Abstract:
Ref.: Ms. No. EJFOR-D-08-00181R1
accepted on 16-06-2009
Ecosystem analysis is typically done by determination of species composition, structural ex-ploration, determination of matter and energy fluxes and/or system analyses based on deter-ministic or probabilistic/stochastic model approaches. However, regarding ecosystem dynam-ics, temporal structure, information content, complexity of signals, and their modifications when subsequently passing through different subsystems, have not intensively been studied to date. Structure in time series characterised by information and complexity measures may pro-vide additional, powerful tools to analyse state and dynamics of ecosystems. Along their path through ecosystem compartments e.g. hydrological signals are transformed in several ways, comprising changes in randomness, autocorrelation structures, and smoothness. Thus, time series analyses with complexity and information measures is of interest for a holistic under-standing of ecosystem behaviour and early indications of natural and anthropogenic distur-bances of ecosystems like ecosystem degradation and climate change. Further, these measures provide additional criteria for the calibration of model parameters tests of model validity, and determination of the necessary degree of complexity of process models. In this paper we pre-sent the outcome from applications of information and complexity measures to hydrological time series in two climatically different forest ecosystems in South Germany and Southern Ecuador. The values of information and complexity measures have a clearly different range for the different hydrological parameters but for ecosystems of the same type like mountain forest the values of information and complexity measures exhibit similar behaviour for the hydrological parameters. We hypothesize that complexity of hydrological time series in-creases with the number of abiotic and biotic variables involved in the generating process of the time series. Thus, complexity should have a minimum in the precipitation signal which is controlled by abiotic, atmospheric factors only, and reach a maximum in the root zone where the interaction of abiotic and biotic variables is high. Hydrological time series under study cover the sequence of hydrological signals from open precipitation, throughfall, sapflow, wa-ter fluxes in the soil compartment and system discharge. We detected pronounced data aggre-gation and transformation effects of hydrological signals along their path through subsystems in terms of information propagation. We further found similar patterns in different ecosystems of the same general type. As a result of intensive abiotic and biotic interactions, a pronounced maximum of complexity was found in the moisture signal of the soil compartment.
