0.6
r
-2
ln.r
ln.r
-4
-3
0.4
-3
Temperature and phytoplankton: disentangling empirical paAerns and compe5ng paradigms. -5
0.0
-4
0.2
1
2
3
4 Colin T. Kremer , Mridul K. Thomas , Elena Litchman , Charles Stock
1Yale U38
2EAWAG: 4NOAA Geophysical Fluid Dynamics Laboratory 39
40
41
42
5
15
20 Science 25
30 and 35 Technology, 53Michigan 10
15 S20
30
35
niversity, Swiss Federal InsUtute o10f AquaUc tate 25University, temperature
39
40
41
42
5
10
inv.kT
Func5onal form E = 0.405 eV, E = 0.304 eV b = 0.0631 b = 0.0474 E = 0.32 eV, E = 0.31 eV b = 0.0498 b = 0.0428 bT
Eppley µmax = ae
MTE E
µmax ⇡ µ0 exp
T
2
kT0

p < 0.001 p < 0.001 -2-2 -1-1 0 0 1 1 2 2 3 3 4 4 5 5
-2 -1 0 1 2 3 4 5
Growth rate, d-­‐1 30
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20
-2
22
11
00
-1-1
-2-2
-1-1
11
1
00
0
-2-2
-2
-1-1
-1
-1
0 rate
ln(Growth
ln(Growth
rated1d) )
2
22
2
25
30
37
Temperature temperature (C) 38
35
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3737 3838 3939 4040 4141 4242
41 37
42 38 39 40 41 42
-15
1/(kT) Temperature (1/kT)
Temperature (1/kT)
References Scaling relaUonships esUmated using quanUle regression (Eppley curve), and mulUple linear regression (MTE). For clarity, only diatoms are shown. Eppley 1972 Bissinger et al. 2008 Savage et al. 2004 Allen et al. 2005 Tmax ln(Growth rate) ln(Growth rate d )
-1-1
ln(Growthrate
ratedd-1) )
ln(Growth
-2
35
Temperature(1/kT)
(1/kT)
Temperature
2
Total Z (prod)
-5
-5 -5
0
00
ln(biovolume, μm3) ln(mass,
ug)
ln(mass,
ug)
ln(mass, ug)
COBALT Ecosystem model The effects of climate change on plankton depend on constraints and rates of evoluUon. We explored several sTrophic
cenarios within a(productivity
global ecosystem model. responses
& biomass)
Total P (prod)
-15
-10
-15 -10 -10
Growth rate scales with temperature and cell size. FuncUonal groups have idenUcal slopes, but different intercepts. The temperature effect agrees with theory, but the size effect is weaker than predicted. Climate change & Constraint Bacteria (prod)
1
0
−1
−2
10
1010
20
2020
30
3030
Temperature (C) 40
4040
Temperature (C)
Temperature(C)
(C)
Temperature
Growth rates do not increase indefinitely as temperatures rise. Standing trait variaUon for toleraUng high temperatures is constrained. We quanUfied this limit using the thermal tolerance curves of >150 phytoplankton species. −3
Total P (prod)
0.02
Total P (biomass)
2
0.01
1
0.00
0
−1
−2
−3
Total Z (prod)
Bacteria (prod)
Total Z (biomass)
Z&P
Bacteria (biomass)
% change in total P biomass
just Z
% change
−0.01
−0.02
Groups
Constrained
−0.03
0.02
Total P (biomass)
Total Z (biomass)
Z&P
Bacteria (biomass)
just Z
0.01
0.00
LN
N
EN
LN
N
EN
−0.01
Ques5ons? [email protected] N export
El Nino State
−0.02
−0.03
LN
N
EN
LN
N
EN
LN
N
EN
LN
N
EN
50
Latitude
0
00
Groups
Stock et al. 2014 Constrained
Trophic responses (productivity & biomass)
% change relative to control
Growth
Growthrate
rate
Growth rate
25
temperature
Constraints to growth at high temperatures Topt 20
% change
Theory Different Predic5ons Es5mates from Eppley? 15
diatoms
greens
cyanos
dinos
0
-2
38
2
0
-1
ln(Growth rate d )
4
3
2
1
r
Growth rate (day-­‐1) 2
MTE
linear
50th Q
95th Q (linear)
95th Q (direct)
Eppley
-2
-1
0
ln.r
-1
ln.r
0
1
1
2
Two paradigms describe the scaling of maximum growth rates with temperature, the Eppley curve and Metabolic Theory (MTE). MTE predicts that maximum growth rates are constrained by size and the acUvaUon energy of photosynthesis. The phenomenological Eppley curve predicts a steeper increase. We use a database of phytoplankton growth rates and sizes to test these compeUng theories. MTE analyses support a weaker temperature scaling of growth rate, consistent with theory. Eppley analyses agree with MTE, but only when we account for differences between the growth capacity of funcUonal groups. MTE fit by funcUonal group MTE on Eppley
axes,
Eppley vs. Mmultiple
TE regr.
1
multiple r
regr.
Hybrid,
multiple regr.
Phytoplankton gMTE
rowth ates scale with size, temperature ln(Growth rate d-1)
temperature
-1
inv.kT
4
0
0
−4
−50
−200
−100
Longitude
0