Spatial and Temporal Variation in Feather Moss Associated Nitrogen Fixation in Coniferous and Deciduous Dominated Alaskan Boreal Forests

Abstract:

Dominant canopy tree species have strong effects on the composition and function of understory species. In boreal forests, forest floor bryophytes and their associated microbes are a primary source of ecosystem nitrogen (N) inputs, and thus an important process regulating ecosystem productivity. Bryophyte composition and abundance varies with forest composition, yet how such changes can affect ecosystem processes such as N fixation is still poorly understood. Our goal is to investigate how cyanobacteria-based N fixation occurring in the two most common feather mosses in the Alaskan boreal forest (Pleurozium schreberi and Hylocomium splendens) varies among coniferous and deciduous forest types, over the growing season, and across a nutrient availability gradient. Twelve patches of H. splendens and P. schreberi were identified in three pairs (blocks) of adjacent stands of paper birch (Betula neoalaskana) and black spruce (Picea mariana) near Fairbanks, interior Alaska. Sampling occurred in one block in June, July, August, and September 2014, and in the three blocks once in August 2014. Moss leaf area, moisture and weight, as well as environmental variables such as air temperature and canopy cover were recorded. Fixation rates were consistently higher for P. schreberi than for H. splendens. Overall, N fixation rates were lower in birch than in spruce stands and peaked in August, or July for P. schreberi in birch stands. Moreover, fixation rates varied along the nutrient availability gradient, with fixation rates higher where nutrient availability was lower. This difference was especially clear in spruce stands. Our preliminary results suggest that moss species, canopy type, and environmental factors all influence N fixation rates in Alaskan boreal forests. Our results will enhance the knowledge of the processes that drive N fixation in boreal forests, which is important for predicting ecosystem consequences of changing forest composition.