Physical drivers of interannual
variability in phytoplankton phenology
Harriet Cole1, Stephanie Henson2,
Adrian Martin2, Andrew Yool2
1University
of Southampton
2 National Oceanography Centre
Harriet.Cole@noc.soton.ac.uk
Outline
• What is phenology and why is seasonality important?
• Seasonality metric definition – bloom timing
• Basin-wide relationships between bloom timing and
physical drivers
• Discussion – focus on subpolar North Atlantic and
bloom initiation
• Future work
harriet.cole@noc.soton.ac.uk
Phytoplankton bloom phenology
• Date of annually
occurring
features
Peak
• Defined in bloom
timing metrics
Initiation
Termination
harriet.cole@noc.soton.ac.uk
Why seasonality is important
• Overlap with peak abundance in grazers
Match-mismatch
hypothesis (Cushing,
1990)
Time
harriet.cole@noc.soton.ac.uk
Why seasonality is important
• Overlap with peak abundance in grazers
• Carbon export – biological pump
• Seasonal variability linked to magnitude of
flux and fraction that is labile/refractory
– Lutz et al. 2007
harriet.cole@noc.soton.ac.uk
Key Questions
• Meteorological conditions modulate bloom magnitude
– Subpolar North Atlantic - annual mean net heat flux, wind, TKE
– Spatially quite strong but not seen interannually (Follows and
Dutkiewicz, 2002)
• Mean winter net heat flux and wind speed predictors for bloom
initiation
– Irminger Basin (Henson et al. 2006)
• Does timing of change in physical environment influence bloom
timing? – e.g. date the ML shoals/ML deepens
• Do physical processes drive all of bloom timing?
harriet.cole@noc.soton.ac.uk
Critical depth vs. critical turbulence
• Critical depth
– Bloom starts when MLD
becomes shallower than
critical depth
• Critical turbulence
– Bloom starts when mixing
rates become slower than
phytoplankton growth and
accumulation rates
– Net heat flux becomes positive
(Taylor and Ferrari, 2011)
harriet.cole@noc.soton.ac.uk
Huismann et al. 1999
Bloom timing metrics
• GlobColour – satellite-derived chlorophyll
– Merges SeaWiFS, MODIS and MERIS
– 1x1 degree resolution, 8 day composites, 2002-2009
• NASA Ocean Biogeochemical Model (NOBM)
– Assimilates SeaWiFS, 8 day composites, 2002-2007 – Nerger & Gregg, 2008
– High fidelity to seasonal characteristics – Cole et al. 2012
– No gaps – error on bloom initiation (30 days), peak (15 days) from gaps in satellite data
• Initiation: rises 5%
above annual median
• Peak: maximum
chlorophyll value
+5%
Annual median
• End: falls below 5%
above annual median
• Siegel et al., 2002
harriet.cole@noc.soton.ac.uk
Physical data sources
• MLD
– T and S profiles (http://www.coriolis.eu.org/)
– density change of 0.03 kg m-3
• Net heat flux
– Satellite data + reanalysis products (NCEP/ECMWF)
– (http://oaflux.whoi.edu/)
• Irradiance
– PAR data from MODIS (http://oceancolor.gsfc.nasa.gov/)
– Average ML irradiance
harriet.cole@noc.soton.ac.uk
Average time series for North Atlantic
harriet.cole@noc.soton.ac.uk
Physical timing metrics
• Mixed layer depth
– Timing of MLD max, MLD shoaling
• PAR
– ML PAR starts to increase, fastest increase, MLD
shallower than euphotic zone depth
• Net heat flux
– Timing that NHF turns positive – Taylor and Ferrari,
2011
harriet.cole@noc.soton.ac.uk
Results
• Bloom initiation more strongly correlated
than peak and end with physical drivers
• Basin-wide response seen in subpolar N.
Atlantic
• Patchy correlations in subpolar N. Pacific and
S. Ocean
harriet.cole@noc.soton.ac.uk
North Atlantic latitudinal gradients
r=0.94
r=0.76
r=0.71
r=0.69
Bloom
initiation
Physical
metric
r=0.58
r=0.86
harriet.cole@noc.soton.ac.uk
North Atlantic interannual variability
r=0.73
r=0.38
• 6 30°x10°
boxes in North
Atlantic.
r=0.45
r=(0.36)
•
(r=-0.12)
(r=-0.013)
harriet.cole@noc.soton.ac.uk
Brackets
indicate
correlation
coefficient is not
statistically
significant at the
95% confidence
interval
North Atlantic vs.
r=0.73
r=0.38
r=0.45
North Pacific
r=0.32
(r=0.03)
(r=-0.11)
harriet.cole@noc.soton.ac.uk
Correlation map of bloom initiation and
NHF turns positive
• Coherent patches
harriet.cole@noc.soton.ac.uk
Discussion
• Bloom initiation – strongest relationship with changes in
physical environment
• Suggests biological processes more important for peak and
end timing
– Nutrient limitation, grazing, etc.
• NHF better than MLD for predicting start of bloom - critical
turbulence vs. critical depth
• Basin-wide response seen in N. Atlantic both spatially and
interannually
– Why different to N. Pacific and S. Ocean?
– Large scales – strong correlation, small scales - noisy
harriet.cole@noc.soton.ac.uk
Next steps
• Impact of global warming on the seasonal
cycle of phytoplankton
• Climate change-driven trends in bloom timing
using biogeochemical models
• Final year – submitting in October
harriet.cole@noc.soton.ac.uk
Summary
• Seasonality metrics develop to estimate bloom timing
• Correlated with timing of changes in physical environment –
spatially and interannually
• Bloom initiation more strongly correlated than peak and end
of bloom
• NHF better predictor than MLD for onset of bloom
• Basin-wide relationships weaker in N. Pacific and S. Ocean
harriet.cole@noc.soton.ac.uk
Acknowledgments
GlobColour Project/ESA
NOBM/Giovanni
MODIS/NASA
Coriolis Project
WHOI OAflux Project
Liége Colloquium – travel grant
Thank you for listening!
Questions?
harriet.cole@noc.soton.ac.uk
References
Cole, H., S. Henson, A. Martin and A. Yool (2012), Mind the gap: The impact of missing data on the calculation
of phytoplankton phenology metrics, J. Geophys. Res., 117(C8), C08030, doi:10.1029/2012jc008249.
Cushing, D. H. (1990), Plankton production and year-class strength in fish populations - an update of the match
mismatch hypothesis, Adv. Mar. Biol., 26, 249-293.
Follows, M. and S. Dutkiewicz (2002), Meteorological modulation of the North Atlantic spring bloom, Deep-Sea
Research Part Ii-Topical Studies in Oceanography, 49(1-3), 321-344.
Henson, S.A., I. Robinson, J.T. Allen and J.J. Waniek (2006), Effect of meteorological conditions on interannual
variability in timing and magnitude of the spring bloom in the Irminger Basin, North Atlantic, Deep-Sea
Research Part I-Oceanographic Research Papers, 53(10), 1601-1615, doi:10.1016/j.dsr.2006.07.009.
Lutz, M.J., K. Caldeira, R.B. Dunbar and M.J. Behrenfeld (2007), Seasonal rhythms of net primary production
and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean,
Journal of Geophysical Research-Oceans, 112(C10), C10011, doi:10.1029/2006JC003706.
Nerger, L. and W.W. Gregg (2008), Improving assimilation of SeaWiFS data by the application of bias correction
with a local SEIK filter, Journal of Marine Systems, 73(1-2), 87-102, doi:10.1016/j.jmarsys.2007.09.007.
Siegel, D.A., S.C. Doney and J.A. Yoder (2002), The North Atlantic spring phytoplankton bloom and Sverdrup's
critical depth hypothesis, Science, 296(5568), 730-733, doi: 10.1126/science.1069174.
Taylor, J.R. and R. Ferrari (2011), Shutdown of turbulent convection as a new criterion for the onset of spring
phytoplankton blooms, Limnology and Oceanography, 56(6), 2293-2307, doi:10.4319/lo.2011.56.6.2293.
harriet.cole@noc.soton.ac.uk