|theory overview | detailed description|
The model 4C (FORESEE – Forest Ecosystems in a Changing Environment) is a forest dynamics model using physiological processes and assumes a horizontal homogeneity of the forest structure (Lasch et al. 2002). 4C aims at investigating the long-term forest behaviour under changing environmental conditions (Bugmann et al. 1997). It has been evaluated at different forest stands in Europe (Suckow et al. 2001) and used in a variety of studies (Lasch et al. 2002; Gerstengarbe et al. 2003; Stock 2005). The model uses tree and stand level variables to simulate tree species composition, forest structure, leaf area index as well as ecosystem carbon and water balances. Growth and mortality are described for tree cohorts as a group of identical trees concerning their tree characteristics (e.g. stem, leaf, and fine root biomass, height, diameter at breast height and at crown base, species type). The annual course of net photosynthesis is simulated with a mechanistic formulation of net photosynthesis as a function of environmental influences (temperature, water, and nitrogen availability, radiation, and CO2) where the physiological capacity (maximal carboxylation rate) is calculated based on the optimisation theory (modified after Haxeltine and Prentice 1996) plus the calculation of total tree respiration following the concept of constant annual respiration fraction as proposed by Landsberg and Waring (1997). The growth is modelled according to the pipe model theory (Shinozaki et al. 1964) , the functional balance hypothesis (Davidson 1969) and several allometric relationships. The fine root distribution is estimated by depth depending power function (Jackson et al. 1996).
Tree cohorts compete for water and nutrients whereas the establishment and the mortality are modelled according to the concepts of Keane (1996), Loehle and LeBlanc (1996) and Sykes (1996). Mortality is deterministic and can be caused by stress due to negative leaf mass increment in successive stress years.
4C requires climatic driving variables on a daily resolution but the outputs are given according to various time steps. The model estimates the soil carbon stock until the depth defined by the rooting depth in the soil.
The soil model of 4C consists of a water, temperature, and carbon/nitrogen sub-model. Following the soil horizons (organic layer and mineral soil horizons) the soil is divided into layers of varying thickness. The physical and chemical soil parameters and the initial carbon and nitrogen stocks as sum of soil organic matter and dead organic matter (litter) are determined by measurements or from soil map data. Water content, soil temperature, carbon, and nitrogen content of each layer are estimated as functions of the basic soil parameters, air temperature, net precipitation, and N deposition beneath the canopy. The carbon and nitrogen dynamics is driven by the litter input which is separated into 5 fractions for each species type (stems, twigs and branches, foliage, fine roots and coarse roots). The turnover of all litter fractions and of the soil organic matter compartment is described as a first order reaction (Grote et al. 1999). The processes are controlled by matter and species-specific reaction coefficients and modified by soil moisture, temperature and pH value.
Currently the model is parameterised for the five most abundant tree species of Central Europe (beech, Fagus sylvatica L.; Norway spruce, Picea abies L. Karst., Scots pine, Pinus sylvestris L., oaks, Quercus robur L., and Quercus petraea Liebl., and birch, Betula pendula Roth) and aspen (Populus tremula (L.), P. tremuloides (Michx.)), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), Aleppo pine (Pinus halepensis Mill.), Ponderosa pine (Pinus ponderosa Dougl.).
Bugmann, H., R. Grote, P. Lasch, M. Lindner and F. Suckow. 1997. A new forest gap model to study the effects of environmental change on forest structure and functioning. In Impacts of Global Change on Tree Physiology and Forest Ecosystems. G.M.J. Mohren, Kramer, K. and Sabaté, S. Forestry Sciences. Dordrecht, Kluwer Academic Publishers. 52: 255-261.
Davidson, R. L. 1969. Effect of root/leaf temperature differentials on root/shoot ratios in some pasture grasses and clover. Annals of Botany. 33: 561-569.
Gerstengarbe, F.-W., F.-W. Badeck, F. Hattermann, V. Krysanova, W. Lahmer, P. Lasch, M. Stock, F. Suckow, F. Wechsung and P. C. Werner. 2003. Studie zur klimatischen Entwicklung in Land Brandenburg bis 2055 und deren Auswirkungen auf den Wasserhaushalt, die Forst- und Landwirtschaft sowie die Ableitung erster Perspektiven. Potsdam Institute for Climate Impact Research. Potsdam, PIK-Report 83. 77 pages.
Grote, R., F. Suckow and K. Bellmann. 1999. Modelling of of carbon-, nitrogen-, and water balances in pine stands under changing air pollution and deposition. In Changes of Atmospheric Chemistry and Effects on Forest Ecosystems A Roof Experiment Without Roof. R.F. Hüttl and K. Bellmann, K. Dordrecht, Kluwer. 3: 251-281.
Haxeltine, A. and I. C. Prentice. 1996. A general model for the light-use efficiency of primary production. Functional Ecology. 10 (5): 551-561.
Jackson, R. B., J. Canadell, J. R. Ehleringer, H. A. Mooney, O. E. Sala and E. D. Schulze. 1996. A global analysis of root distributions for terrestrial biomes. Oecologia. 108 (3): 389-411.
Keane, R. E., P. Morgan and S. W. Running. 1996. Fire-Bgc - a Mechanistic Ecological Process Model For Simulating Fire Succession On Coniferous Forest Landscapes of the Northern Rocky Mountains. 122.
Landsberg, J. J. and R. H. Waring. 1997. A Generalised Model of Forest Productivity Using Simplified Concepts of Radiation-Use Efficiency, Carbon Balance and Partitioning. Forest Ecology and Management. 95 (3): 209-228.
Lasch, P., F.-W. Badeck, M. Lindner and F. Suckow. 2002. Sensitivity of simulated forest growth to changes in climate and atmospheric CO2. Forstwiss Centralblatt. 121 (Supplement 1): 155-171.
Lasch, P., F. W. Badeck, F. Suckow, M. Lindner, P. Mohr (2005). Model-based analysis of management alternatives at stand and regional level in Brandenburg (Germany). Forest Ecology And Management 207(1-2): 59-74.
Loehle, C. and D. LeBlanc. 1996. Model-based assessments of climate change effects on forests: a critical review. Ecological Modelling. 90: 1-31
Shinozaki, K., K. Yoda, K. Hozumi and T. Kira. 1964. A quantitative analysis of plant form - the pipe model theory. I. Basic analysis. Jap J of Ecology. 14: 97-105.
Stock, M. H. E. 2005. KLARA. Kimawandel - Auswirkungen, Risiken, Anpassung. PIK-Report. F. W. Gerstengarbe. Potsdam Institute for Climate Impact Research. Potsdam, PIK-Report Nr. 99. 199 pages.
Suckow, F., F.-W. Badeck, P. Lasch and J. Schaber. 2001. Nutzung von Level-II-Beobachtungen für Test und Anwendungen des Sukzessionsmodells FORESEE. Beiträge für Forstwirtschaft und Landschaftsökologie. 35 (2): 84-87.
Sykes, M. T., I. C. Prentice and W. Cramer. 1996. A bioclimatic model for the potential distributions of north European tree species under present and future climates. J Biogeogr. 23: 203-233.