Artificial Life VI


Investigating Forest Growth Model Results on Evolutionary Time Scales

Holger Lange
BITOEK, Univ. Bayreuth, D-95440 Bayreuth, Germany
http://www.bitoek.uni-bayreuth.de/Mitarbeiter/000125/EN.html

Birgit Thies
BITOEK, Univ. Bayreuth, D-95440 Bayreuth, Germany
http://www.bitoek.uni-bayreuth.de/Mitarbeiter/000490/EN.html

Alois Kastner-Maresch
BITOEK, Univ. Bayreuth, D-95440 Bayreuth, Germany
http://www.bitoek.uni-bayreuth.de/Mitarbeiter/000120/EN.html

Walter Doerwald
BITOEK, Univ. Bayreuth, D-95440 Bayreuth, Germany
http://www.bitoek.uni-bayreuth.de/Mitarbeiter/000109/EN.html

Jan T. Kim
MPI Koeln


Abstract

The output time series from the individual-based tree growth model TRAGIC++ are characterized by measures quantifying their randomness and complexity and by power spectra. TRAGIC++ provides, in addition to spatially very explicit tree stand representations, annual values for biomass production, root development, tree height and many others, for arbitrarily long simulation periods. Site conditions are translated into external growth constraints affecting the aggregated ecosystem level in the form of long-term nutrient input fluxes. Evolutionary effects are included by random mutations of parameters related to height growth strategies of individual trees. Genealogies are being traced to reconstruct evolutionary paths of successful strategies. Long-range correlations for some of the output variables are observed. At the ecosystem level, the nutrient budget remains stationary and uneffected by mutations. Tree strategies, however, appear to show long-term "genetic" drift. Different phenotypes appear to cluster relative independently of mutation rates and resemble adaptation within real forest ecosystems and experiences in forestry."


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