EPOCA WP9:
From process studies to
ecosystem models
Participants involved:
LOV, UiB, IFM-GEOMAR, GKSS, KNAW,
UGOT, UNIVBRIS
(a.o. J.-P. Gattuso, R. Bellerby, M. Schartau, J.
Middelburg, A. Oschlies)
Motivation:
Current parameterisations of
calcification
• PIC prod. ~ Prim.Prod. (of some PFT,
possibly modulated by )
• PIC prod. ~ Detritus prod.
• Essentially all current parameterisations
employ Eppley’s temperature dependence.
Calcification & temperature
(according to current models)
low T
low PP, slow microbial loop
high T
high PP, fast microbial loop
low PIC prod.
large PIC prod.
low PIC export
large PIC export
irrespective of nutrient supply, export production, grazing…
Example: calcification & temperature
UVic model: temperature dependence helps to get
latitudinal distribution of rain ratio “right”:
(Schmittner et al., 2008)
Example: calcification & temperature
PICprod
PICprod
PP
EP
Does this give meaningful
results in global-warming
runs?
Increase in PIC production
closely linked to
temperature-driven
increase in Prim.Prod.
(Schmittner et al., 2008)
General problem with empirical models
• May work well under empirical conditions
• No guarantee that this will continue under
new environmental conditions
– higher temperatures
– higher CO2
–…
Aim for mechanistic models
Objectives
• Integration & Synthesis
Efficient knowledge transfer
experiments
models
Feedback to efficiently reduce uncertainty
Approach
1. Analysis
experiments
Coherent data base
T9.1 (organisms, ecosystems)
T9.2
Meta-analysis
(mesocosm, microcosm)
models
Meta-analysis
(model assumptions, T9.3
parameterisations)
Approach
2. Modelling of micro- and mesocosm experiments
experiments
models
Data-assimilative parameter estimation
2. Model improvement: balance complexity,
performance, portability
3. Assessment and recommendations for
incorporation into global-scale models
T9.4
T9.5
T9.6
Deliverables
• D9.1: advice/guidance: data
storage/documentation/protocol (month 2, R, PU)
• D9.2: structured data base (month 12, R, PP)
• D9.3: Mesocosm meta-analysis, guidance to future
experiments (month 12, R, PP)
• D9.4: Identification of physiological/ecological processes
that contribute most to uncertainties in ecosystem models
(month 24, R, PU)
• D9.5: Improved model formulation for pH-sensitive
processes -> Earth system models (month 40, R, PU)
• D9.6: Uncertainty analysis (month 48, R, PU)
Example 1
Calibration by chemostat/turbidostat data
Chain model of N, P, light colimitation
(Pahlow & Oschlies, subm.)
Example 2
Calibration by mesocosm data
(Schartau et al., 2007)
Example 3:
Transfer to global models
350 ppm
700 ppm
1050 ppm
(Riebesell et al., 2007)
50% increase
in suboxic
volume
(<5mmol/m3)
(Oschlies et al., subm.)
Questions from model study
& feedback to experimentalists
• Temperature effects vs. pH effects?
• Observational evidence of pCO2-sensitive C:N
ratios in the ocean?
• What is the mechanism for export of excess C?