1. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Adjusting a global ecosystem model for local performance – calibration and sensitivity analysis of BIOME-BGC in Switzerland N.E. Zimmermann WSL

2. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Scaling carbon fluxes from stands to landscapes: calibrating and testing BIOME-BGC along multiple environmental gradients

3. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses The Biome-BGC Terrestrial Ecosystem Process Model Biome= an area characterized by its flora, fauna, and climate BGC= BioGeochemical Cycles The model uses a daily time-step. Flux (and pools) are estimated for a one- day period. Between days, the program updates its memory of the mass stored in different components of the vegetation, litter, and soil. Weather is the most important control on vegetation processes. Flux estimates in Biome-BGC depend strongly on daily weather conditions. Model behavior over time depends on the history of these weather conditions, the climate.

4. New leaf growth and old leaf litterfall Sunlight interception by leaves, and penetration to the ground Precipitation routing to leaves and soil Snow accumulation and melting Drainage and runoff of soil water Evaporation of water from soil and wet leaves Transpiration of soil water through leaf stomata Photosynthetic fixation of carbon from CO 2 in the air Uptake of nitrogen from the soil Distribution of carbon and nitrogen to growing plant parts Decomposition of fresh plant litter and old soil organic matter Plant mortality Fire Biome-BGC is a computer program that estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. It is a process model because its algorithms represent physical and biological processes that control fluxes of energy and mass. These processes include: Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

5. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

6. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

7. Biome: required meteorological inputs Daily maximum temperature (°C) Daily minimum temperature (°C) Daylight average temperature (°C) Daily total precipitation (cm) Daylight average partial pressure of water vapor (Pa) Daylight average shortwave radiant flux density (W/m 2 ) Daylength (s) In many cases, the only data available for a particular site are daily Tmin/Tmax and Prec. The model MT- CLIM can then be used to derive estimates of the other required meteorological parameters. Biome: required soils inputs: % clay, silt, sand Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

8. Site Characteristics Meteorological inputs Maximum temperature Minimum temperature Precipitation Radiation Humidity/ VPD Soil characteristics Ecophysiological Parameters Biome properties Leaf/Litter/Wood chemistry & characteristics ( C:N, SLA, lignin, cellulose, etc. ) Photosynthetic characteristics Allocation rules Turnover rates etc. BIOME-BGC BIOME-BGC input Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

9. Biome properties Phenology info Turnover info Mortality info Allocation rules C:N ratios Decomposition info Canopy/leaf info Leaf physiology Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

10. BIOME-BGC output Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses NPP [kgC/m 2 ] Net Primary Productivity for Othmarsingen, 1931-2001

11. < BIOME-BGC output Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses NPP [kgC/m 2 ] Net Primary Productivity for Othmarsingen, 1931-2001

12. Net Primary Productivity (NPP) [kgC/m 2 ] Net Primary Productivity for Missoula, Montana 1994 BIOME-BGC output Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

13. < BIOME-BGC output Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Net Primary Productivity for Othmarsingen, 1998 kgC/m 2

14. < BIOME-BGC output Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Net Ecosystem Exchange for Othmarsingen, 1998 kgC/m 2

15. Concept & state of the Swiss Biome-BGC project Calibrate and thoroughly test the Biome-BGC model for Swiss forests along multiple environmental gradients A Test the hypothesis of increased tree growth in Central European forests in the decade of 1991 to 2000 compared to earlier decades. B Testing MODIS-MOD17 (NPP/GPP) data on the same test sites ( calculated using the Biome-BGC logic, but based on RS inputs, partly ) C Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

16. Calibration and test sites Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

17. Project work flow and progress Test data LWF sites stand level data, structure, mass leaf chemistry, mass intra-annual growth rates soils & roots data Calibration data C:N of leafs, roots, wood leaf-level physiology C-partitioning decay rates, etc. Test model testing against field data sensitivity analyses Run simulations past 4 decades, test w| tree rings test set of hypotheses test effect of scale & resolution Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

18. progress Project work flow and progress Test data LWF sites stand level data, structure, mass leaf chemistry, mass intra-annual growth rates soils & roots data Calibration data C:N of leafs, roots, wood leaf-level physiology C-partitioning decay rates, etc. Test model testing against field data sensitivity analyses Run simulations past 4 decades, test w| tree rings test set of hypotheses test effect of scale & resolution Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

19. Calibration & test data preparation The following data were primarily collected in the field C:N of sunlit/shaded leafs & stem wood A/Ci curves of sunlit (some shaded) leafs Sunlit and Shaded leafs SLA Leaf phenology (flush, drop) of deciduous trees Number of needle years (needle turnover fraction) Wood/tree cores for inter-/intraannual growth and density People involved: Matt Jolly, Theo Forster, Stéphanie Schmid, Markus Schaub, Dani Nievergelt, Paolo Cherubini, Peter Suter, Werner Schoch, Matthias Dobbertin, Norbert Kräuchi, Felix Kienast, Dmitry Golikov, Lorenz Waltert, Stefan Zimmermann, Gustav Schneiter, Peter Jakob, etc. etc. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

20. Vcmax:Maximum carboxylation rate (=PS-rate) lnc:Leaf nitrogen content (from C:N and SLA) flnr:Fraction of leaf nitrogen in Rubisco fnr:Rubisco nitrogen fraction (enzyme structure) act:enzyme activity of Rubisco Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses  valid if stomatal resistance is minimal Calibration & test data preparation Leaf physiology

21. (lnc) x (flnr) x (fnr) x (act) = (Vcmax) Area-based leaf N concentration = 1/ (SLA C:N leaf ) Rubisco activity = f(T leaf ) Maximum rate of photosynthesis (determined from fit to AC i curves) Determined from protein structure Leaf physiology Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

22. Leaf physiology Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses constant 1/ (SLA C:N leaf ) AC i curves

23. Beauty and pain of field work - Vc max Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

24. Beauty and pain of field work – SLA / C:N Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

25. Leaf physiology Lapse Rate  Vcmax Plateau  Jmax &/or TPU Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

26. useless data.... Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation Leaf physiology

27. Wc = Vcmax; Maximum rate of carboxylation by RuBisCO (CO 2 limitation) Wj = Jmax; RuBP-Regeneration (electron transport limitation) Wp = Regeneration of inorganic phosphate; (TPU-limitation) A/Ci curves are analyzed using the Photosyn Assistant software [Dundee Scientific, UK] Param Est. SE Resp 1.533.38E-01 Vcmax 57.51.12E+00 Jmax 1894.38E+00 TPU 12.21.83E-01 CO2 comp. est. (from Wc) = 5.13 Sy.x = 6.10E-01 DF= 8 Iteration count 2014 SSqs 2.98 Example output: Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation Leaf physiology

28. Modified Farquhar (1980) photosynthesis eqn.: Where, e.g.: Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation Leaf physiology internal CO 2 concentration internal O 2 concentration Michaelis-Menten constants of Rubisco for CO2 and O2 respiration other than photorespiration

29. Calibration of C:N for Fagus sylvatica Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

30. Calibration of SLA for Fagus sylvatica Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

31. Calibration of FLNR for Fagus sylvatica Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

32. Vcmax seasonal pattern: Fagus sylvatica Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Calibration & test data preparation

33. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses How much do simulations differ with locally optimized parameters compared to the global DBF parameter set? 1 How sensitive is the model with respect to the accuracy of the measured parameters? 2 These questions are mostly analyzed by evaluating effects on carbon and nitrogen pools (not so much fluxes). Most variables varied 5-15% between sites.

34. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Set up for sensitivity analyses Aannual whole plant mortality fraction BC:N of leaves CC:N of live wood DC:N of dead wood Edead wood lignin/cellulose proportion Fcanopy light extinction coefficient Gcanopy average SLA Hratio of shd:sun SLA Ifraction of leaf N in Rubisco JB & G & H at the same time KB & G & H & I at the same time Lsoil depth Msand proportion in soil each variable was increased by 5% and by 15% respectively

35. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results Othmarsingen (C-Pool)

36. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results Othmarsingen (N-Pool)

37. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results Othmarsingen (C-Pool, change)

38. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results Othmarsingen (N-Pool, change)

39. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results Lausanne (C-Pool, change)

40. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Summary-1 The accuracy of the measured parameter has a clear impact on the model simulations. 1 C:N ratio’s have a higher impact in Othmarsingen, where soils are shallow(er) and less rich. 2 Mortality and soil parameters are additionally important. 3

41. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses How does the sensitivity of parameters change across environmental gradients? 1 Do different parameters behave differently? 2

42. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Distribution of F. sylvatica in the environmental space

43. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Set up for 2 nd sensitivity analyses Aannual whole plant mortality fraction BC:N of leaves Gcanopy average SLA Ifraction of leaf N in Rubisco each variable was increased by 15% on each plot and compared to the standard calibration Soil parameters (sand, silt, clay, soil depth) are kept constant The climate of Othmarsingen is linearly adjusted for temperature and/or precipitation for each lattice point in order to exclude the effect of climate seasonality

44. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Simulation results for Tave=7.0; Prcp=850mm

45. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Climate effects on Veg-C

46. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Climate effects on Soil-C

47. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Sensitivity along env. gradients (C:N  Veg-C)

48. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Sensitivity along env. gradients (SLA  Veg-C)

49. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Sensitivity along env. gradients (FLNR  Veg-C)

50. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Sensitivity along env. gradients (Mort  Veg-C)

51. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Summary-2 The model reacts non-linear to changes in the model parameters along environmental gradients. 1 Different parameters show differing patterns along environmental gradients 2 Mortality and leaf level chemistry parameters are highly sensitive to ecosystem simulations. 3

52. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Outlook – next steps Finish this sensitivity analysis for enlarged gradients. 1 Include other major tree species that are now calibrated. 2 Test model on LWF and WSI sites. 3

53. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Evaluate hypotheses of increased/decrease NPP along environmental gradients using single point and spatial Biome-BGC simulations. 1 Different parameters show differing patterns along environmental gradients 2 Mortality and leaf level chemistry parameters are highly sensitive to ecosystem simulations. 3 Outlook – and thereafter

54. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Requirements – 1: daily climate maps Daily Tmin simulations (L. Bernhard & N.Zimmermann)

55. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Requirements – 1: daily climate maps Daily Tmax simulations (L. Bernhard & N.Zimmermann)

56. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Model runs and sensitivity analyses Requirements – 2: fractional covers Daily Tmax simulations (M. Schwarz, L. Mathys & N.Zimmermann)

57. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Thank you for your attention

58. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses Some more stuff / results

59. Progress report on test data & -simulations Examples of preliminary LWF site simulations Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

60. Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

61. Progress report on test data & -simulations Examples of preliminary LWF site simulations Othmarsingen Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

62. % daily wood formation Avg. daily NPP (kg C/m 2 /day) simulated NPP (mass+storage) vs. stemwood production (mass) Othmarsingen Othmarsingen (Fagus sylvatica) Leaves Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

63. simulated NPP (mass+storage) vs. stemwood production (mass) Vordemwald Vordemwald (Abies alba & Picea abies) Needles % daily wood formation Avg. daily NPP (kg C/m 2 /day) Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

64. Next tasks (loose list) Stand structural data (3-4 year colume increments per size class) Densitometry and Ring width of individual years, sizes Calibrate for 3-4 year period per LWF plot Reconstruct NPPa for last few decades Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

65. Next tasks (loose list) Finish additional calibration data (roots, LWF, …) Mostly root turnover, C:N, allocation is not well included yet Lots of C:N (leafs, needles, wood) is in the analyses lab Leaf litter data from LWF is currently under analysis Finish preparation for spatial simulations Prepare input maps for dominant forest types Using a combination of RS and GIS/Statistical modelling Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

66. Next tasks (loose list) Finish preparation for spatial simulations (ctnd.) Developed by M. Schwarz & N. Zimmermann Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

67. Progress report on calibration Intra-annual Growth Sampling: every 2 weeks (later 4 weeks) 6 sites (LWF) dominant spp., 3 size classes, 2 cores per tree Analysis # of cells added since last date diameter increment (1/100mm) since last date % daily average growth per period average per species (size). Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

68. Progress report on calibration Intra-annual Growth  some results Othmarsingen Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses

69. Progress report on calibration Intra-annual Growth  some results Vordemwald Mountain Forest Ecology Seminar; Jan. 22 nd 2004 Niklaus E. Zimmermann Biome-BGC: Calibration and Sensitivity Analyses