Arctic-alpine vegetation biomass is driven by fine-scale abiotic heterogeneity

Abstract

During recent decades large changes in vegetation biomass have been observed in arctic and alpine areas. While these temporal trends have been clearly linked to changing climatic conditions, the drivers of local spatial variation in biomass are still relatively poorly understood. Thus, we examine the effects of abiotic conditions (as measured by ten variables representing topography, soil properties and geomorphological processes) on variation in aboveground vascular plant biomass to understand the determinants of contemporary fine scale heterogeneity in this variable. We also compare the results from one destructive biomass estimation method (clipharvesting) to three non-destructive biomass estimates: vegetation cover, height and volume. To investigate the local drivers of biomass we analysed an extensive data set of 960 1 m2 cells in arctic–alpine tundra using spatially-explicit generalized estimation equations to conduct variation partitioning. The abiotic environment had a clear impact on the fine scale distribution of biomass (variance explained 32.89 % with full model for sampled biomass). Soil properties (temperature, moisture, pH and calcium content) were most strongly related to aboveground biomass (independent effect in variation partitioning 7.03 % and combined effect including joined effects with topography and geomorphology 19.6 %). Topography had only a small influence after soil and geomorphology were taken into account (independent effect only 2.23 % and combined effect 18.73 %), implying that topography has only indirect effects on vegetation biomass. Of the three non destructive biomass estimates, the results for vegetation volume were most similar to those for clipharvested biomass samples. Thus, we recommend utilizing vegetation volume as a cost-efficient and robust non-destructive biomass estimate in arctic-alpine areas. Our results indicate that the fine scale environmental variation has to be taken into account more carefully when modelling vegetation biomass and carbon budget, especially under changing climatic conditions.