Primary productivity in a
changing ocean
Francisco Chavez
Senior Scientist
Monterey Bay Aquarium Research Institute
Topics/outline
•! PP and biogeochem variability in the sea
1.!Drivers and their variability
2.!Coastal versus open ocean
3.!How to best use the OOI array for biogeo?
4.!To measure (global) variability?
5.!To measure regional trends in quantity and quality?
6.!To determine the right way to measure in situ? To
replicate, calibrate satellites and parameterize models
7.!Provide an example based on OOI infrastructure
Societal drivers
pCO2
HOT
MB
pH
1992
2000
2009
How long (and where) do we need to measure i.e. Henson et al.
The Length of the Record is Important
Behrenfeld et al., Nature 2007
Locations where the full photosynthetic plankton community was
enumerated and sized by flow cytometry and microscopy
All stations collapsed into a single latitudinal profile
and the same done with SeaWiFS chlorophyll
PP = 0.66125 * PAR / (PAR+4.1) * Zeu * B0 * * DL
R=0.91 between
cruise data and
composite satellite
chlorophyll
Sum all of the
groups and estimate
~50 Petagrams
carbon per year
Diatom domination that transitions to pico-dominated offshore
Coastal out to
150 km ~16%
of global NPP
Coastal and open
ocean observing
systems quite
different
PP variability
•! Global climate variability during the
twentieth century from SST
•! Primary production over the past 20 years
from SeaWiFS, BATS, Cariaco, La Coruña
(Spain), HOT, MB and Peru
•! Looking to the past to learn something
about future changes in climate
•! Some thoughts about the future
The first four global modes of SST variability
El Niño/ La Niña
M1
M2
(Messie and Chavez, JClim)
Pacific Decadal Oscillation
M3
M4
Atlantic Multidecadal Oscillation El Niño Modoki/North Pacific Gyre
Past century
•! M1 = ENSO (high interannual and some
multidecadal energy)
•! M2 = AMO, longest period
•! M3 like but not the same as PDO
•! PDO = M1 + M3
•! M4 linked to North Pacific Gyre Oscillation
and El Niño Modoki (Modoki is Japanese
for like but not the same) – increasing in
amplitude, negative recently, recent El
Niño events more western than eastern.
Multidecadal variability and regime shifts,
same pattern in Pacific as recent cooling
Sardine demise
76 warm regime Recent cooling
This variability is associated with recent trends in SST y SLA
1981-2009
1993-2009
Major change around 97-98 and this regime shift largest in past century?
Terrestrial NPP
Global new production = 9.83
El Niño new production = 8.81
Delta ~ 1 gigaton/Pg C per year
About 30% of PP delta
Change due to nutricline 98%
Change due to winds 2%
Change in tropics 85%
Change at high latitudes 15%
Coherence with climate much less clear at (some) fixed point sites
1990 1995 2000 2005 2010
Scales of variability
•! Past century – ENSO, AMO, PDO, NPGO,
El Niño Modoki
•! Past 400-500 years – Medieval Warm
Period, Little Ice Age, the present – very
different than ENSO
•! THE Ice ages
•! Global warming – which of the above is
the most likely analog?
The biological pump: a complex process in an
ever-changing and moving ocean – not 1-D!
Follow a molecule
of CO2 from here
Or here
To here on a scale of
of hours to weeks
and eventually to years
Seafloor
A
Dream
A dream that today has very much a semblance of reality
How to measure primary, new,
community and export
production on global scales –
Ultimately we need to calibrate
satellites and models as well as
determine optimal in situ
measurement strategies
An example using the Pioneer array
•! Array may provide physical basis
to
•! Resolve budgets of carbon and
nutrients
•! Shipboard estimates of PP, NP
and EP by diverse methods
•! AUVs/gliders/floats/moorings
with carbon/nutrient sensors and
samplers/traps to provide
lagrangian perspective
•! Ultimate goal to develop
algorithms/parameterizations and
•!The next generation of
observatories – GBF-OOI
Conclusions
•! Climate variability and change have strong and measurable
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impacts on global ocean ecosystems –i.e. PP and
biogeochem
Anthropogenic global change (i.e. ocean acidification,
overfishing) exists without a doubt, climate change does as
well but anthropogenic climate change harder to pinpoint
How to best measure climate variability and change?
Three strategies:
Use fixed-point sentinel stations – need to pick carefully –
some for change, some for variability
Use fixed-point sentinel stations to develop optimal in situ
measurements – intercalibration experiments, develop
algorithms (AUVs/floats/satellites), model parameterization
Use well-calibrated satellites, ARGO floats/AUVs and models
for global estimates