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European Journal of Forest Research

, Volume 124, Issue 4, pp 349–362 | Cite as

Effects of environmental changes on the vitality of forest stands

  • Thomas RötzerEmail author
  • Rüdiger Grote
  • Hans Pretzsch
Original Paper

Abstract

Using the physiological single tree growth model BALANCE, vitality of forest stands was simulated in dependence of the site-related factors, climate and stand structure. At six level II plots in southern Germany with the main tree species beech (Fagus sylvatica L.), oak (Quercus robur L.), spruce (Picea abies [L.] Karst.), and pine (Pinus sylvestris L.), simulated results were compared to measured values (soil water content, bud burst and leaf colouring, diameter at breast height, tree height and crown density) in order to validate the model. Sensitivity tests were done to examine the influence and the interactions of the environmental parameters. The validation results show that BALANCE is capable of realistically simulating the growth and vitality of forest stands for central European regions for medium term time spans (several years). The validation of the water balance module produces mean absolute errors based on field capacity between 2.7 and 6.9% in dependence of sites and forest stands. Senescence of foliage as well as crown density is reproduced with a correlation coefficient of 0.70 compared to measurements. Differences between measured and simulated diameter values were smaller than 1% for spruce and smaller than 6.5% for beech after 7 years of simulation, and smaller than 1% for oak after 8 years of simulation. On the other hand, the simulations for pine trees conform less with the measurements (difference: 22.6% after 8 years). The sensitivity of the model on environmental changes and on combinations of these parameters could be demonstrated. The responses of the forest stands were quite different.

Keywords

Tree growth modelling Vitality Crown condition Forest stand Climate change Level II 

Notes

Acknowledgements

The investigation was funded by German Federal Agency for Agriculture and Food (BLE-00HS041). The basic model BALANCE was developed in the framework of the special research program SFB 607 ‘growth and parasite defence’. The authors are indebted to C. Pitkanen for the contribution in data processing and analysis and T. Seifert for his critical review of the article. The authors thank Bavarian State Institute of Forestry (LWF) for providing the data of the Bavarian level II plots, especially W. Grimmeisen for the soil moisture data and B. Schultze for the actual climate data. Thanks also to German Weather Service (DWD) for providing phenological data.

References

  1. Allen RG, Jensen ME, Wright JL, Burman RD (1989) Operational estimates of reference evapotranspiration. Agron J 81:650–662CrossRefGoogle Scholar
  2. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment. Part I: Model development. J Am Water Res Assoc 34:73–89CrossRefGoogle Scholar
  3. Armour H, Straw N, Day K (2003) Interactions between growth, herbivory and long-term foliar dynamics of Scots pine. Trees 17:70–80CrossRefGoogle Scholar
  4. Barbo DN, Chappelka AH, Somers GL, Miller-Goodman MS, Stolte K (2002) Ozone impacts on loblolly pine (Pinus taeda L.) grown in a competitive environment. Environ Pollut 116:27–36CrossRefPubMedGoogle Scholar
  5. BMELF (1997) Dauerbeobachtungsflächen zur Umweltkontrolle im Wald (Level II). Bundesministerium für Ernährung, Landwirtschaft und Forsten, BonnGoogle Scholar
  6. Chmielewski FM, Rötzer T (2001) Response of tree phenology to climate change across Europe. Agric For Meteor 108:101–112CrossRefGoogle Scholar
  7. Demchik MC, Sharpe WE (2000) The effect of soil nutrition, soil acidity and drought on northern red oak (Quercus rubra L.) growth and nutrition on Pennsylvania sites with high and low red oak mortality. For Ecol Manage 136:199–207CrossRefGoogle Scholar
  8. Derner JD, Johnson HB, Kimball BA, Pinter PJ, Polley HW, Tischler CR, Boutton TW, LaMorte RL, Wall GW, Adam NR, Leavitt SW, Ottman MJ, Matthias AD, Brooks TJ (2003) Above- and below-ground responses of C3-C4 species mixtures to elevated CO2 and soil water availability. Global Change Biol 9/4:452–460CrossRefGoogle Scholar
  9. Dohrenbusch A, Jaehne S, Bredemeier M, Lamersdorf N (2002) Growth and fructification of a Norway spruce (Picea abies L. Karst) forest ecosystem under changed nutrient and water input. Ann For Sci 59:359–368CrossRefGoogle Scholar
  10. Ellenberg H, Mayer R, Schauermann J (1986) Ökosystemforschung—Ergebnisse des Solling-Projektes 1966–1986. Eugen Ulmer-Verlag, StuttgartGoogle Scholar
  11. Federer CA (1995) BROOK90: A simulation model for evaporation, soil water and streamflow, Version 3.1 Computer freeware and documentation. USDA Forest Service, PO Box 640, Durham NH, USAGoogle Scholar
  12. Grote R (1998) Integrating dynamic morphological properties into forest growth modeling. II. Allocation and mortality. For Ecol Manage 111(2/3):193–210CrossRefGoogle Scholar
  13. Grote R (2003) Estimation of crown radii and crown projection area from stem size and tree position. Ann For Sci 60:393–402CrossRefGoogle Scholar
  14. Grote R, Pretzsch H (2002) A model for individual tree development based on physiological processes. Plant Biol 4:167–180CrossRefGoogle Scholar
  15. Grote R, Reiter IM (2004) Competition-dependent modelling of foliage biomass in forest stands. Trees 18:596–607CrossRefGoogle Scholar
  16. Grote R, Patzner K, Seifert T (2003) Modelling water availability in individual trees—a contribution of process-based simulation to the prediction of developments in heterogeneous stands. 17th International Conference on Informatics for Environmental Protection, Cottbus, 24–26 October 2003. A. Gnauck and R. Heinrich. Anonymous. Marburg: Metropolis Verlag. Umwelt-Informatik aktuell vol 31, pp 804–812Google Scholar
  17. Gruber F (2002) Steuerung und Vorhersage der Fruktifikation bei der Rotbuche (Fagus sylvatica L.) für den Standort Zierenberg 38A und den Level I Flächen von Hessen durch die Witterung. AFZ 4:67–79Google Scholar
  18. Gruber F (2003) Welche Witterung bestimmt die Fruchtbildung bei der Rotbuche? AFZ 5:246–250Google Scholar
  19. Gusev YM, Nasova ON (2003) The simulation of heat and water exchange in the boreal spruce forest by the land-surface model SWAP. J Hydrol 280:162–191CrossRefGoogle Scholar
  20. Guttenberg A (1897) Die Aufstellung von Holzmassen- und Geldertragstafeln auf grundlage von Stammanalysen. Selbstverlag Guttenberg, Vienna, p 62Google Scholar
  21. Hamilton JG, DeLucia EH, George K, Naidu SL, Finzi AC, Schlesinger WH (2002) Forest carbon balance under elevated CO2. Oecologia 131:250–260CrossRefGoogle Scholar
  22. Haxeltine A, Prentice IC (1996) A general model for the light-use efficiency of primary production. Funct Ecol 10:551–561CrossRefGoogle Scholar
  23. IPCC (2000) Land, use, land use change and forestry. In: Watson RT, Noble IR, Bolin B, Ravindranath NH, Verardo DJ, Docken DJ (eds), IPCC special report. Cambridge University Press, Cambridge, 337ppGoogle Scholar
  24. Kikuzawa K (1995) The basis for variation in leaf longevity of plants. Vegetation 121:89–100CrossRefGoogle Scholar
  25. Lewis JD, Lucash M, Olszyk D, Tingey DT (2001) Seasonal patterns of photosynthesis in Douglas fir seedlings during the third and fourth year of exposure to elevated CO2 and temperature. Plant Cell Environ 24:539–548CrossRefGoogle Scholar
  26. Mäkinen H, Nöjd P, Kahle HP, Neumann U, Tveite B, Mielikäinen K, Röhle H, Spiecker H (2003) Large scale climatic variability and radial increment variation of Picea abies (L.) Karst. in central and northern Europe. Trees 17:173–184Google Scholar
  27. Mayer FJ (1999) Beziehungen zwischen der Belaubungsdichte der Waldbäume und Standortparametern—Auswertungen der bayerischen Waldstandinventuren. Schriftenreihe der Forstwissenschaftlichen Fakultät der TU München und der Bayerischen Landesanstalt für Wald und Forstwirtschaft, 195 ppGoogle Scholar
  28. McDonald EP, Kruger EL, Riemenschneider DE, Isebrands JG (2002) Competitive status influences tree-growth responses to elevated CO2 and O3 in aggrading aspen stands. Funct Ecol 16:792–801CrossRefGoogle Scholar
  29. Menzel A, Fabian P (1999) Growing season extended in Europe. Nature 397:659CrossRefGoogle Scholar
  30. Mohren GMJ, Bartelink HH (1990) Modelling the effects of needle mortality rate and needle area distribution on dry matter production of Douglas fir. Netherlands J Agric Sci 38:53–66Google Scholar
  31. Monteith JL (1965) Evaporation and environment. In: Fogg GE (ed) The state and movement of water in living organisms. Academic, LondonGoogle Scholar
  32. Oleksyn J, Tjoelker MG, Lorenc-Plucinska G, Konwinska A, Zytkowiak R, Karolewski P, Reich PB (1997) Needle CO2 exchange, structure and defense traits in relation to needle age in Pinus heldreichii Christ—arelict of Tertiary flora. Trees 12:82–89CrossRefGoogle Scholar
  33. Paar U, Kirchhoff A, Westphal J, Eichhorn J (2000) Fruktifikation der Buche in Hessen. AFZ 25:1362–1363Google Scholar
  34. Pretzsch H (1996) Growth trends of forests in southern Germany. In: Spieker H, Mielikänen K, Köhl M, Skovsgaard JP (eds) Growth trends in European forests—studies from 12 countries. EFI-Research Rep. 5. Springer, Berlin, Heidelberg, New YorkGoogle Scholar
  35. Pretzsch H (1997) Analysis and modelling of spatial stand structures—methological considerations based on mixed beech-larch stands in Lower Saxony. For Ecol Manage 97:237–253CrossRefGoogle Scholar
  36. Pretzsch H (2002) Diversität und Produktivität von Wäldern. AFJZ 174:88–98Google Scholar
  37. Preuhsler T (1993–2000) Year books of the Bavarian forest climate stations. Bayerische Landesanstalt für Wald und Forstwirtschaft, FreisingGoogle Scholar
  38. Reich PB (2001) Body size, geometry, longevity and metabolism: do plant leaves behave like animal bodies? Trends Ecol Evol 16/1:674–680CrossRefGoogle Scholar
  39. Reich PB, Ellsworth DS, Walters MB, Vose JM, Gresham C, Volin JC (1999) Generality of leaf trait relationships: a test across six biomes. Ecology 80:1955–1969CrossRefGoogle Scholar
  40. Rötzer T (2000) Bestimmung von Transferfunktionen zur Berechnung der Witterung von Waldstandorten (transformation of meteorological data on specific geographical sites). Final report on a project of the University of Applied Sciences Weihenstephan, Department of Forests and Forestry, Freising, 55ppGoogle Scholar
  41. Rötzer T, Chmielewski FM (2001) Phenological maps of Europe. Clim Res 18:249–257CrossRefGoogle Scholar
  42. Rötzer T, Häckel H., Würländer R (1997) Agrar- und Umweltklimatologischer Atlas von Bayern (agricultural and environmental atlas of Bavaria). German Weather Service, Weihenstephan, ZollingGoogle Scholar
  43. Rötzer T, Dittmar C, Elling W (2004a) A model for site specific estimation of the available soil water content and the evapotraspiration in forest ecosystems. J Environ Hydrol 12/7:1–14Google Scholar
  44. Rötzer T, Grote R, Pretzsch H (2004b) The timing of bud burst and its effect on tree growth. Int J Biomet 48:109–118CrossRefGoogle Scholar
  45. Schober R (1975) Ertragstafeln wichtiger Baumarten. JD Sauerländer’s Verlag, Frankfurt am Main, p 154Google Scholar
  46. Sinoquet H, Le Roux X (2000) Short term interactions between tree foliage and the aerial environment: an overview of modelling approaches available for tree structure–function models. Ann For Sci 57:477–496CrossRefGoogle Scholar
  47. Spinnler D, Egli P, Körner C (2002) Four-year growth dynamics of beech-spruce model ecosystems under CO2 enrichment on two different forest soils. Trees 16:423–436CrossRefGoogle Scholar
  48. Thornley JHM, Cannell MGR (2000) Modelling the components of plant respiration: representation and realism. Ann Bot 85:55–67CrossRefGoogle Scholar
  49. UNECE (1998) Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Federal Research Centre for Forestry and Forest Products (BFH), Hamburg. 4th ednGoogle Scholar
  50. Wegehenkel M, Jochheim H (2003) Modellierung des Wasserhaushaltes von Kiefernbeständen des Level-II-Programms in Brandenburg mit unterschiedlich komplexen Simulationsmodellen. Forstwissenschaftliches Centralblatt 122:302–317CrossRefGoogle Scholar
  51. White MA, Running SW, Thornton PE (1999) The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest. Int J Biometeorol 42:139–145CrossRefPubMedGoogle Scholar
  52. Zeide B, VanderSchaaf C (2001) The effect of density on the height–diameter relationship. Gen. Tech. Rep. SRS-XX Asheville, NC. Kenneth W. Outcalt. Anonymous. Knoxville, TN: US Department of Agriculture, Forest Service, Southern Research Station. 453–456Google Scholar
  53. Zhang Y, Reed DD, Cattelino PJ, Gale MR, Jones EA, Liechty HO, Mroz GD (1994) A process-based growth model for young red pine. For Ecol Manage 69:21–40CrossRefGoogle Scholar
  54. Zheng D, Freeman M, Bergh J, Røsberg I, Nilsen P (2002) Production of Picea abies in South-east Norway in Response to Climate Change: A Case Study Using Process-based Model Simulation with Field Validation. Scand. J For Res 17:35–46Google Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Department of Ecosystem and Landscape Management, Chair of Forest Yield ScienceTechnische Universität MünchenFreisingGermany

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