Assessment of light absorption within highly scattering bottom sea ice from under‐ice light measurements: Implications for Arctic ice algae primary production

• Published in: Limnology and Oceanography
• Main Authors: Ehn, Jens K., Mundy, C. J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2013
• Subjects: ice algae; Sea ice
• Online Access: http://dx.doi.org/10.4319/lo.2013.58.3.0893; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.4319%2Flo.2013.58.3.0893; https://aslopubs.onlinelibrary.wiley.com/doi/pdf/10.4319/lo.2013.58.3.0893

Primary production estimates of ice algae within the bottommost layers of the Arctic ice cover are commonly derived using irradiance measurements taken immediately below the solid ice bottom. However, radiation absorbed by ice algae is significantly affected by the high‐scattering sea ice environment they are embedded within because scattering increases the pathlength traveled by photons and therefore the probability of photon encounters with algal cells. Failing to account for this enhanced absorption may considerably affect estimates of the timing and magnitude of ice algal production. To demonstrate the effect of scattering and attenuation, multipliers for absorption amplification (Φ) and layer average opacity ( χ ) were derived from observations of chlorophyll a concentration and the vertical attenuation coefficient over the bottom 2.5 cm of landfast sea ice. Φ reached values over 19 at low chlorophyll a , but became < 2 at high biomass levels, whereas χ became larger as biomass levels increased. Using Φ to construct an apparent photosynthesis vs. irradiance relationship showed that light limitation is greatly reduced relative to the case where scattering is not considered. This highlights an important interaction not previously noted for ice algal production in their high‐scattering environment. Knowledge of this absorption amplification can help explain ice algal phenology during the spring bloom and will improve ice algal production estimates and model parameterizations.