Application of ergodic theory within ecosystem modelling
Abstract
Terrestrial ecosystem models are designed to assess the flux of energy, water, carbon and nitrogen corresponding to a given vegetation type. Ecosystem model validations use classical statistical methods (regression analysis of predicted versus observed values, paired t-statistics and error assessment procedures). These validations concentrate on static aspects of the model but fail to describe model dynamics. Recent research revealed that inconclusive outputs of large scale BGC-models resulted from instabilities in model dynamics. Ecosystem models are designed as “diagnostic tools” to study the behaviour of complex ecosystem processes. In this research we present “ergodic theory” as an excellent tool to provide us with estimates on the instabilities of ecosystem models. In our approach we will gain sound scientific knowledge by alternating the use of two principal descriptive views of reality; (i) the statistical view uses a set of observations on particular properties of individuals to extrapolate the behavior of the system from observations; (ii) the dynamic view explains the particular properties of observed system behavior using mechanistic descriptions of the interactions among the participating forces. We will use statistically generated climate data to run a dynamic ecosystem model. Model uncertainty will be assessed using statistical validation techniques, while model dynamics will be captured by ergodic theory. This “flip-flop” use of the two principal descriptive views is a major strength of our approach. The “ergodic theory” will enable us to assess five descriptive measures of system dynamics (i.e. Lyapunov exponents, entropy and three estimates for attractor dimension). Our hypothesis is that these five measures indicate the stability status of a given model simulation. If the model behaves stable then the accuracy and precision of model outputs will remain valid. If the model behaves unstable it may indicate either a reduced predictability or a reduction in the stability of a real world ecosystem. Test cases for this methodology are the western Congolian lowland rain forest and tropical savannas of the western Congo basin which exhibited fluctuations in their distribution during the holocene. Outputs from this research project may have fundamental practical implications allowing us to compare the stability of different ecosystem types or the change in the stability according to a change in driving forces like climate change.
Publikationen
Congo basin rainforest stability and carbon stocks
Autoren: Pietsch, S.A. Jahr: 2012
Conference & Workshop proceedings, paper, abstract
4°+: Ecosystem Resilience and Predictability
Autoren: Pietsch, S.A. Jahr: 2009
Conference & Workshop proceedings, paper, abstract
Stocks de carbone dans les Monts Birougou, Gabon
Autoren: Pietsch, S.A. Jahr: 2013
Conference & Workshop proceedings, paper, abstract
Project staff
Stephan Pietsch
Mag. Dr. Stephan Pietsch
stephan.pietsch@boku.ac.at
Project Leader
01.07.2008 - 30.06.2013