Subnivean Arctic and sub-Arctic net ecosystem exchange (NEE)

• Published in: Progress in Physical Geography: Earth and Environment
• Main Authors: Luus, Kristina A., Lin, John C., Kelly, Richard E.J., Duguay, Claude R.
• Format: Article in Journal/Newspaper
• Language: English
• Published: SAGE Publications 2013
• Subjects: General Earth and Planetary Sciences; Earth and Planetary Sciences (miscellaneous); Geography, Planning and Development; Arctic
• Online Access: http://dx.doi.org/10.1177/0309133313491130; http://journals.sagepub.com/doi/pdf/10.1177/0309133313491130; http://journals.sagepub.com/doi/full-xml/10.1177/0309133313491130

In the Arctic and sub-Arctic, up to half of annual net ecosystem exchange (NEE) occurs during the snow season. Subnivean soil respiration can persist at a greater rate when the overlying snowpack has a lower thermal conductivity, and the rate of photosynthetic uptake at the start and end of the snow season can be diminished by fractional snow cover. Although recent studies have indicated that uncertainty in model estimates of NEE can be reduced by representing the influence of a modeled snowpack on soil respiration, models of NEE have not represented the influence of snowpack dynamics on processes such as subnivean photosynthesis or CO 2 diffusivity, and have not used remote sensing observations to characterize snow season processes. We therefore: (1) review snow season processes and their effects on NEE; (2) assess the suitability of cryospheric remote sensing approaches for models of NEE; and (3) suggest strategies for representing snow season processes in models of NEE. Strategies include: using observations of fractional snow cover in spring and fall to restrict estimates of photosynthetic uptake; combining observations of snow accumulation and soil freeze/thaw with observations of air temperature to generate more realistic estimates of soil temperature and soil respiration; and using observations of depth to estimate the influence of snow accumulation and tree wells on soil respiration. Including remote sensing observations of snow properties in models of NEE could reduce uncertainty in snow season estimates of NEE, resulting in a better understanding of the northern carbon cycle and how it is responding to climate-driven changes in the interconnected biospheric, atmospheric and cryospheric systems.