@phdthesis{Schwager2005, author = {Schwager, Monika}, title = {Climate change, variable colony sizes and temporal autocorrelation : consequences of living in changing environments}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-5744}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {Natural and human induced environmental changes affect populations at different time scales. If they occur in a spatial heterogeneous way, they cause spatial variation in abundance. In this thesis I addressed three topics, all related to the question, how environmental changes influence population dynamics. In the first part, I analysed the effect of positive temporal autocorrelation in environmental noise on the extinction risk of a population, using a simple population model. The effect of autocorrelation depended on the magnitude of the effect of single catastrophic events of bad environmental conditions on a population. If a population was threatened by extinction only, when bad conditions occurred repeatedly, positive autocorrelation increased extinction risk. If a population could become extinct, even if bad conditions occurred only once, positive autocorrelation decreased extinction risk. These opposing effects could be explained by two features of an autocorrelated time series. On the one hand, positive autocorrelation increased the probability of series of bad environmental conditions, implying a negative effect on populations. On the other hand, aggregation of bad years also implied longer periods with relatively good conditions. Therefore, for a given time period, the overall probability of occurrence of at least one extremely bad year was reduced in autocorrelated noise. This can imply a positive effect on populations. The results could solve a contradiction in the literature, where opposing effects of autocorrelated noise were found in very similar population models. In the second part, I compared two approaches, which are commonly used for predicting effects of climate change on future abundance and distribution of species: a "space for time approach", where predictions are based on the geographic pattern of current abundance in relation to climate, and a "population modelling approach" which is based on correlations between demographic parameters and the inter-annual variation of climate. In this case study, I compared the two approaches for predicting the effect of a shift in mean precipitation on a population of the sociable weaver Philetairus socius, a common colonially living passerine bird of semiarid savannahs of southern Africa. In the space for time approach, I compared abundance and population structure of the sociable weaver in two areas with highly different mean annual precipitation. The analysis showed no difference between the two populations. This result, as well as the wide distribution range of the species, would lead to the prediction of no sensitive response of the species to a slight shift in mean precipitation. In contrast, the population modelling approach, based on a correlation between reproductive success and rainfall, predicted a sensitive response in most model types. The inconsistency of predictions was confirmed in a cross-validation between the two approaches. I concluded that the inconsistency was caused, because the two approaches reflect different time scales. On a short time scale, the population may respond sensitively to rainfall. However, on a long time scale, or in a regional comparison, the response may be compensated or buffered by a variety of mechanisms. These may include behavioural or life history adaptations, shifts in the interactions with other species, or differences in the physical environment. The study implies that understanding, how such mechanisms work, and at what time scale they would follow climate change, is a crucial precondition for predicting ecological consequences of climate change. In the third part of the thesis, I tested why colony sizes of the sociable weaver are highly variable. The high variation of colony sizes is surprising, as in studies on coloniality it is often assumed that an optimal colony size exists, in which individual bird fitness is maximized. Following this assumption, the pattern of bird dispersal should keep colony sizes near an optimum. However, I showed by analysing data on reproductive success and survival that for the sociable weaver fitness in relation to colony size did not follow an optimum curve. Instead, positive and negative effects of living in large colonies overlaid each other in a way that fitness was generally close to one, and density dependence was low. I showed in a population model, which included an evolutionary optimisation process of dispersal that this specific shape of the fitness function could lead to a dispersal strategy, where the variation of colony sizes was maintained.}, subject = {Populationsbiologie}, language = {en} } @phdthesis{Kucklaender2006, author = {Kuckl{\"a}nder, Nina}, title = {Synchronization via correlated noise and automatic control in ecological systems}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-10826}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = { Subject of this work is the possibility to synchronize nonlinear systems via correlated noise and automatic control. The thesis is divided into two parts. The first part is motivated by field studies on feral sheep populations on two islands of the St. Kilda archipelago, which revealed strong correlations due to environmental noise. For a linear system the population correlation equals the noise correlation (Moran effect). But there exists no systematic examination of the properties of nonlinear maps under the influence of correlated noise. Therefore, in the first part of this thesis the noise-induced correlation of logistic maps is systematically examined. For small noise intensities it can be shown analytically that the correlation of quadratic maps in the fixed-point regime is always smaller than or equal to the noise correlation. In the period-2 regime a Markov model explains qualitatively the main dynamical characteristics. Furthermore, two different mechanisms are introduced which lead to a higher correlation of the systems than the environmental correlation. The new effect of "correlation resonance" is described, i. e. the correlation yields a maximum depending on the noise intensity. In the second part of the thesis an automatic control method is presented which synchronizes different systems in a robust way. This method is inspired by phase-locked loops and is based on a feedback loop with a differential control scheme, which allows to change the phases of the controlled systems. The effectiveness of the approach is demonstrated for controlled phase synchronization of regular oscillators and foodweb models.}, subject = {Markov-Prozess}, language = {en} }