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Studies of the role of disturbance in vegetation or ecosystems showed that disturbances are an essential and intrinsic element of ecosystems that contribute substantially to ecosystem health, to structural diversity of ecosystems and to nutrient cycling at the local as well as global level. Fire as a grassland, bush or forest fire is a special disturbance agent, since it is caused by biotic as well abiotic environmental factors. Fire affects biogeochemical cycles and plays an important role in atmospheric chemistry by releasing climate-sensitive trace gases and aerosols, and thus in the global carbon cycle by releasing approximately 3.9 Gt C p.a. through biomass burning. A combined model to describe effects and feedbacks between fire and vegetation became relevant as changes in fire regimes due to land use and land management were observed and the global dimension of biomass burnt as an important carbon flux to the atmosphere, its influence on atmospheric chemistry and climate as well as vegetation dynamics were emphasized. The existing modelling approaches would not allow these investigations. As a consequence, an optimal set of variables that best describes fire occurrence, fire spread and its effects in ecosystems had to be defined, which can simulate observed fire regimes and help to analyse interactions between fire and vegetation dynamics as well as to allude to the reasons behind changing fire regimes. Especially, dynamic links between vegetation, climate and fire processes are required to analyse dynamic feedbacks and effects of changes of single environmental factors. This led us to the point, where new fire models had to be developed that would allow the investigations, mentioned above, and could help to improve our understanding of the role of fire in global ecology. In conclusion of the thesis, one can state that moisture conditions, its persistence over time and fuel load are the important components that describe global fire pattern. If time series of a particular region are to be reproduced, specific ignition sources, fire-critical climate conditions and vegetation composition become additional determinants. Vegetation composition changes the level of fire occurrence and spread, but has limited impact on the inter-annual variability of fire. The importance to consider the full range of major fire processes and links to vegetation dynamics become apparent under climate change conditions. Increases in climate-dependent length of fire season does not automatically imply increases in biomass burnt, it can be buffered or accelerated by changes in vegetation productivity. Changes in vegetation composition as well as enhanced vegetation productivity can intensify changes in fire and lead to even more fire-related emissions. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2002/2003.
In this thesis, I investigated the factors influencing the growth and vertical distribution of planktonic algae in extremely acidic mining lakes (pH 2-3). In the focal study site, Lake 111 (pH 2.7; Lusatia, Germany), the chrysophyte, Ochromonas sp., dominates in the upper water strata and the chlorophyte, Chlamydomonas sp., in the deeper strata, forming a pronounced deep chlorophyll maximum (DCM). Inorganic carbon (IC) limitation influenced the phototrophic growth of Chlamydomonas sp. in the upper water strata. Conversely, in deeper strata, light limited its phototrophic growth. When compared with published data for algae from neutral lakes, Chlamydomonas sp. from Lake 111 exhibited a lower maximum growth rate, an enhanced compensation point and higher dark respiration rates, suggesting higher metabolic costs due to the extreme physico-chemical conditions. The photosynthetic performance of Chlamydomonas sp. decreased in high-light-adapted cells when IC limited. In addition, the minimal phosphorus (P) cell quota was suggestive of a higher P requirement under IC limitation. Subsequently, it was shown that Chlamydomonas sp. was a mixotroph, able to enhance its growth rate by taking up dissolved organic carbon (DOC) via osmotrophy. Therefore, it could survive in deeper water strata where DOC concentrations were higher and light limited. However, neither IC limitation, P availability nor in situ DOC concentrations (bottom-up control) could fully explain the vertical distribution of Chlamydomonas sp. in Lake 111. Conversely, when a novel approach was adopted, the grazing influence of the phagotrophic phototroph, Ochromonas sp., was found to exert top-down control on its prey (Chlamydomonas sp.) reducing prey abundance in the upper water strata. This, coupled with the fact that Chlamydomonas sp. uses DOC for growth, leads to a pronounced accumulation of Chlamydomonas sp. cells at depth; an apparent DCM. Therefore, grazing appears to be the main factor influencing the vertical distribution of algae observed in Lake 111. The knowledge gained from this thesis provides information essential for predicting the effect of strategies to neutralize the acidic mining lakes on the food-web.
Encounters with neighbours
(2003)
In this work, different aspects and applications of the recurrence plot analysis are presented. First, a comprehensive overview of recurrence plots and their quantification possibilities is given. New measures of complexity are defined by using geometrical structures of recurrence plots. These measures are capable to find chaos-chaos transitions in processes. Furthermore, a bivariate extension to cross recurrence plots is studied. Cross recurrence plots exhibit characteristic structures which can be used for the study of differences between two processes or for the alignment and search for matching sequences of two data series. The selected applications of the introduced techniques to various kind of data demonstrate their ability. Analysis of recurrence plots can be adopted to the specific problem and thus opens a wide field of potential applications. Regarding the quantification of recurrence plots, chaos-chaos transitions can be found in heart rate variability data before the onset of life threatening cardiac arrhythmias. This may be of importance for the therapy of such cardiac arrhythmias. The quantification of recurrence plots allows to study transitions in brain during cognitive experiments on the base of single trials. Traditionally, for the finding of these transitions the averaging of a collection of single trials is needed. Using cross recurrence plots, the existence of an El Niño/Southern Oscillation-like oscillation is traced in northwestern Argentina 34,000 yrs. ago. In further applications to geological data, cross recurrence plots are used for time scale alignment of different borehole data and for dating a geological profile with a reference data set. Additional examples from molecular biology and speech recognition emphasize the suitability of cross recurrence plots.