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The length of the vegetation period (VP) plays a central role for the interannual variation of carbon fixation of terrestrial ecosystems. Observational data analysis has indicated that the length of the VP has increased in the last decades in the northern latitudes mainly due to an advancement of bud burst (BB). This phenomenon has been widely discussed in the context of Global Warming because phenology is correlated to temperatures. Analyzing the patterns of spring phenology over the last century in Southern Germany provided two main findings: - The strong advancement of spring phases especially in the decade before 1999 is not a singular event in the course of the 20th century. Similar trends were also observed in earlier decades. Distinct periods of varying trend behavior for important spring phases could be distinguished. - Marked differences in trend behavior between the early and late spring phases were detected. Early spring phases changed as regards the magnitude of their negative trends from strong negative trends between 1931 and 1948 to moderate negative trends between 1948 and 1984 and back to strong negative trends between 1984 and 1999. Late spring phases showed a different behavior. Negative trends between 1931 and 1948 are followed by marked positive trends between 1948 and 1984 and then strong negative trends between 1984 and 1999. This marked difference in trend development between early and late spring phases was also found all over Germany for the two periods 1951 to 1984 and 1984 to 1999. The dominating influence of temperature on spring phenology and its modifying effect on autumn phenology was confirmed in this thesis. However, - temperature functions determining spring phenology were not significantly correlated with a global annual CO2 signal which was taken as a proxy for a Global Warming pattern. - an index for large scale regional circulation patterns (NAO index) could only to a small part explain the observed phenological variability in spring. The observed different trend behavior of early and late spring phases is explained by the differing behavior of mean March and April temperatures. Mean March temperatures have increased on average over the 20th century accompanied by an increasing variation in the last 50 years. April temperatures, however, decreased between the end of the 1940s and the mid-1980s, followed by a marked warming after the mid-1980s. It can be concluded that the advancement of spring phenology in recent decades are part of multi-decadal fluctuations over the 20th century that vary with the species and the relevant seasonal temperatures. Because of these fluctuations a correlation with an observed Global Warming signal could not be found. On average all investigated spring phases advanced between 5 and 20 days between 1951 and 1999 for all Natural Regions in Germany. A marked difference be! tween late and early spring phases is due to the above mentioned differing behavior before and after the mid-1980s. Leaf coloring (LC) was delayed between 1951 and 1984 for all tree species. However, after 1984 LC was advanced. Length of the VP increased between 1951 and 1999 for all considered tree species by an average of ten days throughout Germany. It is predominately the change in spring phases which contributes to a change in the potentially absorbed radiation. Additionally, it is the late spring species that are relatively more favored by an advanced BB because they can additionally exploit longer days and higher temperatures per day advancement. To assess the relative change in potentially absorbed radiation among species, changes in both spring and autumn phenology have to be considered as well as where these changes are located in the year. For the detection of the marked difference between early and late spring phenology a new time series construction method was developed. This method allowed the derivation of reliable time series that spanned over 100 years and the construction of locally combined time series increasing the available data for model development. Apart from analyzed protocolling errors, microclimatic site influences, genetic variation and the observers were identified as sources of uncertainty of phenological observational data. It was concluded that 99% of all phenological observations at a certain site will vary within approximately 24 days around the parametric mean. This supports to the proposed 30-day rule to detect outliers. New phenology models that predict local BB from daily temperature time series were developed. These models were based on simple interactions between inhibitory and promotory agents that are assumed to control the developmental status of a plant. Apart from the fact that, in general, the new models fitted and predicted the observations better than classical models, the main modeling results were: - The bias of the classical models, i.e. overestimation of early observations and underestimation of late observations, could be reduced but not completely removed. - The different favored model structures for each species indicated that for the late spring phases photoperiod played a more dominant role than for early spring phases. - Chilling only plays a subordinate role for spring BB compared to temperatures directly preceding BB.
Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (Müggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.