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EPOCA WP9:EPOCA WP9:From process studies to From process studies to
ecosystem modelsecosystem 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
low PIC prod.
high T
high PP, fast microbial loop
large PIC prod.
irrespective of nutrient supply, export production, grazing…
low PIC export large PIC export
Example: calcification & temperatureUVic model: temperature dependence helps to get
latitudinal distribution of rain ratio “right”:
(Schmittner et al., 2008)
Example: calcification & temperature
Does this give meaningful results in global-warming runs?
PICprod
PICprodPP
EP
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
experiments models
Efficient knowledge transfer
Feedback to efficiently reduce uncertainty
Approach1. Analysis
experiments models
Coherent data base(organisms, ecosystems)
Meta-analysis(mesocosm, microcosm)
Meta-analysis(model assumptions,parameterisations)
T9.1
T9.2
T9.3
Approach2. Modelling of micro- and mesocosm experiments
2. Model improvement: balance complexity, performance, portability
3. Assessment and recommendations for incorporation into global-scale modelsexperiments models
Data-assimilative parameter estimation 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 1Calibration by chemostat/turbidostat data
(Pahlow & Oschlies, subm.)
Chain model of N, P, light colimitation
Example 2Calibration by mesocosm data
(Schartau et al., 2007)
Example 3: Transfer to global models
350 ppm700 ppm1050 ppm
(Riebesell et al., 2007) (Oschlies et al., subm.)
50% increasein suboxicvolume(<5mmol/m3)
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?