4.7 Article

Early ice retreat and ocean warming may induce copepod biogeographic boundary shifts in the Arctic Ocean

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
Volume 121, Issue 8, Pages 6137-6158

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2016JC011784

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Funding

  1. National Science Foundation [PLR-1417677, PLR-1417339, PLR-1416920]
  2. Office of Polar Programs (OPP)
  3. Directorate For Geosciences [1416920] Funding Source: National Science Foundation

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Early ice retreat and ocean warming are changing various facets of the Arctic marine ecosystem, including the biogeographic distribution of marine organisms. Here an endemic copepod species, Calanus glacialis, was used as a model organism, to understand how and why Arctic marine environmental changes may induce biogeographic boundary shifts. A copepod individual-based model was coupled to an ice-ocean-ecosystem model to simulate temperature-and food-dependent copepod life history development. Numerical experiments were conducted for two contrasting years: a relatively cold and normal sea ice year (2001) and a well-known warm year with early ice retreat (2007). Model results agreed with commonly known biogeographic distributions of C. glacialis, which is a shelf/slope species and cannot colonize the vast majority of the central Arctic basins. Individuals along the northern boundaries of this species' distribution were most susceptible to reproduction timing and early food availability (released sea ice algae). In the Beaufort, Chukchi, East Siberian, and Laptev Seas where severe ocean warming and loss of sea ice occurred in summer 2007, relatively early ice retreat, elevated ocean temperature (about 1-2 degrees C higher than 2001), increased phytoplankton food, and prolonged growth season created favorable conditions for C. glacialis development and caused a remarkable poleward expansion of its distribution. From a pan-Arctic perspective, despite the great heterogeneity in the temperature and food regimes, common biogeographic zones were identified from model simulations, thus allowing a better characterization of habitats and prediction of potential future biogeographic boundary shifts.

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