trait trade offs and cell size for ocean ecosystem modeling stephanie dutkiewicz and mick follows...
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TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM
MODELING
Stephanie Dutkiewicz and Mick FollowsMassachusetts Institute of Technology
Darwin Project People:Oliver JahnJason BraggFanny MonteiroAnna HickmanBen Ward
Penny Chisholm Andrew BartonChris KempesSophie ClaytonChris Hill
“Everything is everywhere, but, the environment selects” Lourens Baas-Becking
genetics
physics,nutrient
communitystructure
TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING
OUTLINE OF TALK:• Trait-based ecology framework• Example from our ecosystem model: Trade-offs are key!• Size as “master” trait – a brief review• Models with explicit size spectrum – a brief review• Preliminary results from MIT self-organizing ecosystem model• Where next …
(from Litchman+Klausmeier, 2008)
TRAIT-BASED APPROACH TO ECOLOGY
HOW DO THESE TRAITS TRADE OFF AGAINST EACH OTHER?
• Competitive ability for different resources - diatoms (Fe versus light) - diazotrophs (N versus Fe)
• Grazer resistance and nutrient acquisition
• Maximum growth rate and nutrient acquisition: - K versus r strategy (gleaners/opportunists)
(from Litchman and Klausmeier)
HOW DO THESE TRAITS TRADE OFF AGAINST EACH OTHER?
• Maximum growth rate and nutrient acquisition: - K versus r strategy (gleaners/opportunists)
K strategy (gleaner): optimize for low nutrient requirements
r strategy (opportunist): optimize for fast growth rate
Test this is a numerical simulation
(see: MacArthur+Wilson, 1967 Kilham+Kilham, 1980)
TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING
OUTLINE OF TALK:• Trait-based ecology framework• Example from our ecosystem model: Trade-offs are key!• Size as “master” trait – a brief review• Models with explicit size spectrum – a brief review• Preliminary results from MIT self-organizing ecosystem model• Where next …
P1
P
● initialize with many potentially viable organism types and interactions● parameters (rates) are chosen
randomly within a reasonable range● allow the system to self-organize … Pi
PjPPPn
NZ1
D
Z2
N
D
Z2Z1
competitionpredationselection
physical and chemical
environment
genetics andphysiology
SELF ORGANIZING ECOSYSTEM MODEL(Follows et al, 2007)
choices and trade-offs on growth parameters
•biogeochemical cycling of N, P, Si, Fe
•78 phytoplankton•2 zooplankton classes
opportunists(r-strategy)
gleaners(K-strategy)
SELF ORGANIZING ECOSYSTEM MODEL(Follows et al, 2007)
high max growth rate
low nutrient half saturation
(Dutkiewicz et al, GBC – submitted http://ocean.mit.edu/~stephd)
biomass of opportunists/total biomass
gleaner(low nutrient requirementsmatter)
opportunists(fast growth matters)
10th yearannual 0-50m mean
RESULTS FROM NUMERICAL SIMULATION: IMPORTANCEOR BIOGEOGRAPHY
(from Dutkiewicz et al, GBC – submitted http://ocean.mit.edu/~stephd)
ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPEred/yellow=opportunists, green/blue=gleaners; opacity=total biomass
Oliver Jahn
ECCO2 MODEL WITH ECOSYSTEM: DOMINANT FUNCTIONAL TYPEred/yellow=opportunists, green/blue=gleaners; opacity=total biomass
(from Litchman+Klausmeier, 2008)
Trade-offs are the key!
Trade-offs are the key!
(from Litchman+Klausmeier, 2008)
How to model these in a consistent manner?
“Size is the most structuring dimension of ecological systems” (Maury et al, 2007)
• consistent regulation of trade-offs (hopefully)
• closer interface with spectral resolution of remotely-sensed data - e.g. particle back-scattering
BENEFITS OF USING CELL SIZE AS A “MASTER” TRAIT:
TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING
OUTLINE OF TALK:• Trait-based ecology framework• Example from our ecosystem model: Trade-offs are key!• Size as “master” trait – a brief review• Models with explicit size spectrum – a brief review• Preliminary results from MIT self-organizing ecosystem model• Where next …
CELL SIZE INFLUENCES:• Metabolic rates and Maximum growth rates• Nutrient acquisition• Chl content and Light absorption• Sinking speeds• Maximum and minimum cell quota• and ….
many of the above are related tocell size by, where S can be V,C,r:
baSX
CELL SIZE INFLUENCES:• Metabolic rates and Maximum growth rates
Bigger phytoplankton grow slower
(from Tang 1995)
growth rate versus cell sizebaVmax
25.0b
• b=-0.25 appears to work over very large range of scales (Platt and Silvert, 1981; West et al 2002)• but b has been found between -0.15 and -0.3 but various studies (Chisholm 1992)
Chris’s work
Kempes et al(in prep)
data from Chrisholm et al (1992)
theoreticalcurve (m-1/4)
CELL SIZE INFLUENCES:• Nutrient acquisition
Bigger phytoplankton require more nutrients
(from Litchman et al, 2007)
half saturation for nitrate versus cell volume
bn aV 33.0b
rate at which molecular diffusionsupplies nutrients to the surfaceof the cell(Aksnes+Egge, 1991; Munk+Riley, 1952 )
(from Chisholm, 1992)
CELL SIZE INFLUENCES:• Chl content and Light absorption
(from Ciotti et al, 2002)
intercellular Chl a versuscell diameter
Bigger phytoplankton absorb light less efficiently
absorption spectra normalized by Chl-a and phaeopigments
(from Finkel et al, 2004)
“packaging effect”
CELL SIZE INFLUENCES:• Sinking speeds
Bigger phytoplankton sink quicker
(from Smayda,1970)
bp arw
17.1b Stokes Law suggest b=2
SO WHY ARE THERE ANY BIG CELLS:• Grazing Pressure - e.g. Thingstad et al 2005
• Susceptibility to Viruses - e.g. Raven et al 2006
• Respiration/Loses - e.g. Laws 1975
• Photo-inhibition
– e.g. Raven et al 2006
• “Luxury quota”• Taxonomically related advantage
SO WHY ARE THERE ANY BIG CELLS:• “Luxury quota”
Scaling of size dependent parameters: X=aSb
gro
wth
ra
te
size
ANALYTICAL MODEL OFVERDY ET AL, MEPS, 2009
SO WHY ARE THERE ANY BIG CELLS:• Taxonomically related advantage
SIZE RELATIONSHIP NOT SO GROWTH CLEAR:(e.g. Chisholm 1992, Raven et al, 2006)
especially for picoplankton e.g. (<1um) Prochloroccus 1 d-1
(4um) Thalassiosira spp. 3 d-1
(from Chisholm 1992)
SO WHY ARE THERE ANY BIG CELLS:• Taxonomically related advantage
(from Irwin et al, 2006)
25.0max
aV
SO WHY ARE THERE ANY BIG CELLS:• Taxonomically related advantage
(from Irwin et al, 2006)
Irwin et al, 2006b=-0.25
Baird, 2008b=-0.15
baVmax
TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING
OUTLINE OF TALK:• Trait-based ecology framework• Example from our ecosystem model: Trade-offs are key!• Size as “master” trait – a brief review• Models with explicit size spectrum – a brief review• Preliminary results from MIT self-organizing ecosystem model• Where next …
NUMERICAL MODELING WITH SIZE AS TRAIT:
some examples-Baird and Sutherland (2007) -Maury et al. (2007)-Stock et al (2007)-Mei, Finkel and Irwin (in prep)
Baird+Sutherland, J. Plankton Res (2007)
(from Baird+Sutherland, 2007)
Schematic of size-resolved biology model
<1um
78mm
Phytoplankton size determines: carbon content/growth/sinking/half saturation/swimming/predation
Maury et al, Prog. Ocean, 2007
Size-dependent physiology and metabolism, using the Dynamic Energy Budget theory (Kooijman, 2001)
Based on Droop’s Growth Model,3 classes of plankton
run in global 3-D MITgcm setup
Phytoplankton size determines: cell quota/growth/uptake/half saturation/mortality
currently adding size-dependent grazing
TRAIT TRADE OFFS AND CELL SIZE FOR OCEAN ECOSYSTEM MODELING
OUTLINE OF TALK:• Trait-based ecology framework• Example from our ecosystem model: Trade-offs are key!• Size as “master” trait – a brief review• Models with explicit size spectrum – a brief review• Preliminary results from MIT self-organizing ecosystem model• Where next …
SELF ORGANIZING ECOSYSTEM MODEL(Follows et al, 2007)
modified Dutkiewicz et al 2009, Monteiro et al, Hickman et al
opportunists gleaners
10’s to 1000’s phytoplankton “types”:choices and trade-offs on growth parametersT, I, nutrients
decision tree on initialized phytoplankton
SELF ORGANIZING ECOSYSTEM MODEL
SIZE SPECTRUM VERSION
10’s to 1000’s phytoplankton “types”:choices and trade-offs• size: growth parameters, nutrient half-saturation, sinking rates grazing
• T, I, types of nutrients
decision tree on initialized phytoplankton
Si No-Si
NH4, NO2, NO3
Diatomanalogues
Non-diatom eukaryoteanalogues
NH4, NO2, NO3
NH4, NO2
NH4
Pico-Eukaryote analogues
HL Prochl.analogues
LL Prochl.analogues
Synechococcusanalogues
SIZE SPECTRUMbigger smaller
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
cell diameter (um)
P – ProchloroccusS – SynochcoccusA – diazotrophC – coccolithophersF - dinoflagellatesD – diatoms
17.16.5 rwp
33.01.0 Vp
25.0max
aV“a” has taxanomicdifferences(following Irwin et al, 2006)
(Smayda, 1970)
(Irwin et al, 2006)
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
gra
zin
g r
ate
SIZE DEPENDENT GRAZING(following Baird+Sutherland 2007)
529.0max 00271.0 zrg
min predator-prey ratio: 3.0max predator-prey ratio: 22.6(parameters from Hansen et al 1994,1997)
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
1-D SIMULATION(S. Atlantic subtropical gyre)
green: <1miconcyan: 1-2 micronsblue: 2-3 microns
nitratephytoplanktonbiomass
de
pth
(m)
(100 plankton types, no temp, light or grazing differences in this version)
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
1-D SIMULATION(S. Atlantic subtropical gyre)
green: <1miconcyan: 1-2 micronsblue: 2-3 microns
(100 plankton types, no temp, light or grazing differences in this version)
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
1-D SIMULATION(S. Atlantic subtropical gyre)
green: <1miconcyan: 1-2 micronsblue: 2-3 microns
nitratephytoplanktonbiomass
de
pth
(m)
(100 plankton types, no temp, light or grazing differences in this version)
SELF ORGANIZING ECOSYSTEM MODELSIZE SPECTRUM VERSION
3-D SIMULATION:PRELIMINARY RESULTS
(78 plankton types, no temp, light in this version)
total biomass (uM)
biomassweightedcell diameter (um)
nitrate (uM)
cell diameter (um)
gro
wth
ra
te (
1/d
)
WHERE WE ARE GOING:
• continuous size spectrum determining many of the rates/parameters• quota based • pigment specific light absorption (with Anna Hickman, see poster)• explicit radiative transfer model (with Watson Gregg)• run in the eddy-permitting ECCO2 framework
ECCO2 with 78-phytoplankton self-organizing model
Oliver Jahn
ECCO2 with 78-phytoplankton self-organizing model
Oliver Jahn
WHERE WE ARE GOING:
• continuous size spectrum determining many of the rates/parameters• quota based • pigment specific light absorption (see poster)• explicit radiative transfer model• run in the eddy-permitting ECCO2 framework
SELF ORGANIZING ECOSYSTEM MODEL
modified Hickman et al
10’s to 1000’s phytoplankton “types”:choices and trade-offs on growth parametersT, I, nutrients
decision tree on initialized phytoplankton
Large Small
Si No-Si
NH4, NO2, NO3
Diatomanalogues
Non-diatom eukaryoteanalogues
NH4, NO2, NO3
NH4, NO2
NH4
Pico-Eukaryote analogues
HL Prochl.analogues
LL Prochl.analogues
Synechococcusanalogues
* = m . a*from absorption spectra
ADDITIONAL OF PIGMENT SPECIFIC ABSORPTION SPECTRA
see poster