Abstract

Ecosystem research benefits enormously from the fact that comprehensive data sets of high quality, and covering long time periods are now increasingly more available. However, facing apparently complex interdependencies between numerous ecosystem components, there is urgent need rethinking our approaches in ecosystem research and applying new tools of data analysis.The concept presented in this paper is based on two pillars. Firstly, it postulates that ecosystems are multiple feedback systems and thus are highly constrained. Consequently, the effective dimensionality of multivariate ecosystem data sets is expected to be rather low compared to the number of observables. Secondly, it assumes that ecosystems are characterized by continuity in time and space as well as between entities which are often treated as distinct units.Implementing this concept in ecosystem research requires new tools for analysing large multivariate data sets. This study presents some of them, which were applied to a comprehensive water quality data set from a long-term monitoring program in Northeast Germany in the Uckermark region, one of the LTER-D (Long Term Ecological Research network, Germany) sites.The effective dimensionality was assessed by the Correlation Dimension approach as well as by a Principal Component Analysis and was in fact substantially lower than the number of observables. Continuity in time, space and between different types of water bodies was studied by combining Self-Organizing Maps with Sammon's Mapping. Groundwater, kettle hole and stream water samples exhibited some overlap, confirming continuity between different types of water bodies. Clear long-term shifts were found at the stream sampling sites. There was strong evidence that the intensity of single processes had changed at these sites rather than that new processes developed. Thus the more recent data did not occupy new subregions of the phase space of observations.Short-term variability of the kettle hole water samples differed substantially from that of the stream water samples, suggesting different processes generating the dynamics in these two types of water bodies. However, again, this seemed to be due to differing intensities of single processes rather than to completely different processes.We feel that research aiming at elucidating apparently complex interactions in ecosystems could make much more efficient use from now available large monitoring data sets by implementing the suggested concept and using corresponding innovative tools of system analysis.

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