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Processes of multibathyal aragonite undersaturation in the A rctic O cean
Author(s) -
Wynn J. G.,
Robbins L. L.,
Anderson L. G.
Publication year - 2016
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1002/2016jc011696
Subject(s) - aragonite , halocline , oceanography , canada basin , arctic , geology , salinity , mineralogy , calcite
During 3 years of study (2010–2012), the western Arctic Ocean was found to have unique aragonite saturation profiles with up to three distinct aragonite undersaturation zones. This complexity is produced as inflow of Atlantic‐derived and Pacific‐derived water masses mix with Arctic‐derived waters, which are further modified by physiochemical and biological processes. The shallowest aragonite undersaturation zone, from the surface to ∼30 m depth is characterized by relatively low alkalinity and other dissolved ions. Besides local influence of biological processes on aragonite undersaturation of shallow coastal waters, the nature of this zone is consistent with dilution by sea‐ice melt and invasion of anthropogenic CO 2 from the atmosphere. A second undersaturated zone at ∼90–220 m depth (salinity ∼31.8–35.4) occurs within the Arctic Halocline and is characterized by elevated p CO 2 and nutrients. The nature of this horizon is consistent with remineralization of organic matter on shallow continental shelves bordering the Canada Basin and the input of the nutrients and CO 2 entrained by currents from the Pacific Inlet. Finally, the deepest aragonite undersaturation zone is at greater than 2000 m depth and is controlled by similar processes as deep aragonite saturation horizons in the Atlantic and Pacific Oceans. The comparatively shallow depth of this deepest aragonite saturation horizon in the Arctic is maintained by relatively low temperatures, and stable chemical composition. Understanding the mechanisms controlling the distribution of these aragonite undersaturation zones, and the time scales over which they operate will be crucial to refine predictive models.