We used three years of in situ field vegetation sampling from an 80,000-km² area in Arctic Alaska, remotely sensed vegetation data (daily normalized difference vegetation index [NDVI]), and modeled output of snow-free date to determine and model the seasonal trends and primary controls on leaf percent nitrogen and biomass (in grams per square meter) among Arctic vegetation functional groups. We determined relative vegetation phenology stage at a 500-m spatial scale resolution, defined as the number of days between the date of the seasonal maximum NDVI and the vegetation field sampling date, and relative snow phenology stage (90-m spatial scale) was determined as the number of days between the date of snow-free ground and the sampling date. Models including relative phenology stage were particularly important for explaining seasonal variability of %N in shrubs, graminoids, and forbs. Similarly, vegetation and snow phenology stages were also important for modeling seasonal biomass of shrubs and graminoids; however, for all functional groups, the models explained only a small amount of seasonal variability in biomass. Relative phenology stage was a stronger predictor of %N and biomass than geographic position, indicating that localized controls on phenology, acting at spatial scales of 500 m and smaller, are critical to understanding %N and biomass.