TY - JOUR A1 - Sibly, Richard M. A1 - Grimm, Volker A1 - Martin, Benjamin T. A1 - Johnston, Alice S. A. A1 - Kulakowska, Katarzyna A1 - Topping, Christopher J. A1 - Calow, Peter A1 - Nabe-Nielsen, Jacob A1 - Thorbek, Pernille A1 - DeAngelis, Donald L. T1 - Representing the acquisition and use of energy by individuals in agent-based models of animal populations JF - Methods in ecology and evolution : an official journal of the British Ecological Society N2 - Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. KW - bioenergetics KW - energy budget KW - individual-based models KW - population dynamics Y1 - 2013 U6 - https://doi.org/10.1111/2041-210x.12002 SN - 2041-210X VL - 4 IS - 2 SP - 151 EP - 161 PB - Wiley-Blackwell CY - Hoboken ER - TY - THES A1 - Schäfer, Merlin T1 - Understanding and predicting global change impacts on migratory birds T1 - Verständnis und Vorhersage von Auswirkungen des globalen Wandels auf Zugvögel N2 - This is a publication-based dissertation comprising three original research stud-ies (one published, one submitted and one ready for submission; status March 2019). The dissertation introduces a generic computer model as a tool to investigate the behaviour and population dynamics of animals in cyclic environments. The model is further employed for analysing how migratory birds respond to various scenarios of altered food supply under global change. Here, ecological and evolutionary time-scales are considered, as well as the biological constraints and trade-offs the individual faces, which ultimately shape response dynamics at the population level. Further, the effect of fine-scale temporal patterns in re-source supply are studied, which is challenging to achieve experimentally. My findings predict population declines, altered behavioural timing and negative carry-over effects arising in migratory birds under global change. They thus stress the need for intensified research on how ecological mechanisms are affected by global change and for effective conservation measures for migratory birds. The open-source modelling software created for this dissertation can now be used for other taxa and related research questions. Overall, this thesis improves our mechanistic understanding of the impacts of global change on migratory birds as one prerequisite to comprehend ongoing global biodiversity loss. The research results are discussed in a broader ecological and scientific context in a concluding synthesis chapter. N2 - Dies ist eine publikationsbasierte Dissertation, welche aus drei wissenschaftlichen Originalstudien (eine publiziert, eine eingereicht und eine einreichbar; Stand März 2019) besteht. Die Dissertation stellt ein generisches Computermodell bereit, um das Verhalten und die Populationsdynamik von Tieren zu untersuchen, welche saisonale Umweltbedingungen erfahren. Mit diesem Computermodell untersuche ich in der vorliegenden Thesis, wie Zugvögel auf verschiedene Szenarien veränderter Nahrungsverfügbarkeit reagieren, welche im Rahmen des globalen Wandels wahrscheinlich sind. Dabei werden ökologische und evolutionäre Zeitskalen berücksichtigt. Außerdem werden biologisch bedingte Einschränkungen und Zielkonflikte einbezogen, welche das einzelne Individuum erfährt, die aber letztendlich auch das Geschehen auf Populationsebene bestimmen. Weiterhin studiere ich mit dem erstellten Computermodell am Beispiel des Weißstorchs, wie sich feinskalige Zeitmuster in der Nahrungsverfügbarkeit auf Zugvögel auswirken. Solche Studien würden eine enorme experimentelle Herausforderung darstellen. Die im Rahmen dieser Dissertation entstandene frei verfügbare Modellierungs-Software kann nun für andere Taxa und verwandte Forschungsfragen eingesetzt werden. Nach meinen Ergebnissen ist im Zuge des globalen Wandels mit verstärkten Populationsabnahmen bei Zugvögeln zu rechnen, sowie mit Änderungen im zeitlichen Verhaltensablauf und nichtlinearen negativen Carry-over-Effekten. Dies verdeutlicht, wie wichtig es ist, die vom globalen Wandel betroffenen ökologischen Mechanismen näher zu erforschen sowie effektive Schutzmaßnahmen für Zugvögel zu entwickeln. Allgemein erhöht die Dissertation unser mechanistisches Verständnis davon, wie sich der globale Wandel auf bedrohte Zugvogelarten auswirkt und damit die globale Biodiversität beeinflusst. Die Forschungsergebnisse werden in einem abschließenden Synthese-Kapitel zusammenführend diskutiert. KW - global change KW - migratory birds KW - life-history theory KW - movement ecology KW - bird migration KW - optimal annual routine model KW - stochastic dynamic programming KW - full annual cycle KW - population dynamics KW - carry-over effects KW - white stork KW - behavioural ecology KW - adaptation KW - mechanistic model KW - energetics KW - behavioural timing KW - reproduction KW - globaler Wandel KW - Zugvögel KW - Lebenszyklustheorie KW - Bewegungsökologie KW - Vogelzug KW - "Optimal annual routine"-Modell KW - stochastisch-dynamische Optimierung KW - vollständiger Jahreszyklus KW - Populationsdynamik KW - Carry-over-Effekte KW - Weißstorch KW - Verhaltensökologie KW - Anpassung KW - mechanistisches Modell KW - Energetik KW - Verhaltens-Timing KW - Reproduktion Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-439256 ER - TY - JOUR A1 - Rosenbaum, Benjamin A1 - Raatz, Michael A1 - Weithoff, Guntram A1 - Fussmann, Gregor F. A1 - Gaedke, Ursula T1 - Estimating parameters from multiple time series of population dynamics using bayesian inference JF - Frontiers in ecology and evolution N2 - Empirical time series of interacting entities, e.g., species abundances, are highly useful to study ecological mechanisms. Mathematical models are valuable tools to further elucidate those mechanisms and underlying processes. However, obtaining an agreement between model predictions and experimental observations remains a demanding task. As models always abstract from reality one parameter often summarizes several properties. Parameter measurements are performed in additional experiments independent of the ones delivering the time series. Transferring these parameter values to different settings may result in incorrect parametrizations. On top of that, the properties of organisms and thus the respective parameter values may vary considerably. These issues limit the use of a priori model parametrizations. In this study, we present a method suited for a direct estimation of model parameters and their variability from experimental time series data. We combine numerical simulations of a continuous-time dynamical population model with Bayesian inference, using a hierarchical framework that allows for variability of individual parameters. The method is applied to a comprehensive set of time series from a laboratory predator-prey system that features both steady states and cyclic population dynamics. Our model predictions are able to reproduce both steady states and cyclic dynamics of the data. Additionally to the direct estimates of the parameter values, the Bayesian approach also provides their uncertainties. We found that fitting cyclic population dynamics, which contain more information on the process rates than steady states, yields more precise parameter estimates. We detected significant variability among parameters of different time series and identified the variation in the maximum growth rate of the prey as a source for the transition from steady states to cyclic dynamics. By lending more flexibility to the model, our approach facilitates parametrizations and shows more easily which patterns in time series can be explained also by simple models. Applying Bayesian inference and dynamical population models in conjunction may help to quantify the profound variability in organismal properties in nature. KW - Bayesian inference KW - chemostat experiments KW - ordinary differential equation KW - parameter estimation KW - population dynamics KW - predator prey KW - time series analysis KW - trait variability Y1 - 2019 U6 - https://doi.org/10.3389/fevo.2018.00234 SN - 2296-701X VL - 6 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Rodríguez Sánchez, Alejandra A1 - Wucherpfennig, Julian A1 - Rischke, Ramona A1 - Iacus, Stefano Maria T1 - Search-and-rescue in the Central Mediterranean Route does not induce migration BT - predictive modeling to answer causal queries in migration research JF - Scientific reports N2 - State- and private-led search-and-rescue are hypothesized to foster irregular migration (and thereby migrant fatalities) by altering the decision calculus associated with the journey. We here investigate this ‘pull factor’ claim by focusing on the Central Mediterranean route, the most frequented and deadly irregular migration route towards Europe during the past decade. Based on three intervention periods—(1) state-led Mare Nostrum, (2) private-led search-and-rescue, and (3) coordinated pushbacks by the Libyan Coast Guard—which correspond to substantial changes in laws, policies, and practices of search-and-rescue in the Mediterranean, we are able to test the ‘pull factor’ claim by employing an innovative machine learning method in combination with causal inference. We employ a Bayesian structural time-series model to estimate the effects of these three intervention periods on the migration flow as measured by crossing attempts (i.e., time-series aggregate counts of arrivals, pushbacks, and deaths), adjusting for various known drivers of irregular migration. We combine multiple sources of traditional and non-traditional data to build a synthetic, predicted counterfactual flow. Results show that our predictive modeling approach accurately captures the behavior of the target time-series during the various pre-intervention periods of interest. A comparison of the observed and predicted counterfactual time-series in the post-intervention periods suggest that pushback policies did affect the migration flow, but that the search-and-rescue periods did not yield a discernible difference between the observed and the predicted counterfactual number of crossing attempts. Hence we do not find support for search-and-rescue as a driver of irregular migration. In general, this modeling approach lends itself to forecasting migration flows with the goal of answering causal queries in migration research. KW - human behaviour KW - population dynamics Y1 - 2023 U6 - https://doi.org/10.1038/s41598-023-38119-4 SN - 2045-2322 VL - 13 IS - 1 PB - Macmillan Publishers Limited, part of Springer Nature CY - London ER - TY - GEN A1 - Reil, Daniela A1 - Rosenfeld, Ulrike M. A1 - Imholt, Christian A1 - Schmidt, Sabrina A1 - Ulrich, Rainer G. A1 - Eccard, Jana A1 - Jacob, Jens T1 - Puumala hantavirus infections in bank vole populations BT - host and virus dynamics in Central Europe T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background In Europe, bank voles (Myodes glareolus) are widely distributed and can transmit Puumala virus (PUUV) to humans, which causes a mild to moderate form of haemorrhagic fever with renal syndrome, called nephropathia epidemica. Uncovering the link between host and virus dynamics can help to prevent human PUUV infections in the future. Bank voles were live trapped three times a year in 2010–2013 in three woodland plots in each of four regions in Germany. Bank vole population density was estimated and blood samples collected to detect PUUV specific antibodies. Results We demonstrated that fluctuation of PUUV seroprevalence is dependent not only on multi-annual but also on seasonal dynamics of rodent host abundance. Moreover, PUUV infection might affect host fitness, because seropositive individuals survived better from spring to summer than uninfected bank voles. Individual space use was independent of PUUV infections. Conclusions Our study provides robust estimations of relevant patterns and processes of the dynamics of PUUV and its rodent host in Central Europe, which are highly important for the future development of predictive models for human hantavirus infection risk. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 957 KW - Myodes glareolus KW - population dynamics KW - Puumala virus seroprevalence KW - space use KW - survival Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431232 SN - 1866-8372 IS - 957 ER - TY - JOUR A1 - Reil, Daniela A1 - Binder, Florian A1 - Freise, Jona A1 - Imholt, Christian A1 - Beyrers, Konrad A1 - Jacob, Jens A1 - Krüger, Detlev H. A1 - Hofmann, Jörg A1 - Dreesman, Johannes A1 - Ulrich, Rainer Günter T1 - Hantaviren in Deutschland BT - Aktuelle Erkenntnisse zu Erreger, Reservoir, Verbreitung und Prognosemodellen JF - Berliner und Münchener tierärztliche Wochenschrift N2 - Hantaviruses are small mammal-associated pathogens that are found in rodents but also in shrews, moles and bats. Aim of this manuscript is to give a current overview of the epidemiology and ecology of hantaviruses in Germany and to discuss respective models for the prediction of virus outbreaks. In Germany the majority of human disease cases are caused by the Puumala virus (PUUV), transmitted by the bank vole (Myodes glareolus). PUUV is associated with the Western evolutionary lineage of the bank vole and is not present in the eastern and northern parts of Germany. A second human pathogenic hantavirus is the Dobrava-Belgrade virus (DOBV), genotype Kurkino; its reservoir host, the striped field mouse (Apodemus agrarius), is mostly occurring in the eastern part of Germany. A PUUV-related hantavirus is the rarely pathogenic Tula virus (TULV), that is associated with the common vole (Microtus arvalis). In addition, Seewis virus, Asikkala virus, and Bruges virus are shrew- and mole-associated hantaviruses with still unknown pathogenicity in humans. Human disease cases are associated with the different hantaviruses according to their regional distribution. The viruses can cause mild to severe but also subclinical courses of the respective disease. The number of human PUUV disease cases in 2007, 2010, 2012, 2015 and 2017 correlates with the occurrence of high levels of seed production of beech trees ("beech mast") in the preceding year. Models based on weather parameters for the prediction of PUUV disease clusters as developed in recent years need further validation and optimisation. in addition to the abundance of infected reservoir rodents, the exposure behaviour of humans affects the risk of human infection. The application of robust forecast models can assist the public health service to develop and communicate spatially and temporally targeted information. Thus, further recommendations to mitigate infection risk for the public may be provided. N2 - Hantaviren sind Kleinsäuger-assoziierte Krankheitserreger, die vor allem in Nagetieren, aber auch in Spitzmäusen, Maulwürfen und Fledermäusen vorkommen. Ziel dieser Arbeit ist es, einen aktuellen Überblick zur Epidemiologie und Ökologie der Hantaviren in Deutschland zu geben und Modelle zur Vorhersage von Virusausbrüchen zu diskutieren. In Deutschland werden die meisten humanen Erkrankungsfälle beim Menschen durch das von der Rötelmaus (Myodes glareolus) übertragene Puumalavirus (PUUV) verursacht. PUUV ist mit der westlichen evolutionären Linie der Rötelmaus assoziiert und fehlt im östlichen und nördlichen Teil Deutschlands. Ein zweites humanpathogenes Hantavirus ist das Dobrava-Belgrad-Virus (DOBV), Genotyp Kurkino, dessen Reservoir die vor allem im östlichen Teil Deutschlands vorkommende Brandmaus (Apodemus agrarius) ist. Ein PUUV-verwandtes Hantavirus ist das selten humanpathogene Tulavirus (TULV), das mit der Feldmaus (Microtus arvalis) assoziiert ist. Darüber hinaus wurden mit dem Seewis-, Asikkala- und Brugesvirus Spitzmaus- und Maulwurf-assoziierte Hantaviren mit noch unklarer Humanpathogenität gefunden. Die humanen Erkrankungen sind jeweils mit den verschiedenen Hantaviren in deren regionaler Verteilung assoziiert und können mild bis schwer, aber auch subklinisch verlaufen. Das Auftreten von Häufungen humaner, durch PUUV verursachter Erkrankungen in den Jahren 2007, 2010, 2012, 2015 und 2017 korreliert mit dem Auftreten einer starken Fruktifikation der Buche („Buchenmast“) im jeweiligen Vorjahr. Auf der Basis von Wetterparametern sind Modelle zur Vorhersage von PUUV-Erkrankungshäufungen entwickelt worden, die zukünftig validiert und optimiert werden müssen. Neben dem Ausmaß des Virusvorkommens im Reservoir wird das Risiko humaner Infektionen durch das Expositionsverhalten des Menschen beeinflusst. Durch die Anwendung von Prognosemodellen soll der öffentliche Gesundheitsdienst in die Lage versetzt werden, räumlich und zeitlich gezielte und sachgerechte Präventionsempfehlungen für die Bevölkerung abzugeben. T2 - Hantaviruses in Germany: current knowledge on pathogens, reservoirs, distribution and forecast models KW - early warning system KW - hantavirus KW - hantavirus disease KW - rodents KW - population dynamics KW - Frühwarn-System KW - Hantavirus KW - Hantavirus-Erkrankung KW - Nagetiere KW - Populationsdynamik Y1 - 2018 U6 - https://doi.org/10.2376/0005-9366-18003 SN - 0005-9366 SN - 1439-0299 VL - 131 IS - 11-12 SP - 453 EP - 464 PB - Schlütersche Verlagsgesellschaft mbH & Co. KG. CY - Hannover ER - TY - GEN A1 - Raatz, Michael A1 - van Velzen, Ellen A1 - Gaedke, Ursula T1 - Co‐adaptation impacts the robustness of predator–prey dynamics against perturbations T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 809 KW - disturbance KW - evolutionary rescue KW - population dynamics KW - stability KW - trait adaptation Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-442489 SN - 1866-8372 IS - 809 ER - TY - JOUR A1 - Raatz, Michael A1 - van Velzen, Ellen A1 - Gaedke, Ursula T1 - Co‐adaptation impacts the robustness of predator–prey dynamics against perturbations JF - Ecology and Evolution N2 - Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations. KW - disturbance KW - evolutionary rescue KW - population dynamics KW - stability KW - trait adaptation Y1 - 2019 U6 - https://doi.org/10.1002/ece3.5006 SN - 2045-7758 VL - 9 IS - 7 SP - 3823 EP - 3836 PB - John Wiley & Sons CY - Hoboken, NJ ER - TY - JOUR A1 - Pennekamp, Frank A1 - Iles, Alison C. A1 - Garland, Joshua A1 - Brennan, Georgina A1 - Brose, Ulrich A1 - Gaedke, Ursula A1 - Jacob, Ute A1 - Kratina, Pavel A1 - Matthews, Blake A1 - Munch, Stephan A1 - Novak, Mark A1 - Palamara, Gian Marco A1 - Rall, Bjorn C. A1 - Rosenbaum, Benjamin A1 - Tabi, Andrea A1 - Ward, Colette A1 - Williams, Richard A1 - Ye, Hao A1 - Petchey, Owen L. T1 - The intrinsic predictability of ecological time series and its potential to guide forecasting JF - Ecological monographs : a publication of the Ecological Society of America. KW - empirical dynamic modelling KW - forecasting KW - information theory KW - permutation entropy KW - population dynamics KW - time series analysis Y1 - 2019 U6 - https://doi.org/10.1002/ecm.1359 SN - 0012-9615 SN - 1557-7015 VL - 89 IS - 2 PB - Wiley CY - Hoboken ER - TY - THES A1 - Patra, Pintu T1 - Population dynamics of bacterial persistence T1 - Populationsdynamik von Bakterielle Persistenz N2 - The life of microorganisms is characterized by two main tasks, rapid growth under conditions permitting growth and survival under stressful conditions. The environments, in which microorganisms dwell, vary in space and time. The microorganisms innovate diverse strategies to readily adapt to the regularly fluctuating environments. Phenotypic heterogeneity is one such strategy, where an isogenic population splits into subpopulations that respond differently under identical environments. Bacterial persistence is a prime example of such phenotypic heterogeneity, whereby a population survives under an antibiotic attack, by keeping a fraction of population in a drug tolerant state, the persister state. Specifically, persister cells grow more slowly than normal cells under growth conditions, but survive longer under stress conditions such as the antibiotic administrations. Bacterial persistence is identified experimentally by examining the population survival upon an antibiotic treatment and the population resuscitation in a growth medium. The underlying population dynamics is explained with a two state model for reversible phenotype switching in a cell within the population. We study this existing model with a new theoretical approach and present analytical expressions for the time scale observed in population growth and resuscitation, that can be easily used to extract underlying model parameters of bacterial persistence. In addition, we recapitulate previously known results on the evolution of such structured population under periodically fluctuating environment using our simple approximation method. Using our analysis, we determine model parameters for Staphylococcus aureus population under several antibiotics and interpret the outcome of cross-drug treatment. Next, we consider the expansion of a population exhibiting phenotype switching in a spatially structured environment consisting of two growth permitting patches separated by an antibiotic patch. The dynamic interplay of growth, death and migration of cells in different patches leads to distinct regimes in population propagation speed as a function of migration rate. We map out the region in parameter space of phenotype switching and migration rate to observe the condition under which persistence is beneficial. Furthermore, we present an extended model that allows mutation from the two phenotypic states to a resistant state. We find that the presence of persister cells may enhance the probability of resistant mutation in a population. Using this model, we explain the experimental results showing the emergence of antibiotic resistance in a Staphylococcus aureus population upon tobramycin treatment. In summary, we identify several roles of bacterial persistence, such as help in spatial expansion, development of multidrug tolerance and emergence of antibiotic resistance. Our study provides a theoretical perspective on the dynamics of bacterial persistence in different environmental conditions. These results can be utilized to design further experiments, and to develop novel strategies to eradicate persistent infections. N2 - Das Leben von Mikroorganismen kann in zwei charakteristische Phasen unterteilt werde, schnelles Wachstum unter Wachstumsbedingungen und Überleben unter schwierigen Bedingungen. Die Bedingungen, in denen sich die Mikroorganismen aufhalten, verändern sich in Raum und Zeit. Um sich schnell an die ständig wechselnden Bedingungen anzupassen entwickeln die Mikroorganismen diverse Strategien. Phänotypische Heterogenität ist eine solche Strategie, bei der sich eine isogene Popolation in Untergruppen aufteilt, die unter identischen Bedingungen verschieden reagieren. Bakterielle Persistenz ist ein Paradebeispiel einer solchen phänotypischen Heterogenität. Hierbei überlebt eine Popolation die Behandlung mit einem Antibiotikum, indem sie einen Teil der Bevölkerung in einem, dem Antibiotikum gegenüber tolerant Zustand lässt, der sogenannte "persister Zustand". Persister-Zellen wachsen unter Wachstumsbedingungen langsamer als normale Zellen, jedoch überleben sie länger in Stress-Bedingungen, wie bei Antibiotikaapplikation. Bakterielle Persistenz wird experimentell erkannt indem man überprüft ob die Population eine Behandlung mit Antibiotika überlebt und sich in einem Wachstumsmedium reaktiviert. Die zugrunde liegende Popolationsdynamik kann mit einem Zwei-Zustands-Modell für reversibles Wechseln des Phänotyps einer Zelle in der Bevölkerung erklärt werden. Wir untersuchen das bestehende Modell mit einem neuen theoretischen Ansatz und präsentieren analytische Ausdrücke für die Zeitskalen die für das Bevölkerungswachstums und die Reaktivierung beobachtet werden. Diese können dann einfach benutzt werden um die Parameter des zugrunde liegenden bakteriellen Persistenz-Modells zu bestimmen. Darüber hinaus rekapitulieren wir bisher bekannten Ergebnisse über die Entwicklung solch strukturierter Bevölkerungen unter periodisch schwankenden Bedingungen mithilfe unseres einfachen Näherungsverfahrens. Mit unserer Analysemethode bestimmen wir Modellparameter für eine Staphylococcus aureus-Popolation unter dem Einfluss mehrerer Antibiotika und interpretieren die Ergebnisse der Behandlung mit zwei Antibiotika in Folge. Als nächstes betrachten wir die Ausbreitung einer Popolation mit Phänotypen-Wechsel in einer räumlich strukturierten Umgebung. Diese besteht aus zwei Bereichen, in denen Wachstum möglich ist und einem Bereich mit Antibiotikum der die beiden trennt. Das dynamische Zusammenspiel von Wachstum, Tod und Migration von Zellen in den verschiedenen Bereichen führt zu unterschiedlichen Regimen der Populationsausbreitungsgeschwindigkeit als Funktion der Migrationsrate. Wir bestimmen die Region im Parameterraum der Phänotyp Schalt-und Migrationsraten, in der die Bedingungen Persistenz begünstigen. Darüber hinaus präsentieren wir ein erweitertes Modell, das Mutation aus den beiden phänotypischen Zuständen zu einem resistenten Zustand erlaubt. Wir stellen fest, dass die Anwesenheit persistenter Zellen die Wahrscheinlichkeit von resistenten Mutationen in einer Population erhöht. Mit diesem Modell, erklären wir die experimentell beobachtete Entstehung von Antibiotika- Resistenz in einer Staphylococcus aureus Popolation infolge einer Tobramycin Behandlung. Wir finden also verschiedene Funktionen bakterieller Persistenz. Sie unterstützt die räumliche Ausbreitung der Bakterien, die Entwicklung von Toleranz gegenüber mehreren Medikamenten und Entwicklung von Resistenz gegenüber Antibiotika. Unsere Beschreibung liefert eine theoretische Betrachtungsweise der Dynamik bakterieller Persistenz bei verschiedenen Bedingungen. Die Resultate könnten als Grundlage neuer Experimente und der Entwicklung neuer Strategien zur Ausmerzung persistenter Infekte dienen. KW - Populationsdynamik KW - Antibiotikaresistenz KW - Antibiotika-Toleranz KW - Phänotypische Heterogenität KW - population dynamics KW - drug tolerance KW - antibiotic resistance KW - phenotypic heterogeneity Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-69253 ER -