Contribution of subsurface chlorophyll maxima to primary production in the coastal Beaufort Sea (Canadian Arctic): A model assessment

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Abstract

Previous comprehensive investigations of the Canadian Arctic revealed that subsurface chlorophyll maxima (SCM) are widespread and long-lived structures that can contribute significantly to daily primary production in the water column. However, estimating the annual contribution of SCM to production with in situ or remote-sensing approaches is challenging in the high Arctic. For this reason and to estimate the impacts of fluctuating or changing environmental conditions on SCM, a numerical approach combining a turbulence model and an ecosystem model was implemented for the coastal Beaufort Sea. An ensemble analysis of simulations suggested that SCM contribute 65-90% of total annual primary production and that this proportion is weakly affected by ice regime, winter nitrogen (N) concentration, parameter values determining phytoplankton growth and decay or the physical forcing imposed, all varying within realistic values. Due to the persistent association between the SCM and the shallow nitracline, the pelagic ecosystem of the coastal Beaufort Sea is apparently characterized by a high ratio of new to total production, contrasting with the common assumption that oligotrophic systems are predominantly supported by recycled N and regenerated production. This study demonstrated that the use of a simple model in combination with in situ data leads to novel insights into biogeochemical processes that are otherwise very difficult to measure and track. Key Points Subsurface chlorophyll maxima (SCM) are simulated with a 1D ecosystem model SCM represent a large part of total annual production The association of the SCM with the nitracline favours new production ©2013. American Geophysical Union. All Rights Reserved.

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Martin, J., Dumont, D., & Tremblay, J. É. (2013). Contribution of subsurface chlorophyll maxima to primary production in the coastal Beaufort Sea (Canadian Arctic): A model assessment. Journal of Geophysical Research: Oceans, 118(11), 5873–5886. https://doi.org/10.1002/2013JC008843

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