Polar Biology

, Volume 40, Issue 9, pp 1721–1737 | Cite as

Changes in phytoplankton bloom phenology over the North Water (NOW) polynya: a response to changing environmental conditions

  • Christian Marchese
  • Camille Albouy
  • Jean-Éric Tremblay
  • Dany Dumont
  • Fabrizio D’Ortenzio
  • Steve Vissault
  • Simon Bélanger


Marine ecological indicators can be used to assess the condition of the pelagic ecosystems. The bloom onset provides a warning bell for possible changes in trophic interactions and biogeochemical processes. However, depicting the phenology of phytoplankton blooms at high latitudes, where long-term observations are sparse or unavailable, is not a straightforward task. A data-interpolating empirical orthogonal function algorithm was applied to daily satellite-retrieved chlorophyll-a images to produce a long-term (1998–2014) and cloud-free data set over the North Water (NOW) polynya. The seasonal bloom was modeled using a multi-Gaussian approach from which a baseline of phenological characteristics was extracted. The correlation analysis highlights the influence of environmental factors, such as sea surface temperature, cloud fraction, wind stress, and sea-ice concentration, in modulating the bloom start date, its duration, and amplitude. The year-to-year variability in bloom onset appears to be controlled by a delicate balance between oceanographic and meteorological conditions. Blooms last longer during years characterized by a longer open-water period and are shorter during those characterized by greater sea-ice coverage. Noteworthy is the decrease in phytoplankton bloom amplitude over the 17 years examined. Collectively, these outcomes depict the NOW as a climate-sensitive region in which the pelagic marine ecosystem seems to be going toward a decline in chlorophyll-a concentrations. Satellite time series are still too short to differentiate between inter-annual variability, inter-decadal variability, and climate change signal. Should these changes persist; however, the NOW may no longer act as a productive regional oasis supporting thriving populations of zooplankton and top predators.


Phenology Phytoplankton NOW polynya Gaussian model Remote sensing Physical forcing 



This study was supported by grants from ArcticNet, the Network of Centres of Excellence of Canada and the NSERC, and the Natural Sciences and Engineering Research Council of Canada (to S. B., J.-É. T. and D. D.). C. M. received a postgraduate scholarship from Université du Québec à Rimouski (UQAR) and funded by ArcticNet. C.A. is funded by a MELS FQRNT and RAQ postdoctoral fellowship. This is a contribution to the research programs of ArcticNet and Québec-Océan. We would like to thank M. Taylor for providing useful information about the use of the DINOEF method. We are very grateful to the reviewers for their helpful comments and remarks. We also thank E. Calabretta and L. Gray for language support.

Supplementary material

300_2017_2095_MOESM1_ESM.docx (2.1 mb)
Supplementary material 1 (DOCX 2108 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Christian Marchese
    • 1
  • Camille Albouy
    • 1
    • 2
    • 3
  • Jean-Éric Tremblay
    • 4
  • Dany Dumont
    • 5
  • Fabrizio D’Ortenzio
    • 6
  • Steve Vissault
    • 1
  • Simon Bélanger
    • 1
  1. 1.Département de biologie, Chimie et géographieUniversité du Québec à RimouskiQuébecCanada
  2. 2.Landscape Ecology, Institute of Terrestrial EcosystemsETH ZürichZurichSwitzerland
  3. 3.Swiss Federal Research Institute WSLBirmensdorfSwitzerland
  4. 4.Québec-Océan et Takuvik, Département de biologieUniversité Laval, Pavillon Alexandre-VachonQuébecCanada
  5. 5.Institut des sciences de la mer de RimouskiUniversité du Québec à RimouskiQuébecCanada
  6. 6.Laboratoire d’Oceanographie de Villefranche (LOV)Université Pierre et Marie Curie and CNRS, UMR 7093Villefranche-sur-MerFrance

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