Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics.

In northern Alaska nearly 65% of the terrestrial surface is composed of polygonal ground, where geomorphic tundra landforms disproportionately influence carbon and nutrient cycling over fine spatial scales. Process-based biogeochemical models used for local to Pan-Arctic projections of ecological responses to climate change typically operate at coarse-scales (1km²–0.5°) at which fine-scale (<1km²) tundra heterogeneity is often aggregated to the dominant land cover unit. Here, we evaluate the importance of tundra heterogeneity for representing soil carbon dynamics at fine to coarse spatial scales. We leveraged the legacy of data collected near Utqiaġvik, Alaska between 1973 and 2016 for model initiation, parameterization, and validation. Simulation uncertainty increased with a reduced representation of tundra heterogeneity and coarsening of spatial scale. Hierarchical cluster analysis of an ensemble of 21^st-century simulations reveals that a minimum of two tundra landforms (dry and wet) and a maximum of 4km² spatial scale is necessary for minimizing uncertainties (<10%) in regional to Pan-Arctic modeling applications. Carbon stored in the Arctic is threatened by climate change, but models do not capture the local-scale heterogeneity that influences carbon dynamics. Here the authors refine tundra models to account for heterogeneity, finding improved projections and decreased uncertainty in assessing the fate of carbon. [ABSTRACT FROM AUTHOR]