Vegetation change shows generic features of non-linear dynamics

Question: In non-linear physical, or chemical, systems dynamic instability limits predictability and external fluctuations cause interesting, and sometimes counter intuitive, effects. We ask how these generic properties of complex systems are seen in vegetation change.Methods: An interacting particl...

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Veröffentlicht in:Journal of vegetation science 2005-12, Vol.16 (6), p.703-712
Hauptverfasser: Gassmann, F, Kloetzli, F, Walther, G
Format: Artikel
Sprache:eng
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Zusammenfassung:Question: In non-linear physical, or chemical, systems dynamic instability limits predictability and external fluctuations cause interesting, and sometimes counter intuitive, effects. We ask how these generic properties of complex systems are seen in vegetation change.Methods: An interacting particle system is used to simulate possible developments of a plant community that was observed for 30 years on a test area in the Lueneburger Heide (Germany). We investigate simulated trajectories for five plant types over several decades. The internal updating rule, simulating the interactions between the five plant types, is completely deterministic, the only sources of stochasticity being the initial conditions and the external climatic variations.Results: Though the results of our simulation model share many aspects with those of stochastic models with probabilistic transition matrices, the solution manifold of our non-linear model goes beyond the possibilities of stochastic models. Among many stable developments, chaotic trajectories were also found. Climatic fluctuations increased the frequency of certain plant types. These properties of vegetation dynamics match the long-term field observations. They reflect generic features of complex systems.Conclusions: The presented non-linear model can provide insights into the dynamics of vegetation change, even though the mechanisms observed in the real world are modelled only in a rather general way. The rich behavioural repertoire, resulting from deterministic internal dynamics, can simulate observed properties that are beyond the possibilities of models with probabilistic internal dynamics.Nomenclature:Corley et al. (1981); Corley & Crundwell (1991); Tutin et al. (1964-1983); Grolle (1983); Grolle & Long (2000).Abbreviations: CA = Cellular automaton; IPS = Interacting particle system; M = Moss.
ISSN:1100-9233
1104-7402
DOI:10.1043/1100-9233(2005)016[0703:VCSGFO]2.0.CO;2