Remote estimates of ice algae biomass and their response to environmental conditions during spring melt

• Published in: ARCTIC
• Main Authors: Campbell, Karley, Mundy, C.J., Barber, David, Gosselin, Michel
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2014
• Subjects: Allen Bay; Nunavut; Arctic; ice algae; Sea ice
• Online Access: https://hdl.handle.net/1983/5e88732a-eeb9-4f3c-a539-30fcc071edee; https://research-information.bris.ac.uk/en/publications/5e88732a-eeb9-4f3c-a539-30fcc071edee; https://doi.org/10.14430/arctic4409

In this study, we support previous work showing that a normalized difference index (NDI) using two spectral bands of transmitted irradiance (478 and 490 nm) can be used as a non-invasive method to estimate sea ice chlorophyll a (chl a) following a simple calibration to the local region. Application of this method during the spring bloom period (9 May to 26 June) provided the first non-invasive time series dataset used to monitor changes in bottom ice chl a concentration, an index of algal biomass, at a single point location. The transmitted irradiance dataset was collected on landfast first-year sea ice of Allen Bay, Nunavut, in 2011, along with the physical variables thought to affect chl a accumulation and loss at the ice bottom. Time series biomass calculated using the NDI technique adhered well to core based biomass estimates although, chl a values remained low throughout the bloom, reaching a maximum of 27.6 mg m-2 at the end of May. It is likely that warming of the bottom ice contributed to loss of chl a through its positive influence on brine drainage and ice melt. Chl a content in the bottom ice was also significantly affected by a storm event on 10 June, which caused extensive surface melt and a rapid increase in the magnitude of transmitted irradiance. Furthermore, the velocity of current, measured below the ice at the end of a spring neap-tidal cycle, was negatively associated with ice algae chl a biomass (the stronger the current, the less biomass). The NDI method to remotely estimate ice algal biomass proved useful for application in our time series process study, providing a way to assess the effects of changes to the sea ice environment on the biomass of a single population of ice algae.