Linking Plant Trait Variability to Biogeochemical Cycling in High-Latitude Heathlands

In many high-latitude ecosystems, ericaceous dwarf-shrubs play a dominant role influencing patterns of biodiversity and driving ecosystem functioning. Despite this importance, dwarf-shrubs are underrepresented when modelling how vegetation influences fluxes of carbon, water and energy in land surface models. To create new plant functional types that better represent these important species and processes, we use plant functional traits to explore responses and effects to environmental and biotic interactions. While current land surface models rely on fixed trait parameters, understanding the range and drivers of intraspecific variation is essential for selecting representative values and improving predictions of biogeochemical fluxes. In the DURIN project, we examine intraspecific variability in plant functional traits focusing on the dwarf shrubs Calluna vulgaris, Empentrum nigrum, Vaccinium myrtillus and Vaccinium vitis-idaea which represent both evergreen and deciduous species and a range of the leaf economics spectrum. These keystone species were sampled in paired forested and open heathlands located at coastal and inland sites distributed in southern and northern Norway. Here we found high levels of intraspecific variation across our species, with more conservative trait expression typically exhibited in open habitats, inland and northern sites. Next we seek to investigate how these shifts in trait variation may influence carbon cycling via in-situ assessments of leaf-level thermal tolerance limits for photosynthesis and a litter transplant experiment to understand rates of litter decomposition. Developing these integrated understandings of how leaf traits influence the broader biogeochemical cycle at both local and regional scales, will provide critical insights into not only the adaptive potential of these key species, but also provide more robust parameters for inclusion in land surface models improving our vegetation-climate predictions under ongoing global change.