An Eye in the Ocean: Physical Drivers of Biological Distributions in the Western Chukchi Sea - Synthesis Activities

Carin J. Ashjian  Woods Hole Oceanographic Institution


In the Arctic Ocean, the biological response to climate change should be dramatic yet is difficult to predict because many basic components of the ocean system are undescribed.  Plankton community composition, spatial (vertical, regional) and temporal (diel, seasonal, annual) patterns in distribution and abundance, and the associations of species and taxa with water mass type remain enigmatic for much of the Arctic ecosystem.  In particular, the interaction of physical mechanisms with biological distributions is poorly described, especially at dynamic boundaries. Herald Valley and the Western Chukchi are critical regions where physical mechanisms impact biological distributions.  Strong regional variation in plankton distribution, abundance, and composition in association with the distinct water mass types present should be observed.  Such interactions are best observed using instruments such as the Video Plankton Recorder (VPR) that are capable of resolving high-resolution distributions of planktonic taxa and particles and coincident hydrographic and velocity characteristics

High-vertical resolution distributions of plankton, particles, and coincident hydrography have been collected using a VPR on three cruises to the Chukchi Sea, including the western Chukchi, in 2004, 2009, and 2012 as part of the RUSALCA program.  The objective of this proposal is to participate in the preparation of manuscripts synthesizing data from multiple projects and disciplines within the RUSALCA program that will comprise a special issue of the journal Oceanography.  The primary synthesis activity will focus on Physical Drivers and Biological and Geochemical Responses in the Western Arctic (Chapter 4) but additional contributions to Chapter 5 (Community Production) and Chapter 6 (Plankton Time Series) also are planned.

The proposed work is relevant both to NOAA’s Climate Goal that targets understanding and predicting climate variability and its impact on ecosystems and to the performance measures of the RUSALCA program.  Predicting the impact of climate on ecosystems requires an understanding of the important components and interactions in the ecosystem, both to identify change and to develop a predictive modeling capability for the ecosystem.  This work will provide key distributions and processes for this understanding and capability.