Arctic shrub growth trajectories differ across soil moisture levels.
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Global change biology, ISSN: 1365-2486, Vol: 23, Issue: 10, Page: 4294-4302
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The circumpolar expansion of woody deciduous shrubs in arctic tundra alters key ecosystem properties including carbon balance and hydrology. However, landscape-scale patterns and drivers of shrub expansion remain poorly understood, inhibiting accurate incorporation of shrub effects into climate models. Here, we use dendroecology to elucidate the role of soil moisture in modifying the relationship between climate and growth for a dominant deciduous shrub, Salix pulchra, on the North Slope of Alaska, USA. We improve upon previous modeling approaches by using ecological theory to guide model selection for the relationship between climate and shrub growth. Finally, we present novel dendroecology-based estimates of shrub biomass change under a future climate regime, made possible by recently developed shrub allometry models. We find that S. pulchra growth has responded positively to mean June temperature over the past 2.5 decades at both a dry upland tundra site and an adjacent mesic riparian site. For the upland site, including a negative second-order term in the climate-growth model significantly improved explanatory power, matching theoretical predictions of diminishing growth returns to increasing temperature. A first-order linear model fit best at the riparian site, indicating consistent growth increases in response to sustained warming, possibly due to lack of temperature-induced moisture limitation in mesic habitats. These contrasting results indicate that S. pulchra in mesic habitats may respond positively to a wider range of temperature increase than S. pulchra in dry habitats. Lastly, we estimate that a 2°C increase in current mean June temperature will yield a 19% increase in aboveground S. pulchra biomass at the upland site and a 36% increase at the riparian site. Our method of biomass estimation provides an important link toward incorporating dendroecology data into coupled vegetation and climate models.