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Question

Vascular plant productivity of arctic tundra has often been viewed as varying little between years and thus being largely insensitive to the high inter-annual variation in summer weather conditions. Yet, remote-sensing data and retrospective growth analyses of the circumpolar dwarf shrub, Cassiope tetragona, commonly show considerable between-year variability in plant growth in response to variation in summer temperature. Given that both Cassiope growth and vascular plant biomass production share a common environmental driver, summer temperature, we would expect positive co-variation between them. Here we investigate whether this is indeed the case and if so over what spatial scale.

LocationMethodsNordenskioldland, high arctic Svalbard.

We brought dendroecology and plot-based field estimation methodologies together in an empirical study using retrospective analysis of Cassiope growth and annual estimation of above-ground vegetation biomass production to investigate their temporal and spatial co-variation and sensitivity to summer weather conditions.

ResultsConclusionsDespite substantial small-scale heterogeneity, we found spatial co-variation in Cassiope growth patterns, which weakened as distance between sampling sites increased from 0 to 25km. Furthermore, we found a strong positive correlation between annual estimates of above-ground live vascular plant biomass and Cassiope shoot growth over a 12-year period at a local scale. The correlation declined with distance, likely due to increasing differences in local weather conditions.

We demonstrate that Cassiope growth can be used as a proxy for above-ground tundra vegetation productivity at the local scale. Our findings suggest that Arctic plant productivity is as sensitive to between-year variation in summer temperature as the well-established growth response of Cassiope. This challenges the view that tundra plant productivity varies little between years and provides a mechanistic understanding that helps reconcile field- and satellite-based annual estimation methods.