Role of plankton functional diversity for marine ecosystem services
Supplementary Tables and Figure Captions
Table S1. Main model parameters constraining the resource limitations of growth rates. See the full
model equations in the separate supplementary document for a definition of the parameters.
PFT
Autotrophs
Nutrients half
saturationb
Light
αa
N2-fixers
1
θChl
gChl
gC-1
0.025
Picophytoplankton
1
0.033
4.6
10
0.13
2
Coccolithophores
1
0.033
6.0
25
0.13
2
Mixed phytoplankton
1
0.033
6.0
25
0.1
2
Phaeocystis
1
0.042
8.6
25
0.8
3
Diatoms
1
0.058
8.6
40
0.06
2
Feopt
μmolFe
molC-1
8.6
KFe
KP
KN
μmol L-1
μmol L-1
μmol L-1
40
0.2
13
Heterotrophs
Food half
saturation
KFood
μmol L-1
Bacteria
10
Protozooplankton
6
Mesozooplankton
10
Macrozooplankton
a
-1
20
2
units: gC gChl m (mol photons)-1
b
The reported values are half saturation for uptake for Fe, and half saturation for growth for P and N.
Table S2. Relative preference of zooplankton for food. The preferences are weighted with the biomass
to obtain the model parameter value as in [1].
Plankton Functional Type
Protozooplankton
Mesozooplankton
Macrozooplankton
2
0.1
0.1
Picophytoplankton
2
0.75
0.1
Coccolithophores
2
0.75
1
Mixed phytoplankton
2
0.75
1
Phaeocystis
2
0.75
1
Diatoms
1
1
1
Bacteria
4
0.1
0.1
Protozooplankton
0
2
1
Mesozooplankton
0
0
1
Macrozooplankton
0
0
0
Small organic particles
0.1
0.1
0.1
Large organic particles
0.1
0.1
0.1
Autotrophs
N2-fixers
heterotrophs
Particulate matter
Table S3. Global mean values for rates and biomass for PlankTOM10 averaged over 1998-2009.
Model
Data
Confidencea
Reference
38.2
38-55
high
Buitenhuis and Le Quéré (in prep.)
Export production (100 m)
7.3
9-10
high
Schlitzer (2002); Lee (2001)
CaCO3 export (100 m)
0.7
0.6-1.1
high
Lee (2001); Sarmiento et al. (2002)
SiO2 export (100 m; Tmol Si)
82
120
high
Treguer et al. (1995)
0.28
medium
Rates (PgC y-1)
Primary production
Phytoplankton biomasses 0-150bm (PgC)
N2-fixers
0.049
Picophytoplankton
0.16
Coccolithophores
0.093
Mixed phytoplankton
0.084
Phaeocystis
0.076
Diatoms
0.081
Heterotrophic biomasses 0-300bm (PgC)
Bacteria
0.071
Protozooplankton
0.060
Mesozooplankton
0.40
Le Quéré et al. (2005) based on Uitz et
al. (2006)
0.39
medium
0.11
medium
?
0.24
(0.14-0.33)
0.16
?
Rivkin and Legendre (2002)
medium
Buitenhuis et al. (2010)
medium
Buitenhuis et al. (2006)
Macrozooplankton
0.086
Authors’ assessment of confidence. High: most likely within ± 25% of reported value; medium: most likely within ± 50%
of reported value; low: could be more than ± 50% of reported value.
b
Biomass data is integrated down to 150 m for phytoplankton PFTs and to 300 m for heterotrophs, which corresponds
approximately to the depth levels reported in the observations.
a
Table S4. Average chla concentration from satellite data and from model results for the Pacific Ocean.
The data are averaged between latitudes 40 and 50° in both hemispheres, and longitudes 140 and
280°E in the Pacific sector of the Southern Ocean.
SeaWiFS
PlankTOM10
PlankTOM6
0.58
PlankTOM10
–mac1
0.66
PlankTOM6
+mac2
0.49
PlankTOM10
mac=mes3
0.27
PlankTOM6
mes=mac4
0.29
North
0.49
0.48
South
0.22
0.25
0.46
0.49
0.27
0.26
0.12
Ratio
2.2
1.9
1.3
1.3
1.8
1.0
2.4
1
Same as the PlankTOM10 model but without macrozooplankton.
1
Same as the PlankTOM6 model but with macrozooplankton.
1
Same as the PlankTOM10 model but with the parameterisation of macrozooplankton identical to that of mesozooplankton.
2
Same as the PlankTOM6 model but with the parameterisation of mesozooplankton identical to that of macrozooplankton
in PlankTOM10.
Supplementary Figure captions:
Figure S1. Dominance of picophytoplankton (top), haptophytes (middle) and diatoms (bottom) in the
ocean surface. Left panels show the frequency dominance of each PFT (i.e. fraction of time present)
derived from satellite data by Alvain et al. (2005) for each pixel during 1998-2006. Right panels show
model results as a fraction of surface chla for each PFT in total chla. For the model results,
picophytoplankton include both the picophytoplankton and N2-fixers groups; haptophytes include
coccolithophores, DMSp-producers and mixed phytoplankton. In the model, a PFT is assumed
dominant if it accounts for at least 45% of the biomass for picophytoplankton and haptophytes, and
30% of the biomass for diatoms.
Figure S2. Frequency (i.e. fraction of time present) of blooms of Phaeocystis (top) and
coccolithophores (bottom) in the surface ocean. Phaeocystis values are from Alvain et al. (2005);
coccolithophore blooms are updated from Brown and Yoder (1994). A bloom is defined in the model
as the PFT accounting for at least 30% of the biomass and when chla exceeds 0.3 mgChl/m3.
Figure S3. Taylor diagramme comparing the statistical characteristics of biomass, nutrients and rates
from the PlankTOM 10 model (Y-axis???) with those of observations (X-axis ???). Chla, biomass and
nutrient observations are as in Figure 2; other PFT biomass data are from Alvain et al. (2008); primary
production is from Buitenhuis et al. (subm); export production from Schlitzer (2004).
Figure S4. Covariance between model and observed total chlorophyll and limiting nutrients (left) and
bacteria and zooplankton biomass (right). The red line is from the standard PlankTOM10 model. The
blue line represents a sensitivity test where the mortality of mesozooplankton is doubled, and their
temperature dependence is increased from Q10 = 1.8 to 3.0. The black line and the shaded area are the
median and 25-75% range of observations, respectively, from Figure 2.
Figure S5. Histogramme of the distribution of annual mean surface chlorophyll on a 1x1 global grid
for (a) SeaWiFS data, (b) PlankTOM10, (c) PlankTOM5+, and (d) PlankTOM4+. All data are averaged
over the 1998-2008 time period.
Figure S6. Latitudinal distribution of mean of surface chla from SeaWiFS data (black), and the
PlankTOM10 (red) and the PlankTOM5+ (cyan) models.
Figure S7. Concentrations of carbon in living organic pools in the PlankTOM10 model (μmol L-1) and
fluxes of carbon between pools (μmol C L-1 yr-1) for (top) the North and (middle) the South Pacific
Oceans, and (bottom) the ratio of the two. The average values are calculated between latitudes 40 and
50° in both hemispheres, and longitudes 140 and 280° in the Pacific sector of the Southern Ocean.
Figure S8. Sensitivity study of the change in primary production (PgC yr-1) induced by different
phytoplankton PFTs (pPFTs). In the first experiment (left), one pPFT is added to a model that already
includes two pPFTs (diatoms and picophytoplankton). Each simulation is shown with a symbol
corresponding to the pPFT added (see legend on graph). In the second experiment (middle), one pPFT
is added from a model that includes five pPFTs (i.e. the six in PlankTOM10 minus the one added).
These experiments are corrected to account for the numerical effect of changing the number of pPFTs
by using picophytoplankton as reference. In the third experiment (right), all pPFTs except diatoms are,
in turn, parameterized the same way, hence removing most of the pPFT diversity. This last simulation
is not performed for N2-fixers due to the numerical difficulty of including N2-fixation for all tracers.
All simulations exclude macrozooplankton to limit changes in model structure between the
simulations. All simulations are run for five years; the average of the last three years is shown.
Figure S9. Sensitivity study of the effects of changes in growth rates of proto- and mesozooplankton
on marine ecosystem supporting services using the standard PlankTOM10 model (full lines) and
sensitivity test shown in Figure S4 (dashed lines).
1.
Buitenhuis, E.T. and R.J. Geider, A model of phytoplankton acclimation to
iron-light colimitation. Limnology and Oceanography, 2010. 55(2): p. 714724.