The changing physical and biological drivers for the benthic biological hotspot regions in the northern Bering and Chukchi continental shelf

Zhixuan Feng, East China Normal University, Shanghai, China, Rubao Ji, Woods Hole Oceanographic Inst., Biology Department, Woods Hole, MA, United States, Carin J Ashjian, Woods Hole Oceaonographic Institution, Woods Hole, MA, United States, Jinlun Zhang, University of Washington, Seattle, WA, United States, Robert G Campbell, University of Rhode Island Narragansett Bay, Narragansett, RI, United States and Jacqueline M. Grebmeier, University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, Solomons, MD, United States
The Pacific Arctic Ocean is experiencing significant changes in atmosphere, sea ice, and ocean parameters that may alter the coupling between sympagic (ice-associated), pelagic, and benthic ecosystem components. For example, time series observations through the Distributed Biological Observatory program indicate that, in the St. Lawrence Island Polynya region of the northern Bering Sea, high benthic biomass centers shifted northward recently even prior to bottom water temperatures rising above 0°C in summer 2018 for the first time since the initiation of this time series in 2000. To evaluate the changing physical and biological processes that affect primary and export production of the organic matter, satellite ocean color chlorophyll-a, historical in situ measurements, and ice-ocean-biogeochemical model outcomes from 1998 to 2018 are analyzed with emphases on five known benthic hotspot regions in the Pacific Arctic. Interannual variability and decadal trends of the physical transport rates (advection and sinking) and multiple biological rates (primary production, respiration, mortality, excretion, and zooplankton grazing) contributing to carbon export production are evaluated and compared to variability and trends in satellite-derived net primary productivity and observed benthic biomasses. Combining continuous time series observations with process-based models are imperative to achieve a system-level understanding of this strongly coupled sympagic-pelagic-benthic ecosystem and to develop a predictive capability of the rapidly changing Pacific Arctic Ocean.